IU EMA Channel StrategyIU EMA Channel Strategy
Overview:
The IU EMA Channel Strategy is a simple yet effective trend-following strategy that uses two Exponential Moving Averages (EMAs) based on the high and low prices. It provides clear entry and exit signals by identifying price crossovers relative to the EMAs while incorporating a built-in Risk-to-Reward Ratio (RTR) for effective risk management.
Inputs ( Settings ):
- RTR (Risk-to-Reward Ratio): Define the ratio for risk-to-reward (default = 2).
- EMA Length: Adjust the length of the EMA channels (default = 100).
How the Strategy Works
1. EMA Channels:
- High-based EMA: EMA calculated on the high price.
- Low-based EMA: EMA calculated on the low price.
The area between these two EMAs creates a "channel" that visually highