Easy Trade Pro [Buy and Sell Strategy + Backtesting System]Hello Traders,
Easy Trade Pro is a comprehensive tool that combines multiple technical indicators into a single customizable one. This tool is the culmination of an extensive trading career, it is designed to help traders navigate the markets in any timeframe and financial asset, like Equities, Futures, Crypto, Forex and Commodities.
Before we deep dive into the comprehensive guide on what Easy Trade Pro is, let's kick off by showcasing the strategy used in this example. Please note, we have adopted an extremely conservative approach strictly following the Tradingview House Rules, which you can review here: www.tradingview.com
The backtest strategy parameters:
Currency pair: EUR USD
Timeframe: 15-min chart
Market: Spot, no leverage
Broker: FXCM
Trading range: 2022-09-01 07:30 — 2023-06-26 20:00
Backtesting range: 2022-08-31 23:00 — 2023-06-26 20:00
Initial Capital: $10,000
Buy Order Size: 20% of the capital, $2,000
Stop Loss: 0.50%
Sell orders: Four different take profits where we unload the position by 25% each time
Broker Fees: Commission set at 0.08$
Slippage: 10 ticks
Understanding FXCM Commissions and Setting Realistic Slippage for EUR/USD Spot Trading:
◉I would like to provide some clarity on the commission structure and slippage setting used in the study for trading the EUR/USD pair on the FXCM spot market. Based on the information available, FXCM charges a commission of $4.00 per standard lot (100,000) on both sides of the trade (meaning at open and close) for the EUR/USD pair. Since the study involve an order size of $2,000 USD, which is equivalent to 0.02 lots, the commission fee for one side of the trade (either buying or selling) would be calculated as $4.00 multiplied by 0.02, which is $0.08. This means that for each individual trade, whether it be a buy or sell, the commission fee would be $0.08.
◉As for slippage, it is crucial to account for the inherent uncertainty in the execution price due to market fluctuations. In the forex market, the EUR/USD pair is quoted with a precision of five decimal places, with the smallest price change being a "pipette" (0.00001). Given that slippage can vary based on market conditions, it is considered fair practice to use a slippage of around 10 ticks under normal market conditions for the EUR/USD pair. This allows for a more realistic representation of the execution price, especially in a liquid and fast-moving market such as forex.
More detailed information about FXCM fees structure in the link below:
docs.fxcorporate.com
Enter a Trade conditions:
For our buy order, we utilize a custom buy signal called 'Bullish Reversal'. A detailed explanation of this and other buy orders can be found later in the guide, specifically in section 1).
To enhance realism in our trading strategy, we have implemented a confirmation mechanism. When utilizing the strategy tester, you have the option to input a value to determine the number of confirmation candles to consider.
For example, if you set the input to 1, the system will check if the next candle following the signal meets the criteria for confirmation. If set to 2, the system will evaluate the second candle, and so on for higher values. The confirmation is determined by comparing the closing or opening price of the selected buy signal candle with the corresponding closing price of the confirmation candle.
In this case we choose as buy signal: 'Bullish Reversal' + 2 candle of confirmation
Exit a trade conditions:
On the sell side, we exit a trade in four different types of sell orders where we take profits. Inside '', you will encounter unique labels attributed to our custom sell signals. A detailed explanation of these sell orders can be found later in the guide, specifically in section 1). We used custom order called:
1TP 'Good Sell'
2TP 'Good Sell'
3TP 'Good Sell'
4TP 'Bearish Reversal' + 4 confirmation candles
Our confirmation logic, for sell signals, is applied only to 'Bearish Reversal' signal. The confirmation is determined by comparing the closing or opening price of the selected 'Bearish Reversal' candle with the corresponding closing price of the confirmation candle. In this case, we wait for the fourth candle from the 'Bearish Reversal' signal to confirm the sell trade.
Protect your capital:
This super-conservative study involves a clear low risk, with the use of $2,000, 20% of our capital. If the stop loss of 0.5% were triggered, we lose 10$, equating to 0.10% of $10,000 - thus affecting only 0.10% of our capital.
Super Conservative Approach & Results:
With 353 closed trades, we achieved a net profit of 2.03%, or $203.34$ relative to our initial $10,000 capital, and a win rate of 73.37%.
Less Conservative Approach & Results:
We could also consider increasing our risk to 0.5% of our capital per trade. We would maintain our stop loss at 0.50%, but we would need to use all our capital to enter the market. If the stop loss of 0.5% will be triggered, we would lose 50$, equating to 0.5% of $10,000.
In this scenario, our net profit would have increased to 10.15%, equivalent to $1015.
Please be aware:
While fully automated strategies can bring considerable advantages, they are not without their cons. For one, relying solely on an automated system may not take into account the potential confluence of other strategies or indicators, such as the significance of support and resistance zones. These elements often require a more nuanced, human understanding of the markets and cannot always be perfectly replicated by an algorithm.
Additionally, it's essential to remember that a significant percentage of traders are not consistently profitable. As such, prudent risk management, a conservative approach, and acceptance of a reasonable profit are crucial aspects of successful trading. While the allure of high returns can be tempting, the sustainability of your trading strategy should always take precedence. Achieving steady, reliable profits over time often outweighs the appeal of a risky, high-return strategy that could potentially lead to substantial losses.
So, while automation can be a powerful tool in your trading arsenal, it's also important to consider other strategies and factors. Always ensure you're managing your risk effectively and approaching trading with a realistic and informed perspective.
------------------------------------------------------------------------ Why Easy Trade Pro is Original? ----------------------------------------------------------------------------------
We developed Easy Trade Pro as a unique and comprehensive solution, and we decided to protect our code to preserve its originality. We invested significant time and effort into making it a realistic trading strategy simulator. The standout features that set Easy Trade Pro apart include:
☀ Versatile Stop Loss Mechanisms: Stop loss execution can be complex and often requires careful coding to work as intended. In most freely available open-source codes, stop losses are implemented using the Average True Range (ATR). ATR can be beneficial but has limitations:
☁ Lagging Indicator - Like most technical indicators, the ATR is a lagging indicator. This means it is based on past data, and so it may not accurately reflect future market volatility. If market conditions change rapidly, the ATR may not adjust quickly enough, potentially leading to suboptimal stop loss levels.
☁ No Directional Information - The ATR measures volatility, but it does not provide any indication of the direction of the trend. Therefore, it should not be used as a standalone tool for making trading decisions, but should be used in conjunction with other technical analysis tools that can provide directional cues.
☁ Inefficiency in Trending Markets - In strongly trending markets, ATR-based stops can sometimes be too far from the current price level. This could lead to larger losses if the price moves against your trade before hitting the stop loss. On the flip side, in less volatile, sideways markets, an ATR-based stop might be set too close to the entry point, leading to premature stop outs.
☁ Overoptimization Risk - If you're backtesting a trading strategy, there's a risk of overoptimizing your stop loss settings by fine-tuning them to past data. The best ATR multiplier that worked in the past might not necessarily work in the future, leading to potential performance issues.
☀ We countered these by implementing four different types of 'protect the trade' mechanisms:
✔ Fixed Percentage Stop Loss
✔ Trailing Stop Loss
✔ Stop Loss Moved to Entry Upon Reaching Certain Gain
✔ Stop Loss Moved to Entry Upon Reaching First Take Profit Order ("Custom Order").
☀ Dual Exit Strategy: We incorporated two distinct methods of exiting a trade. The first uses our custom signals, while the second triggers exit at a certain percentage of gain.
☀ Multiple Take Profit Orders: You have the flexibility to establish up to four different sell orders. This feature enables you to fractionate your exit strategy according to your needs. You can choose to trigger these fractions based on our custom signals or determine your own exit points by setting targeted gains at a fixed percentage.
☀ Confirmation Candle System: This feature enhances trade precision by requiring confirmation candles after a buy or sell signal. This confirmation, dependent on the next candle's closing price, helps reduce false signals and improves entry and exit points. While our confirmation system is applicable to all custom buy signals, it's solely dedicated for the bearish reversal when it comes to sell signals.
☀ Universal Compatibility: Easy Trade Pro's Strategy Tester works perfectly with any asset class. The code can handle different contract types, including the SPX contracts and fractional assets like Bitcoin. It's optimized to ensure proper execution of trades without rounding issues.
☀ Bullish and Bearish Reversal candles: Our method of detecting these pivotal candles combines conditions from buy and sell signals with pertinent divergences in Price, RSI, and Volume (OBV). The distinguishing factor, however, lies in recognizing significant shifts in market structure and liquidity grabs. To further enhance the credibility of our indicator, we've incorporated Bollinger Bands, serving as an additional layer in spotting potential trend reversals, particularly when aligned with long-wick candlesticks, engulfing patterns, and morning or evening star formations.
☀ Non-Repainting Indicator: Our indicator signals are designed not to repaint. Once a signal appears, it stays fixed, offering a reliable tool for your trading decisions.
================================================== EXTENSIVE TECHNICAL DESCRIPTION ====================================================
Easy Trade Pro is versatile, allowing you to analyze market trends across any financial asset. With its rigorous testing, our tool can be used confidently on any timeframe, from 1D to 1min, whether you prefer longer-term or shorter-term trades.
Although we recommend trading on timeframes between 1D and 1min, higher timeframes like 1W chart, can also provide broader insights.
Our study combines a variety of popular technical indicators, such as RSI, Stochastic RSI, MACD, DMI, Bollinger Bands as well as relevant EMAs. On the volume side OBV and MFI. Using a data-driven approach, “Easy Trade Pro” analyzes historical market trends to identify optimal ways to combine these indicators with significant divergences between price and oscillators. On top of that the code considers relevant changes in market structure and liquidity grabs, to generate reliable and accurate signals for potential buy and sell opportunities.
* ☎ --> Please not that MACD, BBs, and EMAs account for a minimal part of our script <--- ☎, If you're looking for a simpler tool, consider checking out our open-source indicator, 'RSI, SRSI, MACD, and DMI cross - Open source code'. You can find it here:
With our customizable system, traders will be able to identify:
1) Three types of buy signals🐂,💰,💎 and sell signals 🐻,🔨,💀
2) Bullish and bearish reversal candles with support and resistance lines
3) Bull and bear momentum signals
4) A function that utilizes Color bars to identify the strength of the trend
5) Three customizable moving averages
6) Alerts direct to your email or phone
7) Advanced and customizable settings menu
8) Our software also includes a backtesting system that that allows users to test their trading strategies on historical data, to check how they would have performed in real-world market conditions. This can help refine a trading strategy and make more informed decisions.
------------------------------------------------------------------------------ 1) BUY AND SELL SIGNALS ---------------------------------------------------------------------------------
Our buy and sell signals are generated using a custom combination of RSI, MFI, and Stochastic RSI levels, as well as relevant MACD and Stochastic RSI crosses. These indicators are carefully analyzed to identify potential trading opportunities and determine optimal entry and exit points for trades.
RSI (Relative strength index) measures the strength of a security's price action, while the SRSI (Stochastic Relative Strength Index) is a momentum oscillator that measures the current price relative to its high and low range over a set period. The Money Flow Index (MFI) is another momentum indicator that uses both price and volume data to measure buying and selling pressure. MACD (Moving Average Convergence Divergence) is a popular technical indicator used in financial markets to analyze price trends and momentum.
▶ With our system, you'll be able to identify three different levels of buy signals:
◉ The first level of buy signal is represented by a 🐂 emoji and is a "Good Buy". This signal indicates a possible buying opportunity. It indicates that could be a good opportunity to enter in a long trade. It's important to note that, the "Good Buy" signal can sometimes be supplemented with a green "Bull" text and a flag plotshape positioned beneath the signal. In these scenarios, we categorize this as a "Good Buy Bull" signal.
◉ The second level of buy signal is represented by a 💰 emoji and is a "Great Buy". This signal indicates a stronger buying opportunity than the "Good Buy" signal.
◉ The third and strongest buy signal is represented by a 💎 emoji and is an "Incredible Buy". This signal indicates a stronger buying opportunity than the "Good Buy" and "Great Buy" signals
▶ With our system, you'll be able to identify three different levels of sell signals:
◉ On the sell side, the first level is represented by a 🐻 emoji and is a "Good Sell". This signal indicates a possible selling opportunity. It indicates that could be a good opportunity to exit a trade or open a short position. It's important to note that, the "Good Sell" signal can occasionally be accompanied by a red "Bear" text and a flag plotshape positioned beneath the signal. In such instances, we refer to this as a "Good Sell Bear" signal.
◉ The second sell signal is represented by a 🔨 emoji and is a "Great Sell". This signal indicates a stronger selling opportunity than the "Good Sell" signal.
◉ The third and strongest sell signal is represented by a 💀 emoji and is an "Incredible Sell". This signal indicates a stronger selling opportunity than the "Good Sell" and "Great Sell" signals.
------------------------------------------2) "BULLISH AND BEARISH REVERSAL CANDLES PLUS SUPPORT AND RESISTANCE LINES" ------------------------------------------------
Bullish and bearish reversal candles are specific candles that have more probability to reverse the trend.
Our trading indicator is designed to identify bullish and bearish reversal candles. Our method of detecting these pivotal candles combines conditions from buy and sell signals with pertinent divergences in Price, RSI, and Volume (OBV). The distinguishing factor, however, lies in recognizing significant shifts in market structure and liquidity grabs. To further enhance the credibility of our indicator, we've incorporated Bollinger Bands, serving as an additional layer in spotting potential trend reversals, particularly when aligned with long-wick candlesticks, engulfing patterns, and morning or evening star formations.
These candles are represented by blue and orange colors respectively by default. Additionally, the indicator also uses lines that are drawn at either the opening or closing of candles to help identify pivot points of support or resistance. These candles, lines color or shape are customizable in the settings menu.
How can I benefit the most from bullish reversal candles? To make the most of bullish reversal candles, a powerful strategy is:
E.g, 1D chart - Wait for the next 1 or 2 candles to close above the support line linked to the bullish reversal candle. For lower timeframes, it is recommended to wait for 2 or 3 candles before making a trading decision. A good tip is also to look for other signals (confluence), like a buy signal. Traders should decide based on their risk tolerance.
Here below we can see an example of a bullish reversal candle in the BTC/USDT, 1D, chart. The system identify a bullish reversal candle (blue color), the next 2 candles are green and closed above the support blue line, in addition we have other bullish signals (confluence).
How can I benefit the most from bullish reversal lines? Bullish reversal lines can help traders to identify key level of support and maintain control of their position until a clear break below occurs.
In the example below we se how the price retrace to the support line:
After touching the price bounce up.
How can I benefit the most from bearish reversal candles? To make the most of bearish reversal candles, a powerful strategy is:
E.g, 1D chart - Wait for the next 1 or 2 candles to close below the resistance line linked to the bearish reversal candle. For lower timeframes, it is recommended to wait for 2 or 3 candles before making a trading decision. Traders should decide based on their risk tolerance.
Here below we can see an example of a bearish reversal candle in the ETH/USDT, 1D, chart. The system identify a bearish reversal candle (orange color), the next candle is red and closes below the resistance orange line. A good tip is also to look for other signals (confluence), like a sell signal.
How can I benefit the most from bearish reversal lines? Bearish reversal lines can help traders to identify key level of resistance and maintain control of their position until a clear break above occurs.
In the example below we se how the price bounce back to the resistance line and get rejected.
------------------------------------------------------------------------- 3) BULL AND BEAR MOMENTUM SIGNALS -----------------------------------------------------------------------
We analyzed factors such as buy or sell signals, long or short confirmation signals, DMI crossup or crossdown and breaks of market structure (BOS) or change of character (CHoCh) to determine the strength and direction of the trend. These study give us bull trend or bear trend signals that can help traders identify potential trading opportunities and make informed decisions.
These conditions are represented by a green word "BULL" and a flag shape below (bull momentum) and by a red word "BEAR" and a flag shape above (bear momentum) respectively by default. These plots shapes are customizable in the settings menu.
How can I benefit the most from bull momentum signals? To make the most of bull momentum signals, a powerful strategy is:
E.g, 1D chart - Look for confluence. If bull signal comes with a "Good Buy 🐂" in the same candle the signal is more strong. Another good combo is to look for a bullish reversal candle prior or after this signal, usually within a range of 1/2 candles. For lower timeframes, it is recommended to wait 2/3 candles before making a trading decision.
In the picture below we can see an example of a bull momentum signal in the US500, 1D, chart.
How can I benefit the most from bear momentum signals? To make the most of bear momentum signals, a powerful strategy is:
E.g, 1D chart - Look for confluence. If bear signal comes with a "Good Sell 🐻" in the same candle the signal is more strong. Another good combo is to look for a bearish reversal candle prior or after this signal, usually within a range of 1/2 candles. For lower timeframes, it is recommended to wait 2/3 candles before making a trading decision.
In the picture below we can see an example of a bear momentum signal in combo with a sell signal, NETFLIX, 1D, chart.
-------------------------------------------------------------- 4) "COLOR BARS THAT INDICATE THE STRENGTH OF THE TREND -----------------------------------------------------
This code is responsible for changing the color of the bars on a chart based on certain conditions. The gradient colors are defined for green and red, and the algorithm checks if the current bar is within a certain range of either a bearish reversal or bullish reversal candle and whether the price is above or below certain exponential moving averages or if important break of market structure occurs.
Ultimately, this feature helps traders visually identify potential trends and market shifts and avoid getting distracted by price fluctuations. Please note that every gradient of color can be customize by the user. We set 3 different bullish colors and 3 different bearish colors.
Below the picture of the settings menu related to the bar color.
----------------------------------------------------------------------5)THREE CUSTOMIZABLE MOVING AVERAGES ----------------------------------------------------------------------
You can choose up to three moving averages, any length and any type like SMA, EMA, WMA, HMA, RMA, SWMA and VWMA. Furthermore, you have the freedom to adjust the color and width of the lines to your preference.
Below the picture of the settings menu related to the moving averages.
----------------------------------------------------------------------6) ALERTS DIRECT TO YOUR EMAIL OR PHONE --------------------------------------------------------------------
Our alert feature sends real-time notifications directly to your email or phone when a signal is generated, allowing you to take immediate action and stay ahead of the market.
With our system, you first establish your own rules for trading in the strategy tester - this includes your criteria for entering and exiting trades.
Once you've defined these conditions, our system will start sending you alerts. These alerts will be triggered whenever your specified conditions are met. So, if the market matches your 'enter trade' conditions, you'll receive an alert prompting. Similarly, when your 'exit trade' conditions are met, you'll receive another alert.
Remember, these alerts are purely based on the conditions you set.
Once the condition is met, you will receive alerts directly to your email or phone when enter and exit a trade based on your custom conditions. To make sure you receive these notifications click on notifications tab.
---------------------------------------------------------------7) ADVANCED AND CUSTOMIZABLE SETTINGS MENU----------------------------------------------------------------------
We designed Easy Trade indicators with traders in mind, so it's user-friendly, easy to navigate and users can customize inputs, style, and colors of every feature in the indicator's settings menu.
-----------------------------------------------------------------------8) EASY TRADE PRO - BACKTESTING SYSTEM----------------------------------------------------------------------
Easy Trade Pro features a highly effective and realistic backtesting system, designed to mirror as closely as possible the real-world scenarios of entering and exiting trades.
Step 1:
Open the settings menu of the Indicator.
Once opened the settings menu click on properties.
Decide on the capital you wish to invest. Choose whether to use contracts or USD and determine the size of your orders. For the sake of realism, we recommend not exceeding 25% of your capital per order. However, if you decide to utilize your entire capital, make sure to adjust your stop loss accordingly. For instance, if you have a capital of 10K and use 10K with a stop loss at 2%, your potential loss would be $200. Conversely, if you use only 2K of your 10K capital with a stop loss at 10%, you would still lose the same 2% of your capital. To make your simulation even more authentic, consider incorporating broker fees or commissions into your calculations. For example, spot market fees are typically around 0.10%. If you're backtesting markets with low liquidity, consider factoring in slippage as well.
Step 2:
Navigate to the 'Inputs' section and scroll down until you come across 'Backtesting System - Strategy Test'. Once you locate this, click on the box and activate the 'USE STRATEGY SYSTEM' option by checking the tick box.
Also You will then need to set a 'Start Date' and 'End Date', establishing a specific time period during which you wish to test your strategy.
Otherwise you can consider to use the deep backtesting feature.
Step 3:
It's now time to establish the conditions for entering a trade. You can choose from five different types of custom buy signals: Good Buy, Good Buy Bull, Great Buy, Incredible Buy, and Bullish Reversal. Note that 'Great Buy' and 'Incredible Buy' are rare signals, so we advise against using them frequently in mechanical strategy tests; instead, consider them more for manual live tests. For more consistent results, we recommend using the other buy signals.
After determining your preferred buy signal, you can choose how many confirmation candles you wish to wait for before entering a trade. A 'confirmation' means that if the next candle closes above the opening or closing price of the chosen buy signal, it's considered a confirmation. This could be the opening or closing price, depending on whether the candle is green (close > open) or red.
You can set the number of confirmation candles in different time frames: below 2h, between 2h and 10h, and above 10h.
Step 4:
It's now time to safeguard your trade by managing risk. You can choose to implement a stop loss, expressed in percentage terms, or opt for a trailing stop. A trailing stop is a type of stop loss order that moves with the market price. It is designed to protect gains by enabling a trade to remain open and continue to profit as long as the market price is moving in a favorable direction. However, the trade closes if the market price changes direction by a specified amount (the 'trailing stop distance').
Additionally, you can minimize losses and move the stop loss to your entry point once the price reaches a certain percentage of profit. This strategy can help secure potential gains while limiting the potential for losses.
Step 5:
Now it's time to set the conditions for exiting the trade. You have the option to divide your exit into a maximum of four parts, with each part representing 25% of the position size. For each take profit point, you can choose from three different custom sell signals: Good Sell, Good Sell Bear, and Bearish Reversal.
Similarly, the concept of confirmation candles also applies here, but in this case, the candles are not closing above. A 'confirmation' for a sell signal means that if the next candle closes below the opening or closing price of the selected sell signal, it's considered a confirmation. This could be the opening or closing price, depending on whether the candle is green (open > close) or red (close < open).
So, when you're looking to sell, a confirmation would occur if the next candlestick's closing price is lower than the opening or closing price of the candlestick that triggered the sell signal. This indicates a potential bearish trend, providing the confirmation to execute the sell order.
Additionally, we've introduced a feature that allows you to move your stop loss to the entry point whenever the first take profit (1TP) is reached, which equates to hitting one custom sell signal.
Step 6:
We've also designed an alternative method for taking profits. With this approach, you can choose to exit your position once a fixed percentage gain from the entry point is reached. For instance, you might decide to exit when a 10% profit is achieved. Similarly to the previous method, this approach allows you to choose up to four exit points and determine the proportion of your position you want to close at each stage.
Conclusion:
Easy Trade Pro provides users with various options for entering and exiting trades. To effectively utilize the indicator, we strongly recommend conducting thorough backtesting and considering the results across your preferred trading pairs. It is advisable to analyze a substantial number of trades, ideally exceeding 100 trades, to obtain reliable insights into the indicator's performance. This approach will help you gain a better understanding of how Easy Trade Pro aligns with your trading strategy and objectives.
❗Keep attention❗
It is important to note that no trading indicator or strategy is foolproof, and there is always a risk of losses in trading. While this indicator may provide useful information for making conclusions, it should not be used as the sole basis for making trading decisions. Traders should always use proper risk management techniques and consider multiple factors when making trading decisions.
It is also important to be aware of the limitations of simulated performance results. Hypothetical or simulated results do not represent actual trading, and since trades have not been executed, results may be over- or under-compensated for market factors such as lack of liquidity. Simulated trading programs are also designed with the benefit of hindsight, and no representation is being made that any account will achieve profits or losses similar to those shown. Therefore, our indicators are for informative purposes only and not intended to be used as financial advice.
We encourage traders to use our indicators as part of a well-rounded trading strategy and to always be aware of the risks involved in trading. Remember that past performance is not indicative of future results and always trade responsibly.
Analisi trend
Ta StrategyHello guys
This script follows traditional technical indicators
MACD, ADX, RSI and pivot points
If the price is above the resistance and the MACD has crossover ,and the RSI 14 is above 50
ADX is higher than 20, and DI+ is higher than DI-. This is a buy signal and vice versa for a sell signal
The script moves the stop loss to the entry price after the first target is reached
You can specify the quantity you want to sell when the price reaches the first target
There are also options like if you want the script to entry long or short, or both
you can reverse the strategy if it does not work well
If you want to inquire about any details, please let me know in the comments
METRIC-TREND-TRADERThis script is a Fully Automated trading script meant to be used with "Oanda" broker and the plug-ins for algorithmic trading automation.( FOREX ONLY)
This script is meant to capture "TREND FOLLOWING " for intraday charts (1hour) preferably and will hold for days / weeks .trading on forex markets.
(The combination of indicators includes a short high and low price channel and a longer term high and low price channel)
This script is original in description as being automated to try and capture dynamic trending markets with both long and short fractal price channels. although trend trading is not an original concept. trend trading with this dynamic indicator allows the user visualize both short term and longer term price action at the same time, helping to make better trading decisions. the channels are designed to buy breakouts in the direction of the longer term trend while trailing stop a built-in stop loss that allows normal market movement while attempting to lock in flexible profits.
The concept of this indicator is be able to quickly visualize trends by high lighting the large green areas beneath price "when trending long" which is the difference between the (user defined) short term lows and the (user defined) Long period price lows.
For "down trending" markets a large red area above price will be displayed and this is the difference between the (user defined) short term highs and the (user defined) long term highs.
This strategy uses a lower than reward profile to jump in direction of market moves for continuation,
(1 risk to 4 reward)
in the likelihood the instrument will continue (example) 200 pips before it reverts 50 pips in the counter direction.
This strategy should only be used in markets that you believe are "TRENDING" at the time of trading otherwise you risk trend trading a range market.
This script uses a (user defined period) of short term high and low price ( green/red color) and (user defined period) Long Term high and low price (green/red) chosen in the indicator settings menu.
The default parameters are 10 with a (minimum of 1 and maximum of 10000) for the short term channel and 50 with a (minimum of 1 and maximum of 10000) for the long term price channel , the default parameters = roughly 2 days "long term" and 10 hours "short term" of price action on the (1 hour) chart.
Strategy entries and exits , for Long trades the trade will be entered if the short term high crosses above the Long Term high and the Short term low is not equal to the Long term low . the trade will exit if profit or stop loss are hit or if the Short term low crosses under the long term low.
For Short trades the trade will enter short if , the short term low crosses under the long term low and the short term high is not equal to the long term high. the trade will exit if profit or stop loss are hit or the short term high crosses over the long term high
"The default parameters should be kept unless you fully understand the complete strategy"
There are two very important inputs to be selected at the user setting menu "Long Only " and "Short Only" if you are looking to place long trades only select "Long Only" or for short trades select " Short Only" it is not recommended to keep both selected as it will trade both sides!
When the trade is entered a red , a blue and green horizontal dotted line will appear on the chart.
the blue line is the strategy entry price , the red line is the stop loss price , and the green line is the take profit price . the colors will invert if the trade is long or short.
(Setting alerts should be done in the indicator settings menu, and the parameters you chose will determine the stop loss/target and the amount of "units = (position size)" you wish to trade for the (forex only) markets. using "alert() function calls only" is the only alert that should be used with this strategy.
(note : when "alert() function calls only" is set two messages will be sent, one closing any open position in the opposite direction and one placing the new order regardless if you are currently in a trade or not)
Trade targets , stoploss and trade position size are a user defined variables entered in the indicator settings menu. (target pips minimum 0 and a maximum of 1000)(stop pips minimum of 0 and maximum of 1000)
Back test date range is included in the script for back testing different data periods.
the back ground will be colored a transparent navy blue if the period you are looking trading is with in the date range( note: to place live trades the end date will need to be in the future)
this is also adjustable in the settings menu
The avoid spread filter is a user defined time in which the spread is typically higher than average, applying this filter avoids trades in the specified time. When this filter is applied there will be a transparent red back ground color in the specified time.
Back test default setting are equivocal to OANDA:USDJPY
at the time of this publication placing trades with the "Oanda" broker are as follows , USD units = 2000 equal 2000 USD position size . "Oanda" current leverage is 20 to 1 for this particular pair and commission is paid in spread (1.4) pips = 0.19 USD per trade , Margin required for the trade is 100.0 USD , Position sizing = 10% of a 1000 USD account.
OANDA:USDJPY
Volume-Weighted Supertrend Strategy [wbburgin]This is a script that can be used as a strategy or a standalone indicator.
The Volume-Weighted Supertrend is a supertrend based on a rolling VWAP, instead of a normal price source. The strategy has two components - a supertrend based off of this VWAP (shown on the chart) and a supertrend from volume itself (not plotted on the chart directly). The supertrend from volume is an example of my "Supertrend Any Source" indicator, where a custom ATR is created from non-OHLC data; this is available as both a separate public script and also in my "wbburgin_utils" library for you to use in your own script creation.
The supertrend from volume acts as a confirmation filter for the VWAP-supertrend shown on-chart. If the volume supertrend is trending up and the VWAP-based supertrend is also trending up, a buy signal is generated. Likewise, if the volume supertrend is trending down and the VWAP-supertrend is trending down, a sell signal is generated. The colors are based off of whether both supertrends are trending up or down: green for both up, blue for only price up, orange for only price down, and red for both down.
The settings enable you to change the volume length and the ATR length separately, as well as the multiplier and the source for the price supertrend. If you load the indicator for the first time and see no entries and exits, this is because "Show Strategy Entries and Exits" is disabled in the settings. This is if you plan on using the strategy as an indicator and don't want to be bothered by the entry and exit symbols on the chart. Additionally, for those who like clean charts (like me), you can turn all the labels off in the settings, as well as the highlighting.
My default strategy settings for the strategy results shown below are as follows: 5% equity per trade, 5 degrees of pyramiding, commissions of 0.08% per trade. This strategy doesn't come with stops yet, so please be aware of that before using it to trade - I highly suggest you create your own stops based off of your R/R ratio and personal risk tolerance. Additionally, it works best on trending assets (b/c of the supertrends) with high volume. This might mean it does not work as well on lower timeframes.
DCA-Integrated Trend Continuation StrategyIntroducing the DCA-Integrated Trend Continuation Strategy 💼💰
The DCA-Integrated Trend Continuation Strategy represents a robust trading methodology that harnesses the potential of trend continuation opportunities while seamlessly incorporating the principles of Dollar Cost Averaging (DCA) as a risk management and backup mechanism. This strategy harmoniously blends these two concepts to potentially amplify profitability and optimize risk control across diverse market conditions.
This strategy is well-suited for both trending and ranging markets. During trending markets, it aims to capture and ride the momentum of the trend while optimizing entry points. In ranging markets or pullbacks, the DCA feature comes into play, allowing users to accumulate more assets at potentially lower prices and potentially increase profits when the market resumes its upward trend. This cohesive approach not only enhances the overall effectiveness of the strategy but also fosters a more resilient and adaptable trading approach in ever-changing market dynamics.
💎 How it Works:
▶️ The strategy incorporates a customizable entry signal based on candlestick patterns, enabling the identification of potential trend continuation opportunities. By focusing on consecutive bullish candles, it detects the presence of bullish momentum, indicating an optimal time to enter a long position.
To refine the precision of the signals, traders can set a specific percentage threshold for the closing price of the candle, ensuring it is above a certain percentage of its body. This condition verifies strong bullish momentum and confirms significant upward movement within the candle, thereby increasing the reliability of the signal.
In addition, the strategy offers further confirmation by examining the relationship between the closing price of the signal candle and its previous candles. If the closing price of the signal candle is higher than its preceding candles, it provides an additional layer of assurance before entering a position. This approach is particularly effective in detecting sharp movements and capturing significant price shifts, as it focuses on identifying instances where the closing price shows clear strength and outperforms the previous candle's price action. By prioritizing such occurrences, the strategy aims to capture robust trends and capitalize on notable market movements.
▶️ During market downturns, the strategy incorporates intelligent management of price drops, offering flexibility through fixed or customizable price drop percentages. This unique feature allows for additional entries at specified drop percentages, enabling traders to accumulate positions at more favorable prices.
By strategically adjusting the custom price drop percentages, you can optimize your entry points to potentially maximize profitability. Utilizing lower percentages for initial entries takes advantage of price fluctuations, potentially yielding higher returns. On the other hand, employing higher percentages for final entries adopts a more cautious approach during significant market downturns, emphasizing enhanced risk management. This adaptive approach ensures that the strategy effectively navigates challenging market conditions while seeking to optimize overall performance.
▶️ To enhance performance and mitigate risks, the strategy integrates average purchase price management. This feature dynamically adjusts the average buy price percentage decrease after each price drop, expediting the achievement of the target point even in challenging market conditions. By reducing recovery times and ensuring investment safety, this strategy optimizes outcomes for traders.
▶️ Risk management is at the core of this strategy, prioritizing the protection of capital. It incorporates an account balance validation mechanism that conducts automatic checks prior to each entry, ensuring alignment with available funds. This essential feature provides real-time insights into the affordability of price drops and the number of entries, enabling traders to make informed decisions and maintain optimal risk control.
▶️ Furthermore, the strategy offers take profit options, allowing traders to secure gains by setting fixed percentage profits from the average buy price or using a trailing target. Stop loss protection is also available, enabling traders to set a fixed percentage from the average purchase price to limit potential losses and preserve capital.
▶️ This strategy is fully compatible with third-party trading bots, allowing for easy connectivity to popular trading platforms. By leveraging the TradingView webhook functionality, you can effortlessly link the strategy to your preferred bot and receive accurate signals for position entry and exit. The strategy provides all the necessary alert message fields, ensuring a smooth and user-friendly trading experience. With this integration, you can automate the execution of trades, saving time and effort while enjoying the benefits of this powerful strategy.
🚀 How to Use:
To effectively utilize the DCA-Integrated Trend Continuation Strategy, follow these steps:
1. Choose your preferred DCA Mode - whether by quantity or by value - to determine how you want to size your positions.
2. Customize the entry conditions of the strategy to align with your trading preferences. Specify the number of consecutive bullish candles, set a desired percentage threshold for the close of the signal candle relative to its body, and determine the number of previous candles to compare with.
3. Adjust the pyramiding parameter to suit your risk tolerance and desired returns. Whether you prefer a more conservative approach with fewer pyramids or a more aggressive stance with multiple pyramids, this strategy offers flexibility.
4. Personalize the price drop percentages based on your risk appetite and trading strategy. Choose between fixed or custom percentages to optimize your entries in different market scenarios.
5. Configure the average purchase price management settings to control the percentage decrease in the average buy price after each price drop, ensuring it aligns with your risk tolerance and strategy.
6. Utilize the account balance validation feature to ensure the strategy's actions align with your available funds, enhancing risk management and preventing overexposure.
7. Set take profit options to secure your gains and implement stop loss protection to limit potential losses, providing an additional layer of risk management.
8. Use the date and time filtering feature to define the duration during which the strategy operates, allowing for specific backtesting periods or integration with a trading bot.
9. For automated trading, take advantage of the compatibility with third-party trading bots to seamlessly integrate the strategy with popular trading platforms.
By following these steps, traders can harness the power of the DCA-Integrated Trend Continuation Strategy to potentially maximize profitability and optimize their trading outcomes in both trending and ranging markets.
⚙️ User Settings:
To ensure the backtest result is representative of real-world trading conditions, particularly in the highly volatile Crypto market, the default strategy parameters have been carefully selected to produce realistic results with a conservative approach. However, you have the flexibility to customize these settings based on your risk tolerance and strategy preferences, whether you're focusing on short-term or long-term trading, allowing you to potentially achieve higher profits. The backtesting was conducted using the BTCUSDT pair in 15-minute timeframe on the Binance exchange. Users can configure the following options:
General Settings:
- Initial Capital (Default: $10,000)
- Currency (Default: USDT)
- Commission (Default: 0.1%)
- Slippage (Default: 5 ticks)
Order Size Management:
- DCA Mode (Default: Quantity)
- Order Size in Quantity (Default: 0.01)
- Order Size in Value (Default: $300)
Strategy's Entry Conditions:
- Number of Consecutive Bullish Candles (Default: 3)
- Close Over Candle Body % (Default: 50% - Disabled)
- Close Over Previous Candles Lookback (Default: 14 - Disabled)
- Pyramiding Number (Default: 30)
Price Drop Management:
- Enable Price Drop Calculations (Default: Enabled)
- Enable Current Balance Check (Default: Enabled)
- Price Drop Percentage Type (Default: Custom)
- Average Price Move Down Percentage % (Default: 50%)
- Fixed Price Drop Percentage % (Default: 0.5%)
- Custom Price Drop Percentage % (Defaults: 0.5, 0.5, 0.5, 1, 3, 5, 5, 10, 10, 10)
TP/SL:
- Take Profit % (Default: 3%)
- Stop Loss % (Default: 100%)
- Enable Trailing Target (Default: Enabled)
- Trailing Offset % (Default: 0.1%)
Backtest Table (Default: Enabled)
Date & Time:
- Date Range Filtering (Default: Disabled)
- Start Time
- End Time
Alert Message:
- Alert Message for Enter Long
- Alert Message for Exit Long
By providing these customizable settings, the strategy allows you to tailor it to your specific needs, enhancing the adaptability and effectiveness of your trading approach.
🔐 Source Code Protection:
The source code of the DCA-Integrated Trend Continuation Strategy is designed to be robust, reliable, and highly efficient. Its original and innovative implementation merits protecting the source code and limiting access, ensuring the exclusivity of this strategy. By safeguarding the code, the integrity and uniqueness of the strategy are preserved, giving users a competitive edge in their trading activities.
DCA EMA Simple Bot [Starbots]
This is a simple idea of DCA trading on EMA crosses. Strategy is not repainting.
The difference between this and any other strategy is, that this script allows you to preset DCA buy triggers at desired levels and customize each DCA order size independently. Alerts are working, this strategy is easily used for automatic trading.
I mainly trade on Cryptohopper, Pionex, 3commas. This was created for community, alerts are working and non-repainting. Should work on any other as well.
Trading Condition:
It's buying when Fast EMA crosses up Slow EMA. Set your paramters.
It's selling if EMA's crosses back, signaling a sell. Optional.
DCA:
You can enter DCA on 20 custom levels or layers. It buys DCA when price hits the plotted blue line on the chart that's set by input % triggers. (buy 1st DCA at 2% drop, buy 2nd DCA at 5% drop,...)
Set your Inital Capital and Pyramiding in Properties tab, Initial Order Size and DCA Order Size (lot1,lot2,lot3,..), Order Type are changed in strategy inputs.
-By default you can see that we buy when EMA's cross up and signal a buy for 10% of equity, if market is dropping you will then place a first DCA order ( 20% equity) at 2% drop (lower) from initial order. If market keeps dropping you have more DCA levels where you can buy and average down your holding position. For selling you can use Take profit and Stop Loss targets that averages down multiple open positions, it will sell it once it reaches your desirable Take Profit and close a deal. You can also close your trade if EMA signals a sell.
Pyramiding - number of orders you can open at a time
Your first buy order is pyramiding 1. To allow it to buy 1 DCA or merge one time, set pyramding to 2.
Want to DCA 10 times? Set pyramiding at 11. (+1 always)
More features:
- Profit Calendar
- Show Balance label before every new trade
- DCA table - visualize how much of your investment is used in trades. If a background of the table is green you are okay, if the background color is red - you are using more money for orders than you actually have.
Buy Orders << Strategy Equity/Capital
- Show / Hide DCA lines - if your chart processing is getting slow you should hide some DCA levels to speed it up
- Backtesting Range - for testing the strategy in different time windows
- Alerts
When all trades are closed on your chart, winning rate of the strategy is 100% actually.
Win rate is shown differently as it's actually closing and opening every trade individually by default in TradingView system. We merge positions together and average it down into one big position to later sell for a profit (DCA).
You use this Trading Algorithm at your own risk. Do not trade before testing or invest something you cannot afford to lose on markets.
HK Percentile Interpolation One
This script is designed to execute a trading strategy based on Heikin Ashi candlesticks, moving averages, and percentile levels.
Please note that you should keep your original chart in normal candlestick mode and not switch it to Heikin Ashi mode. The script itself calculates Heikin Ashi values from regular candlesticks. If your chart is already in Heikin Ashi mode, the script would be calculating Heikin Ashi values based on Heikin Ashi values, which would produce incorrect results.
The strategy begins trading from a start date that you can specify by modifying the `startDate` parameter. The format of the date is "YYYY MM DD". So, for example, to start the strategy from January 1, 2022, you would set `startDate = timestamp("2022 01 01")`.
The script uses Heikin Ashi candlesticks, which are plotted in the chart. This approach can be useful for spotting trends and reversals more easily than with regular candlestick charts. This is particularly useful when backtesting in TradingView's "Rewind" mode, as you can see how the Heikin Ashi candles behaved at each step of the strategy.
Buy and sell signals are generated based on two factors:
1. The crossing over or under of the Heikin Ashi close price and the 75th percentile price level.
2. The Heikin Ashi close price being above certain moving averages.
You have the flexibility to adjust several parameters in the script, including:
1. The stop loss and trailing stop percentages (`stopLossPercentage` and `trailStopPercentage`). These parameters allow the strategy to exit trades if the price moves against you by a certain percentage.
2. The lookback period (`lookback`) used to calculate percentile levels. This determines the range of past bars used in the percentile calculation.
3. The lengths of the two moving averages (`yellowLine_length` and `purplLine_length`). These determine how sensitive the moving averages are to recent price changes.
4. The minimum holding period (`holdPeriod`). This sets the minimum number of bars that a trade must be kept open before it can be closed.
Please adjust these parameters according to your trading preferences and risk tolerance. Happy trading!
Premium Smart Exit HMA [ByteBoost]The Premium Smart Exit HMA strategy is designed for fast-paced trend detection and is well-suited for small trades in highly volatile markets. It utilizes the Hull Moving Average (HMA) as a signal to execute trades and offers customizable inputs for price calculation, period settings, and stop loss/take profit levels. The strategy aims to reduce lag associated with traditional moving averages, allowing it to catch trends quickly.
Development Notes
This Strategy was developed with the PineScript language, version 5. The aim of the strategy is to provide a trading system that catches fast trend reversals and uses a modified version of the Hull Moving Average. The HMA adeptly adapts to swift variations in price movements while offering better smoothing and utilizes a user selected moving averages, mitigating the smoothing effect and is controlled with a custom weight design.
Features
Customizable trading periods.
Customizable stop loss and take profit levels.
Adjustable date range for backtesting.
Allows setting of initial capital, commission type and value.
Provides visual aids for better understanding of the market trends.
Customize the visuals of the strategy.
Strategy Description
The Smart Exit HMA strategy offers the flexibility to use various types of moving averages, allowing customization of inputs for price calculation, period settings, and stop loss/take profit levels. The strategy relies on the Hull Moving Average (HMA) as a signal to execute trades. However, you have control over the signal frequency by selecting your preferred period value, which determines the number of candles used in the average calculation. This allows you to adapt the strategy to market tendencies and increase its effectiveness during clear trends.
The Smart Exit HMA strategy is designed to minimize lag associated with traditional moving averages, enabling it to respond more quickly to recent price movements based on your chosen period. It's worth noting that the strategy plots two lines on the graph: the average line and the square root line. Buy and sell signals are generated when both lines intersect, indicating favorable trading opportunities.
Inputs/Settings
Capital - If using any leverage multiply the amount of money to invest by the leverage, else input the amount to be invested in every trade.
Start date - The date from which the strategy should begin its analysis. Leave unchanged to start from the earliest available date based on your account's plan.
End date - The date until which the strategy should conduct its analysis. Leave unchanged to continue until the current date.
Period - The lookback period for the moving average calculation, a longer period will translate into fewer trades that last longer.
Stop loss - Allows the use of a stop loss for all trades.
Take profit - Activates the use of a take profit for all trades.
Stop loss value - The distance from the entry price at which the strategy should exit to prevent further losses.
Take profit value - The distance from the entry price at which the strategy should exit to secure profits.
Take profit % - The percentage of the capital to take as profit.
Stop loss % - The percentage of the capital to set as the maximum loss.
Candles exit - The minimum number of candles before the strategy is allowed to close a trade.
Candles change - The minimum number of candles before the strategy is allowed to change the current trend.
Moving average type - Determines the preprocessing method applied prior to utilizing the HMA.
Custom weight - Enables the utilization of a personalized weighting system for the HMA. If chosen, ensure that the sum of all weights equals 1.
Open weight - Determines the weight assigned to the candle's open value.
Close weight - Specifies the weight assigned to the candle's close value.
High weight - Sets the weight attributed to the candle's high value.
Low weight - Determines the weight assigned to the candle's low value.
Highlighter - Light coloring between the trend and average price of each bar.
Signal labels - View the labels indicating a new long or short position.
Exit labels - Displays the labels indicating exit points.
Color long - Sets the color scheme for a new long position.
Color short - Sets the color scheme for a new short position.
Color exit - Decides the color scheme for the exit tag and cross shown.
Indicator Visuals
The strategy plots the two trendlines on the chart and changes its color based on its direction. It also plots shapes on the chart to denote potential buy (Long) and sell (Short) points where the signals of short and long will appear, as well as crosses for the exit points.
Strategy Alerts
The strategy does not include built-in alerts. However, alerts can be added using the TradingView interface based on the strategy's buy, sell and exit conditions. This way you will be able to receive notifications on your computer or phone when a new signal goes out.
Details
Repainting: It is important to mention that the strategy can mark an uptrend signal during a candle and disappear at the end of it, so please just put long or short when the buy/sell conditions are followed and marked by the strategy at the end of each candle.
Conclusion
The Premium Smart Exit HMA is a versatile strategy that combines the benefits of the Hull Moving Average with adjustable parameters to suit individual trading styles. It offers a combination of speed and smoothness, which can be beneficial in volatile markets.
Disclaimer
This strategy is provided as-is, with no guarantee of profits or responsibility for losses. Trading involves risk, and you should only trade with money you can afford to lose. Always conduct your own research and consider your financial situation before engaging in trading.
Basic PRISM Algorithm [ByteBoost]The Basic ByteBoost PRISM strategy is designed to operate in various market conditions by leveraging the concept of brownian motion theory, which refers to the unpredictable movement of particles suspended in a fluid. This characteristic of random motion can be effectively utilized for analyzing time series data, such as market candles. Based on this notion, we are making the following assumptions regarding the market.
The stock price exhibits characteristics of Brownian motion.
The stock price is distributed in a log-normal pattern.
Volatility remains constant over time.
Options can only be exercised upon expiration.
Risk-free interest does not fluctuate over time.
There are no random or arbitrary opportunities present in the market.
Development Notes
This Strategy was developed with the PineScript language, version 5. This indicator, and most of the descriptions below, were derived largely from the TradingView reference manual. Feedback and suggestions for improvement are more than welcome, as well as recommended input settings and best practices to assist and guide new users effectively.
Features
The ByteBoost PRISM indicator is capable of analyzing multiple aspects of market behavior simultaneously such as:
Detection of potential trend reversals.
Assessment of trend strength and market sentiment.
Identification of stop loss levels.
Discovery of potential entry and exit points.
Ensuring compatibility and effectiveness with other indicators.
Visualization of strategy using historical data.
Strategy Description
PRISM is an all in one strategy that allows the visualization of entry and exit points as well as the historical performance for every set of parameters. PRISM is a slow paced indicator recommended for the 1h timeframe, because it operates on the belief that markets move in a Brownian motion, for which it leaves enough space and time for the market to decide a trend and catch it at the right time as well as finding appropriate exits given the trend.
PRISM can exist in either an uptrend or downtrend state, but it does not necessarily imply that it reflects the true trend being observed. Instead, it emphasizes capturing significant movements and capitalizing on them by utilizing oscillator levels and exit points calculated based on oversold or overbought values, along with the volatility associated with these movements.
Usage
To use this strategy it is first needed to select a correct set of inputs that correspond to the market you are using, the extra, win difference and oscillator length are dependent on the current market and the average price it manages, so these inputs need to be modified for every pair of assets used.
The long and short tags signify the opportune moment to initiate a new position in the market, whether it's a long or short position, respectively. The exit tags indicate when these positions should be closed. If no exits occur before a new long or short position emerges, it is essential to conclude the existing position and commence a new one in the opposite direction.
Regarding exits, up to two exits can be executed for each movement. The user has the flexibility to determine how these exits are utilized. In the input section, a specific percentage of equity can be selected to be sold during the first exit. If set to 100%, only a single exit will be presented. Otherwise, the remaining equity will be sold during the second exit or at the next trend reversal depending on which action occurs first.
In case the user requires additional exits beyond the initial two, the alternative exits option can be activated in the inputs. This will provide access to supplementary exits, although they may be less advisable compared to the primary exits.
Inputs / Settings
Capital - If using any leverage multiply the amount of money to invest by the leverage, else input the amount to be invested in every trade.
Start date - The date from which the strategy should begin its analysis. Leave unchanged to start from the earliest available date based on your account's plan.
End date - The date until which the strategy should conduct its analysis. Leave unchanged to continue until the current date.
Extra - The minimum gain required in the market to trigger an exit opportunity. It can be a negative number to allow exits at a loss, potentially minimizing losses.
First exit % - If an exit is decided to be partial, it is very likely that there will be a second exit, this parameter determines the percentage of equity to be sold at the first exit. Note that a second exit may not always be applicable.
Win difference - The minimum difference between the entry point and the first exit to determine whether it should be a full exit or a partial exit, as the exit price approaches the entry price, the probability of a trend reversal increases, a full exit is beneficial.
Oscillator - Enables or disables the main oscillator, which helps determine entry points. Not all assets may benefit from this parameter.
Oscillator length - Specifies the number of candles considered for the entry points oscillator.
Highlighter - Applies a light color between the trend and average price of each bar.
Labels - Displays all the labels on the chart indicating trends, positions and exits.
Candle color - Color codes the inside of the candles with the current signal.
Oscillator points - Adds visual dots to indicate when the oscillator has changed its trend.
Color uptrend - Determines the color scheme for identifying uptrend movements.
Color downtrend - Determines the color scheme for identifying downtrend movements.
Color long - Sets the color scheme for a new long position.
Color short - Sets the color scheme for a new short position.
Color exit - Decides the color scheme for the exit tag and cross shown.
Indicator Visuals
The strategy plots the direction of the trend on the chart and changes its color based on this. It also plots shapes on the chart to denote potential buy (Long) and sell (Short) points, where the signals of short and long will appear as well as exit points which can be found as three different,
Exit 1 - A partial exit which sells the previously selected percentage of equity.
Exit 2 - A second exit that can only happen after an Exit 1 has happened, and sell the remaining amount of equity.
Exit Full - A full exit is executed when the price at the exit point is lower than the entry price plus the win difference value. This condition indicates that it is more advantageous to take a single exit rather than waiting for a second exit.
Strategy Alerts
The strategy does not include built-in alerts. However, alerts can be added using the TradingView interface based on the strategy's buy and sell conditions. This way you will be able to receive notifications on your computer or phone when a new signal goes out.
Details
Repainting: It is important to mention that the strategy can mark false long or short signals, as the oscillator is allowed to repaint on the same candle. So users must make sure the candle has closed on buy/sell conditions.
Excessive capital issue: If you configure the strategy with a big amount of capital (+$1,000,000 for example) it is possible that it will completely stop calculating exit signals, as they will be too big for TradingView’s engine to process.
Conclusion
The ByteBoost PRISM strategy empowers traders by providing comprehensive market analysis, clear entry and exit signals, and the ability to visualize strategy performance using historical data. It is a superior algorithm that maximizes profit potential and minimizes risks, making it the preferred choice for traders seeking a competitive edge in the financial markets.
Disclaimer
This strategy is provided as-is, with no guarantee of profits or responsibility for losses. Trading involves risk, and you should only trade with money you can afford to lose. Always conduct your own research and consider your financial situation before engaging in trading.
Master Supertrend Strategy [Trendoscope]Here is the strategy version of the indicator - Master Supertrend
Options and variations are same throughout.
🎲 Variations
Following variations are provided in the form of settings.
🎯 Range Type
Instead of ATR, different types of ranges can be used for stop calculation. Here is the complete list used in the script.
Plus/Minus Range* - Calculates plus range and minus range for each candle and uses them for different sides of stop calculation
Ladder ATR - Based on the existing concept of Ladder ATR defined in Supertrend-Ladder-ATR
True Range - True range derived from standard function ta.tr
Standard Deviation - Standard deviation of close prices
🎯 Applied Calculation
In standard ATR, rma of TR is used for calculations. But, the application calculation provides option to users to use different mechanisms. It can be a type of moving average or few other types of calculations.
Available values are
sma
ema
hma
rma
wma
high
median
🎯 Other options
Few other options provided are
Use Close Price - If selected stops are calculated based on the close price instead of high/low prices
Wait for Close If selected, change of supertrend direction is calculated based on close price instead of high/low prices
Diminishing Stop Distance - When selected, stop distance for the trend direction can only reduce and cannot increase. This option is useful for keeping the tight stops on strong trends.
🎯 Plus Minus Range*
One of the range type used is Plus/Minus Range. What it means and how are these ranges calculated? Let's have a look.
Plus Range is an upward movement of a candle from its last price or open price whichever is lower.
Minus Range is a downward movement of a candle from its last price or open price whichever is higher.
This divides True Range into two separate range for positive and negative side.
Note : Effectiveness on daily charts are quire visible. However, if you want to use it for lower timeframes, please play around with settings before settling on suitable configuration.
Premium PRISM Algorithm [ByteBoost]The ByteBoost PRISM strategy is designed to operate in various market conditions by leveraging the concept of brownian motion theory, which refers to the unpredictable movement of particles suspended in a fluid. This characteristic of random motion can be effectively utilized for analyzing time series data, such as market candles. Based on this notion, we are making the following assumptions regarding the market.
The stock price exhibits characteristics of Brownian motion.
The stock price is distributed in a log-normal pattern.
Volatility remains constant over time.
Options can only be exercised upon expiration.
Risk-free interest does not fluctuate over time.
There are no random or arbitrary opportunities present in the market.
Development Notes
This Strategy was developed with the PineScript language, version 5. This indicator, and most of the descriptions below, were derived largely from the TradingView reference manual. Feedback and suggestions for improvement are more than welcome, as well as recommended input settings and best practices to assist and guide new users effectively.
Features
The ByteBoost PRISM indicator is capable of analyzing multiple aspects of market behavior simultaneously such as:
Detection of potential trend reversals.
Assessment of trend strength and market sentiment.
Identification of stop loss levels.
Discovery of potential entry and exit points.
Ensuring compatibility and effectiveness with other indicators.
Visualization of strategy using historical data.
Customization options available.
Strategy Description
PRISM is an all in one strategy that allows the visualization of entry and exit points as well as the historical performance for every set of parameters. PRISM is a slow paced indicator recommended for the 1h timeframe, because it operates on the belief that markets move in a Brownian motion, for which it leaves enough space and time for the market to decide a trend and catch it at the right time as well as finding appropriate exits given the trend.
PRISM can exist in either an uptrend or downtrend state, but it does not necessarily imply that it reflects the true trend being observed. Instead, it emphasizes capturing significant movements and capitalizing on them by utilizing oscillator levels and exit points calculated based on oversold or overbought values, along with the volatility associated with these movements.
Usage
To use this strategy it is first needed to select a correct set of inputs that correspond to the market you are using, the extra, win difference and oscillator length are dependent on the current market and the average price it manages, so these inputs need to be modified for every pair of assets used.
The long and short tags signify the opportune moment to initiate a new position in the market, whether it's a long or short position, respectively. The exit tags indicate when these positions should be closed. If no exits occur before a new long or short position emerges, it is essential to conclude the existing position and commence a new one in the opposite direction.
Regarding exits, up to two exits can be executed for each movement. The user has the flexibility to determine how these exits are utilized. In the input section, a specific percentage of equity can be selected to be sold during the first exit. If set to 100%, only a single exit will be presented. Otherwise, the remaining equity will be sold during the second exit or at the next trend reversal depending on which action occurs first.
In case the user requires additional exits beyond the initial two, the alternative exits option can be activated in the inputs. This will provide access to supplementary exits, although they may be less advisable compared to the primary exits.
Inputs / Settings
Capital - If using any leverage multiply the amount of money to invest by the leverage, else input the amount to be invested in every trade.
Start date - The date from which the strategy should begin its analysis. Leave unchanged to start from the earliest available date based on your account's plan.
End date - The date until which the strategy should conduct its analysis. Leave unchanged to continue until the current date.
Extra - The minimum gain required in the market to trigger an exit opportunity. It can be a negative number to allow exits at a loss, potentially minimizing losses.
First exit % - If an exit is decided to be partial, it is very likely that there will be a second exit, this parameter determines the percentage of equity to be sold at the first exit. Note that a second exit may not always be applicable.
Win difference - The minimum difference between the entry point and the first exit to determine whether it should be a full exit or a partial exit, as the exit price approaches the entry price, the probability of a trend reversal increases, a full exit is beneficial.
Limit length - Specifies the number of candles to consider for the overbought and oversold market calculation.
Low limit - Sets the minimum value of the limit to decide a short exit.
High limit - Sets the maximum value of the limit to decide a long exit.
Band length - Determines the number of candles to consider for the volatility analysis.
Band height - Sets the multiplication factor of the band to set the maximum and minimum height.
Increment - Determines the rate at which trend reversals occur. A higher value brings the line closer to the current price faster.
Candles exit - Specifies the minimum number of candles required to pass for an exit to become available after initiating a new position.
Oscillator - Enables or disables the main oscillator, which helps determine entry points. Not all assets may benefit from this parameter.
Oscillator length - Specifies the number of candles considered for the entry points oscillator.
Highlighter - Applies a light color between the trend and average price of each bar.
Trend Labels - Displays labels indicating an uptrend or downtrend.
Signal Labels - View the labels indicating a new long or short position.
Exit Labels - Displays the labels indicating exit points.
Candle color - Color codes the inside of the candles with the current signal.
Cloud - Visualize the average price cloud to determine trend direction.
Oscillator points - Adds visual dots to indicate when the oscillator has changed its trend.
Oscillator line - Displays the values of the oscillator to indicate upcoming trend changes.
Alternative exits - Shows additional exits to the ones we recommend, useful if the user missed an exit or needs to have more than two.
Color uptrend - Determines the color scheme for identifying uptrend movements.
Color downtrend - Determines the color scheme for identifying downtrend movements.
Color long - Sets the color scheme for a new long position.
Color short - Sets the color scheme for a new short position.
Color exit - Decides the color scheme for the exit tag and cross shown.
Color alternative exit - Changes the color scheme for the alternative exit cross.
Color oscillator line - Determines the color scheme used for the oscillator line.
Indicator Visuals
The strategy plots the direction of the trend on the chart and changes its color based on this. It also plots shapes on the chart to denote potential buy (Long) and sell (Short) points, where the signals of short and long will appear as well as exit points which can be found as three different,
Exit 1 - A partial exit which sells the previously selected percentage of equity.
Exit 2 - A second exit that can only happen after an Exit 1 has happened, and sell the remaining amount of equity.
Exit Full - A full exit is executed when the price at the exit point is lower than the entry price plus the win difference value. This condition indicates that it is more advantageous to take a single exit rather than waiting for a second exit.
Strategy Alerts
The strategy does not include built-in alerts. However, alerts can be added using the TradingView interface based on the strategy's buy and sell conditions. This way you will be able to receive notifications on your computer or phone when a new signal goes out.
Details
Repainting: It is important to mention that the strategy can mark false long or short signals, as the oscillator is allowed to repaint on the same candle. So users must make sure the candle has closed on buy/sell conditions.
Excessive capital issue: If you configure the strategy with a big amount of capital (+$1,000,000 for example) it is possible that it will completely stop calculating exit signals, as they will be too big for TradingView’s engine to process.
Conclusion
The ByteBoost PRISM strategy empowers traders by providing comprehensive market analysis, clear entry and exit signals, and the ability to visualize strategy performance using historical data. It is a superior algorithm that maximizes profit potential and minimizes risks, making it the preferred choice for traders seeking a competitive edge in the financial markets.
Disclaimer
This strategy is provided as-is, with no guarantee of profits or responsibility for losses. Trading involves risk, and you should only trade with money you can afford to lose. Always conduct your own research and consider your financial situation before engaging in trading.
Entropy, Liquidity, and Momentum - ELMoELMo is a momentum trading strategy based on two concepts: entropy and liquidity
The core concept behind the strategy is twofold: trade based on reversals in momentum based on the strength of a trend, and trade when market liquidity is beneficial to the position.
Entries and exits are determined by first calculating Shannon entropy for the time series and applying various moving averages. Separately, the Hui-Heubel Liquidity Ratio (lhh) is calculated and applied as a filter. Finally, additional conditionals such as RSI are applied to reduce false entries.
Entropy is defined as the amount of 'randomness' in a system and in this application can be thought of as a measure of the strength or weakness of a trend. The main moving averages and visible components in ELMo represent the normalized entropy score of the 'close' value (0 is series minimum, 1 is maximum). lhh will measure illiquid/fragile markets with low values and liquid/resilient markets with a high value. In general, the strategy will prefer to enter long when liquidity is high and short when liquidity is low, based off of cross events in the displayed entropy moving averages. I have published lhh as a separate indicator but it is not required for this strategy to function.
Several settings can be configured inside the strategy, including long/short bias, lookback window, MA band lengths, RSI boundaries, and more, but I have tried to choose sensible defaults that work for a large variety of situations and equities. My preferred time scales are 1m 1h 4h 1d 1w 1mo but others may work fine. Trailing stops are implemented using configurable ATR values. Additional settings are available to limit entry times (default is set to US options market open/close), and backtesting start date.
The long strategy is generally more accurate than short. Since Pinescript does not have a way to manage long/short exposure in a hedged fashion, I prefer to run two separate instances of ELMo in long-only and short-only modes for signaling. I prefer to trade this strategy with a long bias using the short signals as indications of windows of weakness where hedging could be prudent.
Premium Volatility Breakout Strategy [wbburgin]This the premium version of my Volatility Breakout strategy, which improves significantly on the original strategy (publicly available on my profile). Improvements are below. A note about any of my premium scripts: I will continue updating and improving the original (public) versions.
This strategy is not built for any specific asset or timeframe, and has been backtested on crypto, equities, and forex from 1min - 1day. However, I recommend using it on more volatile assets because it is a breakout strategy.
********** My Background
I am an investor, trader, and entrepreneur with 10 years of cryptocurrency and equity trading experience and founder of two fintech startups. I am a graduate of a prestigious university in the United States and carry broad and inclusive interests in mathematical finance, computer science, machine learning / artificial intelligence, as well as other fields.
**********
Improvements over the original Volatility Breakout strategy include:
Faster Trend Detection → The Premium Volatility Breakout strategy will catch trends faster by using adaptive volatility-weighted bands instead of standard-width volatility-weighted bands. This can improve win size and has performed well in my backtesting.
ADX Filter → False breakouts dampen the overall results of the original script, as well as the % profitable,so an ADX filter has been programmed into the script (toggle on/off in settings). This filter will only enter long and short trades when the ADX is above a certain threshold. This is by default toggled off because in most instances it will not be necessary, but in certain environments may be useful.
MA Configuration → Different types of moving averages and weights are now configurable in the settings. These can change the responsiveness of the strategy.
External Trend Filter → I use this strategy as a filter for some of my low-timeframe algorithms. I have added an external trend filter (a plot only displayed in the data window) that will return “1” when the trend is long and “-1” when the trend is short (displayed on-chart with red and green trend curves).
Customizable Alert Messages In-Strategy → In the settings, there will be text boxes where you can create your own alerts. All you will need to do is create an alert in the alert panel on TradingView and leave the message box blank - if you fill out the alert boxes in the settings, these will automatically populate into your alerts. There are in total four different customizable alerts messages: Entry and Exit alerts for both Long and Short sides. If you disable stop loss and/or take profit, these alerts will also be disabled. Similarly, if you disable shorts, all short alerts will be disabled.
About stop losses: This strategy does not come with a stop loss because the moving average acts as a stop loss / trade exit for both long and short entries.
**********
Display
You can turn off highlighting or barcolor in the settings. Additionally, future updates may include a color scheme for users using a light-themed window.
**********
Configuring Alerts
In TradingView desktop, go to the ‘Alerts’ tab on the right panel. Click the “+” button to create a new alert. Select this strategy for the condition and one of the two options that includes alert() function calls. Name the alert what you wish and clear the default message, because your text in the settings will replace this message.
Now that the alert is configured, you can go to the settings of the strategy and fill in your chosen text for the specific alert condition. You will need to check “Long and Short” in the “Trade Direction” setting in order for any Short Alerts to become active.
**********
Disclaimer
Copyright by wbburgin.
The information contained in my Scripts/Indicators/Algorithms does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Hobbiecode - SP500 IBS + HigherThis is a simple strategy that is working well on SPY but also well performing on Mini Futures SP500. The strategy is composed by the followin rules:
1. Today is Monday.
2. The close must be lower than the close on Friday.
3. The IBS must be below 0.5.
4. If 1-3 are true, then enter at the close.
5. Sell 5 trading days later (at the close).
If you backtest it on Mini Futures SP500 you will be able to track data from 1993. It is important to select D1 as timeframe.
Please share any comment or idea below.
Have a good trading,
Ramón.
Initial Balance Panel Strategy for BitcoinInitial Balance Strategy
Initial Balance Strategy uses a source code of "Initial Balance Monitoring Panel" that build from "Initial Balance Markets Time Zones - Overall Highest and Lowest".
Initial Balance is based on the highest and lowest price action within the first 60 minutes of trading. Reading online this can depict which way the market can trend for the session. More information about Initial Balance Panel you can read at the end of the article.
Strategy idea
The main idea is to catch the trend move when most of the 16 Crypto pairs break the Low or High levels together. I found good results when 15 of 16 pairs is break that levels and after we manage the trade within some trail stop indicator, I choose Volatility Stop for this strategy.
Additional Strategy idea
The second one idea that was not made is to catch the pullback after fully green/red zones in Initial Balance Panel become white. That mean the main trend can be finished and we can try to catch good pullback in opposite direction.
Binance Crypto pairs
The strategy use the 16 default Crypto currencies pairs from the Binance. As additional variations of the strategy can be changing the currencies pairs and their number.
List of default pairs:
BINANCE:BTCUSDT, BINANCE:ETHUSDT, BINANCE:EOSUSDT, BINANCE:LTCUSDT, BINANCE:XRPUSDT, BINANCE:DASHUSDT, BINANCE:IOTAUSDT, BINANCE:NEOUSDT, BINANCE:QTUMUSDT, BINANCE:XMRUSDT, BINANCE:ZECUSDT, BINANCE:ETCUSDT, BINANCE:ADAUSDT, BINANCE:XTZUSDT, BINANCE:LINKUSDT, BINANCE:DOTUSDT
Summary
The strategy works very well for a buy trades with settings 15 crypto pairs of 16 that follow the trend with breaking the long initial balance level.
Initial Balance Monitoring Panel
Allows you to have an instant view of 16 Crypto pairs within a monitoring panel, monitoring Initial Balance (Asia, London, New York Stock Exchanges).
The code can easily be changed to suit the crypto pairs you are trading.
The setup of my chart would also include this indicator and the "Initial Balance Markets Time Zones - Overall Highest and Lowest" (with all IBs enabled) as shown above.
Initial Balance is based on the highest and lowest price action within the first 60 minutes of trading. Reading online this can depict which way the market can trend for the session.
The indicator has been coded for Crypto (so other symbols may not work as expected).
Though Initial Balance is based off the first 60 minutes of the trading markets opening, but Crypto is 24/7, this indicator looks at how Asia, London and New York Stock Exchanges opening trading can affect Crypto price action.
Source: Initial Balance Monitoring Panel
Pure Morning 2.0 - Candlestick Pattern Doji StrategyThe new "Pure Morning 2.0 - Candlestick Pattern Doji Strategy" is a trend-following, intraday cryptocurrency trading system authored by devil_machine.
The system identifies Doji and Morning Doji Star candlestick formations above the EMA60 as entry points for long trades.
For best results we recommend to use on 15-minute, 30-minute, or 1-hour timeframes, and are ideal for high-volatility markets.
The strategy also utilizes a profit target or trailing stop for exits, with stop loss set at the lowest low of the last 100 candles. The strategy's configuration details, such as Doji tolerance, and exit configurations are adjustable.
In this new version 2.0, we've incorporated a new selectable filter. Since the stop loss is set at the lowest low, this filter ensures that this value isn't too far from the entry price, thereby optimizing the Risk-Reward ratio.
In the specific case of ALPINE, a 9% Take-Profit and and Stop-Loss at Lowest Low of the last 100 candles were set, with an activated trailing-stop percentage, Max Loss Filter is not active.
Name : Pure Morning 2.0 - Candlestick Pattern Doji Strategy
Author : @devil_machine
Category : Trend Follower based on candlestick patterns.
Operating mode : Spot or Futures (only long).
Trades duration : Intraday
Timeframe : 15m, 30m, 1H
Market : Crypto
Suggested usage : Short-term trading, when the market is in trend and it is showing high volatility .
Entry : When a Doji or Morning Doji Star formation occurs above the EMA60.
Exit : Profit target or Trailing stop, Stop loss on the lowest low of the last 100 candles.
Configuration :
- Doji Settings (tolerances) for Entry Condition
- Max Loss Filter (Lowest Low filter)
- Exit Long configuration
- Trailing stop
Backtesting :
⁃ Exchange: BINANCE
⁃ Pair: ALPINEUSDT
⁃ Timeframe: 30m
⁃ Fee: 0.075%
⁃ Slippage: 1
- Initial Capital: 10000 USDT
- Position sizing: 10% of Equity
- Start: 2022-02-28 (Out Of Sample from 2022-12-23)
- Bar magnifier: on
Disclaimer : Risk Management is crucial, so adjust stop loss to your comfort level. A tight stop loss can help minimise potential losses. Use at your own risk.
How you or we can improve? Source code is open so share your ideas!
Leave a comment and smash the boost button!
Thanks for your attention, happy to support the TradingView community.
Price Action - Support & Resistance + MACD LONG StrategyUsing "Price Action - Support & Resistance by DGT" and the MACD (Moving Average Convergence Divergence) indicator in TradingView can help develop a trade strategy. Here's a step-by-step approach you can follow:
1. Identifying Support and Resistance Levels: Apply the "Price Action - Support & Resistance by DGT" indicator to your chart. This indicator helps you identify key support and resistance levels based on price action. These levels act as potential areas where the price may reverse or consolidate.
2. Confirming Support and Resistance Levels: Once the indicator has plotted support and resistance levels on your chart, analyze the historical price action around these levels. Look for multiple touches or bounces from the same level, which adds strength to the support or resistance zone.
3. Analyzing the MACD Indicator: Add the MACD indicator to your chart. The MACD consists of two lines: the MACD line and the signal line, along with a histogram representing the difference between the two lines. The MACD helps identify momentum and potential trend reversals.
When the MACD line crosses above the signal line and the histogram turns positive, it suggests bullish momentum.
4. Identifying Trade Opportunities:
Bullish Trade: Look for a bullish setup when the price approaches a strong support level identified by the "Price Action - Support & Resistance by DGT" indicator. Wait for the MACD lines to cross above the signal line and the histogram to turn positive, indicating bullish momentum. Enter a long position with a stop loss below the
support level.
Managing the Trade: Once you enter a trade, consider setting a target based on the distance between your entry point and the nearest significant support or resistance level. You can also use trailing stop losses or other risk management techniques to protect your profits and limit potential losses.
Remember that no trading strategy is guaranteed to be successful, and it's important to practice proper risk management and conduct thorough analysis before making any trading decisions. Additionally, it's recommended to backtest and demo trade this strategy before using it with real money.
Advanced Trend Detection StrategyThe Advanced Trend Detection Strategy is a sophisticated trading algorithm based on the indicator "Percent Levels From Previous Close".
This strategy is based on calculating the Pearson's correlation coefficient of logarithmic-scale linear regression channels across a range of lengths from 50 to 1000. It then selects the highest value to determine the length for the channel used in the strategy, as well as for the computation of the Simple Moving Average (SMA) that is incorporated into the strategy.
In this methodology, a script is applied to an equity in which multiple length inputs are taken into consideration. For each of these lengths, the slope, average, and intercept are calculated using logarithmic values. Deviation, the Pearson's correlation coefficient, and upper and lower deviations are also computed for each length.
The strategy then selects the length with the highest Pearson's correlation coefficient. This selected length is used in the channel of the strategy and also for the calculation of the SMA. The chosen length is ultimately the one that best fits the logarithmic regression line, as indicated by the highest Pearson's correlation coefficient.
In short, this strategy leverages the power of Pearson's correlation coefficient in a logarithmic scale linear regression framework to identify optimal trend channels across a broad range of lengths, assisting traders in making more informed decisions.
Wunder Breakout botWunder Breakout bot
1. Wunder Breakout bot is based on the breakout of the trend line. Breakout is a technical trading strategy that is used to determine the moment of a trend line breakout on the price chart. It is based on the assumption that when price crosses a trend line, it signals a change in trend direction and the possible start of a new price movement.
2. The entry points for the trendline breakout strategy are based on the principle of breaking through a set trendline. This means that we look for the moment when the price of the asset crosses the trend line that we have established in order to enter a sell or buy position.
3. We use fixed take-profit and stop-loss, but you can use other risk management systems, based on the suggested settings.
4. Wunder Breakout bot script has added a function to calculate the risk per portfolio (your deposit). When this option is enabled, you get the calculation of the entry amount in dollars relative to your Stop Loss. You can chooseselect the percentage of risk per your portfolio in the settings. the percentage of risk per your portfolio in the settings. The loss will be calculated from the amount that will be displayed on the chart.
For example, if your deposit is $1000 and you set your risk at 1%, with a Stop Loss of 5%, your entry volume would be $200. The SL loss would be $10. $10 is your 1% risk or 1% of your deposit.
*Important! ** The risk per trade must be less than the Stop Loss value. If the risk is more than SL, you should use leverage.
The amount of funds included in the deal is calculated in dollars. This option was created if you want to send a dollar amount from Tradingview to the exchange. However, by specifying the volume in dollars, you will get the net profit and drawdown displayed incorrectly in the backtest results because TradingView calculates the backtest volume in contracts.
To display the correct net profit and drawdown values in Tradingview backtest results, use the "Volume in Contracts" option.
FVG Strategy - Fair Value GapThe Fair Value Gap Strategy (FVG) is a trading approach that relies on price action analysis and involves identifying market inefficiencies or imbalances.
The strategy offers a variety of customizable settings to match your preferences and includes an entry and exit strategy to guide you through trades.
The script operates in the following manner:
It begins by searching for fair-value-gaps and subsequently identifies a break in structure.
The next step involves waiting for the price to retrace within the previously established fair value gap.
Within this gap, there is a Fibonacci retracement that must be reached before placing a stop-order.
Example: GER40, 1min Chart
STOP LOSS & RISK MANAGEMENT
FVG : The stop loss will be set at the end of the fair value gap
Last Swing : The stop loss will be at the last swing high/low
ATR (Average True Range) : The stop loss will be placed one 'Average True Range' away from the entry
TAKE PROFIT
Pips/Points : The stop loss will be set at the chosen amount of pips/points.
RiskReward TP : This is a fixed take profit where you can set a specific risk-to-reward ratio for the trade. For example, you can set a 1:3 risk-to-reward ratio.
Trailing Stop : This is a flexible stop that moves with the market price, allowing you to capture more profit as the trade moves in your favor.
Both : This option combines both the RiskReward TP and Trailing Stop. If the price target is set at a 1:3 risk-to-reward ratio, the trailing stop will move with the price until either the stop or take profit is reached, and the position will be closed completely.
THE FVG SECTION
In the FVG section, you will have the ability to customize your settings based on your specific requirements.
Firstly, you will have the choice of two possible entry options:
Candle Close : This option triggers the order once the candle has completely closed and all the set requirements are met.
Stop Orders : This option triggers the order once all the set requirements are met, even if the candle is still active and has not yet closed.
On top, you can activate the "Pinbar-Trading", that will allow you to take a trade on a pinbar, even when the candle just dipped into the FVG and snapped back.
FAIR VALUE GAP TYPE
On volatile market, it may happen that a massive FVG is created. Thats why we have separated the FVG into 2 different variables.
FVG Type: Normal : This is all regular FVG that meet the requirement of you minimum size range. As example FVG must be minimum 5$ big.
FVG Type: Big : This are all big FVG that meet the minimum set size range. The difference to the "normal" type, the stop loss will be set at 50% of the Big-FVG.
FIBONACCI RETRACEMENT & MARKET STRUCTURE
To refine the FVG strategy, you have three options:
Fibonacci Retracement Value (%) : The FVG strategy employs a Fibonacci retracement, which allows you to trade in the direction of the market movement. To initiate the order, the price must reach a predetermined Fibonacci level and then rebound.
Formation-to-Retracement Countdown: : This option provides you with a specified number of candles to meet the necessary conditions. For example, if the order is not triggered within 20 candles, delete the FVG-Zone and skip the trade to avoid getting caught in a sideways ranging trend.
Structure Lookback : This feature filters out older FVG Zones. You can specify the number of candles that should mark the FVG Zones. Keep in mind that newer and fresher zones will automatically conceal older ones.
GKD-BT Giga Confirmation Stack Backtest [Loxx]Giga Kaleidoscope GKD-BT Giga Confirmation Stack Backtest is a Backtesting module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ GKD-BT Giga Confirmation Stack Backtest
The Giga Confirmation Stack Backtest module allows users to perform backtesting on Long and Short signals from the confluence between GKD-C Confirmation 1 and GKD-C Confirmation 2 indicators. This module encompasses two types of backtests: Trading and Full. The Trading backtest permits users to evaluate individual trades, whether Long or Short, one at a time. Conversely, the Full backtest allows users to analyze either Longs or Shorts separately by toggling between them in the settings, enabling the examination of results for each signal type. The Trading backtest emulates actual trading conditions, while the Full backtest assesses all signals, regardless of being Long or Short.
Additionally, this backtest module provides the option to test using indicators with 1 to 3 take profits and 1 stop loss. The Trading backtest allows for the use of 1 to 3 take profits, while the Full backtest is limited to 1 take profit. The Trading backtest also offers the capability to apply a trailing take profit.
In terms of the percentage of trade removed at each take profit, this backtest module has the following hardcoded values:
Take profit 1: 50% of the trade is removed.
Take profit 2: 25% of the trade is removed.
Take profit 3: 25% of the trade is removed.
Stop loss: 100% of the trade is removed.
After each take profit is achieved, the stop loss level is adjusted. When take profit 1 is reached, the stop loss is moved to the entry point. Similarly, when take profit 2 is reached, the stop loss is shifted to take profit 1. The trailing take profit feature comes into play after take profit 2 or take profit 3, depending on the number of take profits selected in the settings. The trailing take profit is always activated on the final take profit when 2 or more take profits are chosen.
The backtest module also offers the capability to restrict by a specific date range, allowing for simulated forward testing based on past data. Additionally, users have the option to display or hide a trading panel that provides relevant information about the backtest, statistics, and the current trade. It is also possible to activate alerts and toggle sections of the trading panel on or off. On the chart, historical take profit and stop loss levels are represented by horizontal lines overlaid for reference.
To utilize this strategy, follow these steps:
1. Adjust the "Confirmation Type" in the GKD-C Confirmation 1 Indicator to "GKD New."
2. GKD-C Confirmation 1 Import: Import the value "Input into NEW GKD-BT Backtest" from the GKD-C Confirmation 1 module into the GKD-BT Giga Confirmation Stack Backtest module setting named "Import GKD-C Confirmation 1."
3. Adjust the "Confirmation Type" in the GKD-C Confirmation 2 Indicator to "GKD New."
4. GKD-C Confirmation 2 Import: Import the value "Input into NEW GKD-BT Backtest" from the GKD-C Confirmation 2 module into the GKD-BT Giga Confirmation Stack Backtest module setting named "Import GKD-C Confirmation 2."
█ Giga Confirmation Stack Backtest Entries
Entries are generated from the confluence of a GKD-C Confirmation 1 and GKD-C Confirmation 2 indicators. The Confirmation 1 gives the signal and the Confirmation 2 indicator filters or "approves" the the Confirmation 1 signal. If Confirmation 1 gives a long signal and Confirmation 2 shows a downtrend, then the long signal is rejected. If Confirmation 1 gives a long signal and Confirmation 2 shows an uptrend, then the long signal is approved and sent to the backtest execution engine.
█ Volatility Types Included
The GKD system utilizes volatility-based take profits and stop losses. Each take profit and stop loss is calculated as a multiple of volatility. Users can also adjust the multiplier values in the settings.
This module includes 17 types of volatility:
Close-to-Close
Parkinson
Garman-Klass
Rogers-Satchell
Yang-Zhang
Garman-Klass-Yang-Zhang
Exponential Weighted Moving Average
Standard Deviation of Log Returns
Pseudo GARCH(2,2)
Average True Range
True Range Double
Standard Deviation
Adaptive Deviation
Median Absolute Deviation
Efficiency-Ratio Adaptive ATR
Mean Absolute Deviation
Static Percent
Close-to-Close
Close-to-Close volatility is a classic and widely used volatility measure, sometimes referred to as historical volatility.
Volatility is an indicator of the speed of a stock price change. A stock with high volatility is one where the price changes rapidly and with a larger amplitude. The more volatile a stock is, the riskier it is.
Close-to-close historical volatility is calculated using only a stock's closing prices. It is the simplest volatility estimator. However, in many cases, it is not precise enough. Stock prices could jump significantly during a trading session and return to the opening value at the end. That means that a considerable amount of price information is not taken into account by close-to-close volatility.
Despite its drawbacks, Close-to-Close volatility is still useful in cases where the instrument doesn't have intraday prices. For example, mutual funds calculate their net asset values daily or weekly, and thus their prices are not suitable for more sophisticated volatility estimators.
Parkinson
Parkinson volatility is a volatility measure that uses the stock’s high and low price of the day.
The main difference between regular volatility and Parkinson volatility is that the latter uses high and low prices for a day, rather than only the closing price. This is useful as close-to-close prices could show little difference while large price movements could have occurred during the day. Thus, Parkinson's volatility is considered more precise and requires less data for calculation than close-to-close volatility.
One drawback of this estimator is that it doesn't take into account price movements after the market closes. Hence, it systematically undervalues volatility. This drawback is addressed in the Garman-Klass volatility estimator.
Garman-Klass
Garman-Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing prices. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change follows a continuous diffusion process (Geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremes.
Researchers Rogers and Satchell have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Rogers-Satchell
Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates a drift term (mean return not equal to zero). As a result, it provides better volatility estimation when the underlying is trending.
The main disadvantage of this method is that it does not take into account price movements between trading sessions. This leads to an underestimation of volatility since price jumps periodically occur in the market precisely at the moments between sessions.
A more comprehensive estimator that also considers the gaps between sessions was developed based on the Rogers-Satchel formula in the 2000s by Yang-Zhang. See Yang Zhang Volatility for more detail.
Yang-Zhang
Yang Zhang is a historical volatility estimator that handles both opening jumps and the drift and has a minimum estimation error.
Yang-Zhang volatility can be thought of as a combination of the overnight (close-to-open volatility) and a weighted average of the Rogers-Satchell volatility and the day’s open-to-close volatility. It is considered to be 14 times more efficient than the close-to-close estimator.
Garman-Klass-Yang-Zhang
Garman-Klass-Yang-Zhang (GKYZ) volatility estimator incorporates the returns of open, high, low, and closing prices in its calculation.
GKYZ volatility estimator takes into account overnight jumps but not the trend, i.e., it assumes that the underlying asset follows a Geometric Brownian Motion (GBM) process with zero drift. Therefore, the GKYZ volatility estimator tends to overestimate the volatility when the drift is different from zero. However, for a GBM process, this estimator is eight times more efficient than the close-to-close volatility estimator.
Exponential Weighted Moving Average
The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, with the main applications being technical analysis and volatility modeling.
The moving average is designed such that older observations are given lower weights. The weights decrease exponentially as the data point gets older – hence the name exponentially weighted.
The only decision a user of the EWMA must make is the parameter lambda. The parameter decides how important the current observation is in the calculation of the EWMA. The higher the value of lambda, the more closely the EWMA tracks the original time series.
Standard Deviation of Log Returns
This is the simplest calculation of volatility. It's the standard deviation of ln(close/close(1)).
Pseudo GARCH(2,2)
This is calculated using a short- and long-run mean of variance multiplied by ?.
?avg(var;M) + (1 ? ?) avg(var;N) = 2?var/(M+1-(M-1)L) + 2(1-?)var/(M+1-(M-1)L)
Solving for ? can be done by minimizing the mean squared error of estimation; that is, regressing L^-1var - avg(var; N) against avg(var; M) - avg(var; N) and using the resulting beta estimate as ?.
Average True Range
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
The true range indicator is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges.
True Range Double
A special case of ATR that attempts to correct for volatility skew.
Standard Deviation
Standard deviation is a statistic that measures the dispersion of a dataset relative to its mean and is calculated as the square root of the variance. The standard deviation is calculated as the square root of variance by determining each data point's deviation relative to the mean. If the data points are further from the mean, there is a higher deviation within the data set; thus, the more spread out the data, the higher the standard deviation.
Adaptive Deviation
By definition, the Standard Deviation (STD, also represented by the Greek letter sigma ? or the Latin letter s) is a measure that is used to quantify the amount of variation or dispersion of a set of data values. In technical analysis, we usually use it to measure the level of current volatility.
Standard Deviation is based on Simple Moving Average calculation for mean value. This version of standard deviation uses the properties of EMA to calculate what can be called a new type of deviation, and since it is based on EMA, we can call it EMA deviation. Additionally, Perry Kaufman's efficiency ratio is used to make it adaptive (since all EMA type calculations are nearly perfect for adapting).
The difference when compared to the standard is significant--not just because of EMA usage, but the efficiency ratio makes it a "bit more logical" in very volatile market conditions.
Median Absolute Deviation
The median absolute deviation is a measure of statistical dispersion. Moreover, the MAD is a robust statistic, being more resilient to outliers in a data set than the standard deviation. In the standard deviation, the distances from the mean are squared, so large deviations are weighted more heavily, and thus outliers can heavily influence it. In the MAD, the deviations of a small number of outliers are irrelevant.
Because the MAD is a more robust estimator of scale than the sample variance or standard deviation, it works better with distributions without a mean or variance, such as the Cauchy distribution.
Efficiency-Ratio Adaptive ATR
Average True Range (ATR) is a widely used indicator for many occasions in technical analysis. It is calculated as the RMA of the true range. This version adds a "twist": it uses Perry Kaufman's Efficiency Ratio to calculate adaptive true range.
Mean Absolute Deviation
The mean absolute deviation (MAD) is a measure of variability that indicates the average distance between observations and their mean. MAD uses the original units of the data, which simplifies interpretation. Larger values signify that the data points spread out further from the average. Conversely, lower values correspond to data points bunching closer to it. The mean absolute deviation is also known as the mean deviation and average absolute deviation.
This definition of the mean absolute deviation sounds similar to the standard deviation (SD). While both measure variability, they have different calculations. In recent years, some proponents of MAD have suggested that it replace the SD as the primary measure because it is a simpler concept that better fits real life.
Static Percent
Static Percent allows the user to insert their own constant percent that will then be used to create take profits and stoploss
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v2.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data to A backtest module wherein the various components of the GKD system are combined to create a trading signal.
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Confiramtion Stack Backtest
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Fisher Transform as shown on the chart above
Confirmation 2: uf2018 as shown on the chart above
Continuation: Vortex
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD system.
GKD-BT Giga Stacks Backtest [Loxx]Giga Kaleidoscope GKD-BT Giga Stacks Backtest is a Backtesting module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ GKD-BT Giga Stacks Backtest
The Giga Stacks Backtest module allows users to perform backtesting on Long and Short signals from the confluence of GKD-B Baseline, GKD-C Confirmation, and GKD-V Volatility/Volume indicators. This module encompasses two types of backtests: Trading and Full. The Trading backtest permits users to evaluate individual trades, whether Long or Short, one at a time. Conversely, the Full backtest allows users to analyze either Longs or Shorts separately by toggling between them in the settings, enabling the examination of results for each signal type. The Trading backtest emulates actual trading conditions, while the Full backtest assesses all signals, regardless of being Long or Short.
Additionally, this backtest module provides the option to test using indicators with 1 to 3 take profits and 1 stop loss. The Trading backtest allows for the use of 1 to 3 take profits, while the Full backtest is limited to 1 take profit. The Trading backtest also offers the capability to apply a trailing take profit.
In terms of the percentage of trade removed at each take profit, this backtest module has the following hardcoded values:
Take profit 1: 50% of the trade is removed.
Take profit 2: 25% of the trade is removed.
Take profit 3: 25% of the trade is removed.
Stop loss: 100% of the trade is removed.
After each take profit is achieved, the stop loss level is adjusted. When take profit 1 is reached, the stop loss is moved to the entry point. Similarly, when take profit 2 is reached, the stop loss is shifted to take profit 1. The trailing take profit feature comes into play after take profit 2 or take profit 3, depending on the number of take profits selected in the settings. The trailing take profit is always activated on the final take profit when 2 or more take profits are chosen.
The backtest module also offers the capability to restrict by a specific date range, allowing for simulated forward testing based on past data. Additionally, users have the option to display or hide a trading panel that provides relevant information about the backtest, statistics, and the current trade. It is also possible to activate alerts and toggle sections of the trading panel on or off. On the chart, historical take profit and stop loss levels are represented by horizontal lines overlaid for reference.
To utilize this strategy, follow these steps (where "Stack XX" denotes the number of the Stack):
GKD-B Baseline Import: Import the value "Input into NEW GKD-BT Backtest" from the GKD-B Baseline module into the GKD-BT Giga Stacks Backtest module setting named "Stack XX: Import GKD-C, GKD-B, or GKD-V."
GKD-V Volatility/Volume Import: Import the value "Input into NEW GKD-BT Backtest" from the GKD-V Volatility/Volume module into the GKD-BT Giga Stacks Backtest module setting named "Stack XX: Import GKD-C, GKD-B, or GKD-V."
GKD-C Confirmation Import: 1) Adjust the "Confirmation Type" in the GKD-C Confirmation Indicator to "GKD New."; 2) Import the value "Input into NEW GKD-BT Backtest" from the GKD-C Confirmation module into the GKD-BT Giga Stacks Backtest module setting named "Stack XX: Import GKD-C, GKD-B, or GKD."
█ Giga Stacks Backtest Entries
Entries are generated form the confluence of up to six GKD-B Baseline, GKD-C Confirmation, and GKD-V Volatility/Volume indicators. Signals are generated when all Stacks reach uptrend or downtrend together.
Here's how this works. Assume we have the following Stacks and their respective trend on the current candle:
Stack 1 indicator is in uptreend
Stack 2 indicator is in downtrend
Stack 3 indicator is in uptreend
Stack 4 indicator is in uptreend
All stacks are in uptrend except for Stack 2. If Stack 2 reaches uptrend while Stacks 1, 3, and 4 stay in uptrend, then a long signal is generated. The last Stack to align with all other Stacks will generate a long or short signal.
█ Volatility Types Included
The GKD system utilizes volatility-based take profits and stop losses. Each take profit and stop loss is calculated as a multiple of volatility. Users can also adjust the multiplier values in the settings.
This module includes 17 types of volatility:
Close-to-Close
Parkinson
Garman-Klass
Rogers-Satchell
Yang-Zhang
Garman-Klass-Yang-Zhang
Exponential Weighted Moving Average
Standard Deviation of Log Returns
Pseudo GARCH(2,2)
Average True Range
True Range Double
Standard Deviation
Adaptive Deviation
Median Absolute Deviation
Efficiency-Ratio Adaptive ATR
Mean Absolute Deviation
Static Percent
Close-to-Close
Close-to-Close volatility is a classic and widely used volatility measure, sometimes referred to as historical volatility.
Volatility is an indicator of the speed of a stock price change. A stock with high volatility is one where the price changes rapidly and with a larger amplitude. The more volatile a stock is, the riskier it is.
Close-to-close historical volatility is calculated using only a stock's closing prices. It is the simplest volatility estimator. However, in many cases, it is not precise enough. Stock prices could jump significantly during a trading session and return to the opening value at the end. That means that a considerable amount of price information is not taken into account by close-to-close volatility.
Despite its drawbacks, Close-to-Close volatility is still useful in cases where the instrument doesn't have intraday prices. For example, mutual funds calculate their net asset values daily or weekly, and thus their prices are not suitable for more sophisticated volatility estimators.
Parkinson
Parkinson volatility is a volatility measure that uses the stock’s high and low price of the day.
The main difference between regular volatility and Parkinson volatility is that the latter uses high and low prices for a day, rather than only the closing price. This is useful as close-to-close prices could show little difference while large price movements could have occurred during the day. Thus, Parkinson's volatility is considered more precise and requires less data for calculation than close-to-close volatility.
One drawback of this estimator is that it doesn't take into account price movements after the market closes. Hence, it systematically undervalues volatility. This drawback is addressed in the Garman-Klass volatility estimator.
Garman-Klass
Garman-Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing prices. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change follows a continuous diffusion process (Geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremes.
Researchers Rogers and Satchell have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Rogers-Satchell
Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates a drift term (mean return not equal to zero). As a result, it provides better volatility estimation when the underlying is trending.
The main disadvantage of this method is that it does not take into account price movements between trading sessions. This leads to an underestimation of volatility since price jumps periodically occur in the market precisely at the moments between sessions.
A more comprehensive estimator that also considers the gaps between sessions was developed based on the Rogers-Satchel formula in the 2000s by Yang-Zhang. See Yang Zhang Volatility for more detail.
Yang-Zhang
Yang Zhang is a historical volatility estimator that handles both opening jumps and the drift and has a minimum estimation error.
Yang-Zhang volatility can be thought of as a combination of the overnight (close-to-open volatility) and a weighted average of the Rogers-Satchell volatility and the day’s open-to-close volatility. It is considered to be 14 times more efficient than the close-to-close estimator.
Garman-Klass-Yang-Zhang
Garman-Klass-Yang-Zhang (GKYZ) volatility estimator incorporates the returns of open, high, low, and closing prices in its calculation.
GKYZ volatility estimator takes into account overnight jumps but not the trend, i.e., it assumes that the underlying asset follows a Geometric Brownian Motion (GBM) process with zero drift. Therefore, the GKYZ volatility estimator tends to overestimate the volatility when the drift is different from zero. However, for a GBM process, this estimator is eight times more efficient than the close-to-close volatility estimator.
Exponential Weighted Moving Average
The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, with the main applications being technical analysis and volatility modeling.
The moving average is designed such that older observations are given lower weights. The weights decrease exponentially as the data point gets older – hence the name exponentially weighted.
The only decision a user of the EWMA must make is the parameter lambda. The parameter decides how important the current observation is in the calculation of the EWMA. The higher the value of lambda, the more closely the EWMA tracks the original time series.
Standard Deviation of Log Returns
This is the simplest calculation of volatility. It's the standard deviation of ln(close/close(1)).
Pseudo GARCH(2,2)
This is calculated using a short- and long-run mean of variance multiplied by ?.
?avg(var;M) + (1 ? ?) avg(var;N) = 2?var/(M+1-(M-1)L) + 2(1-?)var/(M+1-(M-1)L)
Solving for ? can be done by minimizing the mean squared error of estimation; that is, regressing L^-1var - avg(var; N) against avg(var; M) - avg(var; N) and using the resulting beta estimate as ?.
Average True Range
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
The true range indicator is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges.
True Range Double
A special case of ATR that attempts to correct for volatility skew.
Standard Deviation
Standard deviation is a statistic that measures the dispersion of a dataset relative to its mean and is calculated as the square root of the variance. The standard deviation is calculated as the square root of variance by determining each data point's deviation relative to the mean. If the data points are further from the mean, there is a higher deviation within the data set; thus, the more spread out the data, the higher the standard deviation.
Adaptive Deviation
By definition, the Standard Deviation (STD, also represented by the Greek letter sigma ? or the Latin letter s) is a measure that is used to quantify the amount of variation or dispersion of a set of data values. In technical analysis, we usually use it to measure the level of current volatility.
Standard Deviation is based on Simple Moving Average calculation for mean value. This version of standard deviation uses the properties of EMA to calculate what can be called a new type of deviation, and since it is based on EMA, we can call it EMA deviation. Additionally, Perry Kaufman's efficiency ratio is used to make it adaptive (since all EMA type calculations are nearly perfect for adapting).
The difference when compared to the standard is significant--not just because of EMA usage, but the efficiency ratio makes it a "bit more logical" in very volatile market conditions.
Median Absolute Deviation
The median absolute deviation is a measure of statistical dispersion. Moreover, the MAD is a robust statistic, being more resilient to outliers in a data set than the standard deviation. In the standard deviation, the distances from the mean are squared, so large deviations are weighted more heavily, and thus outliers can heavily influence it. In the MAD, the deviations of a small number of outliers are irrelevant.
Because the MAD is a more robust estimator of scale than the sample variance or standard deviation, it works better with distributions without a mean or variance, such as the Cauchy distribution.
Efficiency-Ratio Adaptive ATR
Average True Range (ATR) is a widely used indicator for many occasions in technical analysis. It is calculated as the RMA of the true range. This version adds a "twist": it uses Perry Kaufman's Efficiency Ratio to calculate adaptive true range.
Mean Absolute Deviation
The mean absolute deviation (MAD) is a measure of variability that indicates the average distance between observations and their mean. MAD uses the original units of the data, which simplifies interpretation. Larger values signify that the data points spread out further from the average. Conversely, lower values correspond to data points bunching closer to it. The mean absolute deviation is also known as the mean deviation and average absolute deviation.
This definition of the mean absolute deviation sounds similar to the standard deviation (SD). While both measure variability, they have different calculations. In recent years, some proponents of MAD have suggested that it replace the SD as the primary measure because it is a simpler concept that better fits real life.
Static Percent
Static Percent allows the user to insert their own constant percent that will then be used to create take profits and stoploss
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v2.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data to A backtest module wherein the various components of the GKD system are combined to create a trading signal.
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Stacks Backtest
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Vorext
Confirmation 2: Coppock Curve
Continuation: Fisher Transform
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD system.
GKD-BT Full Giga Kaleidoscope Backtest [Loxx]Giga Kaleidoscope GKD-BT Full Giga Kaleidoscope Backtest is a Backtesting module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ GKD-BT Full Giga Kaleidoscope Backtest
The Full Giga Kaleidoscope Backtest module enables users to backtest Full GKD Long and Short signals, allowing the creation of a comprehensive NNFX trading system consisting of two confirmation indicators, a baseline, a measure of volatility/volume, and continuations.
This module offers two types of backtests: Trading and Full. The Trading backtest allows users to evaluate individual Long and Short trades one by one. On the other hand, the Full backtest enables the analysis of Longs or Shorts separately by toggling between them in the settings, providing insights into the results for each signal type. The Trading backtest simulates actual trading conditions, while the Full backtest evaluates all signals regardless of their Long or Short nature.
Additionally, the backtest module allows testing with 1 to 3 take profits and 1 stop loss. The Trading backtest supports 1 to 3 take profits, while the Full backtest is limited to 1 take profit. The Trading backtest also includes a trailing take profit feature.
Regarding the percentage of trade removed at each take profit, the backtest module incorporates the following predefined values:
Take profit 1: 50% of the trade is removed.
Take profit 2: 25% of the trade is removed.
Take profit 3: 25% of the trade is removed.
Stop loss: 100% of the trade is removed.
After achieving each take profit, the stop loss level is adjusted accordingly. When take profit 1 is reached, the stop loss is moved to the entry point. Similarly, when take profit 2 is reached, the stop loss is shifted to take profit 1. The trailing take profit feature comes into effect after take profit 2 or take profit 3, depending on the number of take profits selected in the settings. The trailing take profit is always activated on the final take profit when 2 or more take profits are chosen.
The backtest module also provides the option to restrict testing to a specific date range, allowing for simulated forward testing using past data. Additionally, users can choose to display or hide a trading panel that provides relevant information about the backtest, statistics, and the current trade. It is also possible to activate alerts and toggle sections of the trading panel on or off. Historical take profit and stop loss levels are displayed as overlaid horizontal lines on the chart for reference.
To utilize this strategy, follow these steps:
1. GKD-B Baseline Import: Import the value "Input into NEW GKD-BT Backtest" from the GKD-B Baseline module into the GKD-BT Full Giga Kaleidoscope Backtest module setting named "Import GKD-B Baseline."
2. GKD-V Volatility/Volume Import: Import the value "Input into NEW GKD-BT Backtest" from the GKD-V Volatility/Volume module into the GKD-BT Full Giga Kaleidoscope Backtest module setting named "Import GKD-V Volatility/Volume."
3. Adjust the "Confirmation 1 Type" in the GKD-C Confirmation Indicator to "GKD New."
4. GKD-C Confirmation 1 Import: Import the value "Input into NEW GKD-BT Backtest" from the GKD-C Confirmation 1 module into the GKD-BT Full Giga Kaleidoscope Backtest module setting named "Import GKD-C Confirmation 1."
5. Adjust the "Confirmation 2 Type" in the GKD-C Confirmation 2 Indicator to "GKD New."
6. GKD-C Confirmation 2 Import: Import the value "Input into NEW GKD-BT Backtest" from the GKD-C Confirmation 2 module into the GKD-BT Full Giga Kaleidoscope Backtest module setting named "Import GKD-C Confirmation 2."
7. Adjust the "Confirmation Type" in the GKD-C Continuation Indicator to "GKD New."
8. GKD-C Continuation Import: Import the value "Input into NEW GKD-BT Backtest" from the GKD-C Continuation module into the GKD-BT Full Giga Kaleidoscope Backtest module setting named "Import GKD-C Confirmation."
The GKD system utilizes volatility-based take profits and stop losses, where each take profit and stop loss is calculated as a multiple of volatility. Users have the flexibility to adjust the multiplier values in the settings to suit their preferences.
In a future update, the Full Giga Kaleidoscope Backtest module will include the option to incorporate a GKD-E Exit indicator, completing the full trading strategy.
█ Full Giga Kaleidoscope Backtest Entries
Within this module, there are ten distinct types of entries available, which are outlined below:
Standard Entry
1-Candle Standard Entry
Baseline Entry
1-Candle Baseline Entry
Volatility/Volume Entry
1-Candle Volatility/Volume Entry
Confirmation 2 Entry
1-Candle Confirmation 2 Entry
PullBack Entry
Continuation Entry
Each of these entry types can generate either long or short signals, resulting in a total of 20 signal variations. The user has the flexibility to enable or disable specific entry types and choose which qualifying rules within each entry type are applied to price to determine the final long or short signal.
The following section provides an overview of the various entry types and their corresponding qualifying rules:
Standard Entry
1. GKD-C Confirmation gives signal
2. Baseline agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
1-Candle Standard Entry
1a. GKD-C Confirmation gives signal
2a. Baseline agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Baseline Entry
1. GKD-B Basline gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
7. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
1-Candle Baseline Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Volatility/Volume Entry
1. GKD-V Volatility/Volume gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Volatility/Volume Entry
1a. GKD-V Volatility/Volume gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSVVC Bars Back' prior
Next Candle
1b. Price retraced
2b. Volatility/Volume agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Baseline agrees
Confirmation 2 Entry
1. GKD-C Confirmation 2 gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Volatility/Volume agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Confirmation 2 Entry
1a. GKD-C Confirmation 2 gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSC2C Bars Back' prior
Next Candle
1b. Price retraced
2b. Confirmation 2 agrees
3b. Confirmation 1 agrees
4b. Volatility/Volume agrees
5b. Baseline agrees
PullBack Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price is beyond 1.0x Volatility of Baseline
Next Candle
1b. Price inside Goldie Locks Zone Minimum
2b. Price inside Goldie Locks Zone Maximum
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Continuation Entry
1. Standard Entry, 1-Candle Standard Entry, Baseline Entry, 1-Candle Baseline Entry, Volatility/Volume Entry, 1-Candle Volatility/Volume Entry, Confirmation 2 Entry, 1-Candle Confirmation 2 Entry, or Pullback entry triggered previously
2. Baseline hasn't crossed since entry signal trigger
4. Confirmation 1 agrees
5. Baseline agrees
6. Confirmation 2 agrees
█ Volatility Types Included
This module includes 17 types of volatility:
Close-to-Close
Parkinson
Garman-Klass
Rogers-Satchell
Yang-Zhang
Garman-Klass-Yang-Zhang
Exponential Weighted Moving Average
Standard Deviation of Log Returns
Pseudo GARCH(2,2)
Average True Range
True Range Double
Standard Deviation
Adaptive Deviation
Median Absolute Deviation
Efficiency-Ratio Adaptive ATR
Mean Absolute Deviation
Static Percent
Close-to-Close
Close-to-Close volatility is a classic and widely used volatility measure, sometimes referred to as historical volatility.
Volatility is an indicator of the speed of a stock price change. A stock with high volatility is one where the price changes rapidly and with a larger amplitude. The more volatile a stock is, the riskier it is.
Close-to-close historical volatility is calculated using only a stock's closing prices. It is the simplest volatility estimator. However, in many cases, it is not precise enough. Stock prices could jump significantly during a trading session and return to the opening value at the end. That means that a considerable amount of price information is not taken into account by close-to-close volatility.
Despite its drawbacks, Close-to-Close volatility is still useful in cases where the instrument doesn't have intraday prices. For example, mutual funds calculate their net asset values daily or weekly, and thus their prices are not suitable for more sophisticated volatility estimators.
Parkinson
Parkinson volatility is a volatility measure that uses the stock’s high and low price of the day.
The main difference between regular volatility and Parkinson volatility is that the latter uses high and low prices for a day, rather than only the closing price. This is useful as close-to-close prices could show little difference while large price movements could have occurred during the day. Thus, Parkinson's volatility is considered more precise and requires less data for calculation than close-to-close volatility.
One drawback of this estimator is that it doesn't take into account price movements after the market closes. Hence, it systematically undervalues volatility. This drawback is addressed in the Garman-Klass volatility estimator.
Garman-Klass
Garman-Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing prices. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change follows a continuous diffusion process (Geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremes.
Researchers Rogers and Satchell have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Rogers-Satchell
Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates a drift term (mean return not equal to zero). As a result, it provides better volatility estimation when the underlying is trending.
The main disadvantage of this method is that it does not take into account price movements between trading sessions. This leads to an underestimation of volatility since price jumps periodically occur in the market precisely at the moments between sessions.
A more comprehensive estimator that also considers the gaps between sessions was developed based on the Rogers-Satchel formula in the 2000s by Yang-Zhang. See Yang Zhang Volatility for more detail.
Yang-Zhang
Yang Zhang is a historical volatility estimator that handles both opening jumps and the drift and has a minimum estimation error.
Yang-Zhang volatility can be thought of as a combination of the overnight (close-to-open volatility) and a weighted average of the Rogers-Satchell volatility and the day’s open-to-close volatility. It is considered to be 14 times more efficient than the close-to-close estimator.
Garman-Klass-Yang-Zhang
Garman-Klass-Yang-Zhang (GKYZ) volatility estimator incorporates the returns of open, high, low, and closing prices in its calculation.
GKYZ volatility estimator takes into account overnight jumps but not the trend, i.e., it assumes that the underlying asset follows a Geometric Brownian Motion (GBM) process with zero drift. Therefore, the GKYZ volatility estimator tends to overestimate the volatility when the drift is different from zero. However, for a GBM process, this estimator is eight times more efficient than the close-to-close volatility estimator.
Exponential Weighted Moving Average
The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, with the main applications being technical analysis and volatility modeling.
The moving average is designed such that older observations are given lower weights. The weights decrease exponentially as the data point gets older – hence the name exponentially weighted.
The only decision a user of the EWMA must make is the parameter lambda. The parameter decides how important the current observation is in the calculation of the EWMA. The higher the value of lambda, the more closely the EWMA tracks the original time series.
Standard Deviation of Log Returns
This is the simplest calculation of volatility. It's the standard deviation of ln(close/close(1)).
Pseudo GARCH(2,2)
This is calculated using a short- and long-run mean of variance multiplied by ?.
?avg(var;M) + (1 ? ?) avg(var;N) = 2?var/(M+1-(M-1)L) + 2(1-?)var/(M+1-(M-1)L)
Solving for ? can be done by minimizing the mean squared error of estimation; that is, regressing L^-1var - avg(var; N) against avg(var; M) - avg(var; N) and using the resulting beta estimate as ?.
Average True Range
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
The true range indicator is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges.
True Range Double
A special case of ATR that attempts to correct for volatility skew.
Standard Deviation
Standard deviation is a statistic that measures the dispersion of a dataset relative to its mean and is calculated as the square root of the variance. The standard deviation is calculated as the square root of variance by determining each data point's deviation relative to the mean. If the data points are further from the mean, there is a higher deviation within the data set; thus, the more spread out the data, the higher the standard deviation.
Adaptive Deviation
By definition, the Standard Deviation (STD, also represented by the Greek letter sigma ? or the Latin letter s) is a measure that is used to quantify the amount of variation or dispersion of a set of data values. In technical analysis, we usually use it to measure the level of current volatility.
Standard Deviation is based on Simple Moving Average calculation for mean value. This version of standard deviation uses the properties of EMA to calculate what can be called a new type of deviation, and since it is based on EMA, we can call it EMA deviation. Additionally, Perry Kaufman's efficiency ratio is used to make it adaptive (since all EMA type calculations are nearly perfect for adapting).
The difference when compared to the standard is significant--not just because of EMA usage, but the efficiency ratio makes it a "bit more logical" in very volatile market conditions.
Median Absolute Deviation
The median absolute deviation is a measure of statistical dispersion. Moreover, the MAD is a robust statistic, being more resilient to outliers in a data set than the standard deviation. In the standard deviation, the distances from the mean are squared, so large deviations are weighted more heavily, and thus outliers can heavily influence it. In the MAD, the deviations of a small number of outliers are irrelevant.
Because the MAD is a more robust estimator of scale than the sample variance or standard deviation, it works better with distributions without a mean or variance, such as the Cauchy distribution.
Efficiency-Ratio Adaptive ATR
Average True Range (ATR) is a widely used indicator for many occasions in technical analysis. It is calculated as the RMA of the true range. This version adds a "twist": it uses Perry Kaufman's Efficiency Ratio to calculate adaptive true range.
Mean Absolute Deviation
The mean absolute deviation (MAD) is a measure of variability that indicates the average distance between observations and their mean. MAD uses the original units of the data, which simplifies interpretation. Larger values signify that the data points spread out further from the average. Conversely, lower values correspond to data points bunching closer to it. The mean absolute deviation is also known as the mean deviation and average absolute deviation.
This definition of the mean absolute deviation sounds similar to the standard deviation (SD). While both measure variability, they have different calculations. In recent years, some proponents of MAD have suggested that it replace the SD as the primary measure because it is a simpler concept that better fits real life.
Static Percent
Static Percent allows the user to insert their own constant percent that will then be used to create take profits and stoploss
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v2.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data to A backtest module wherein the various components of the GKD system are combined to create a trading signal.
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Full Giga Kaleidoscope Backtest as shown on the chart above
Baseline: Hull Moving Average as shown on the chart above
Volatility/Volume: Hurst Exponent as shown on the chart above
Confirmation 1: Vorext as shown on the chart above
Confirmation 2: Coppock Curve as shown on the chart above
Continuation: Fisher Transform as shown on the chart above
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD system.
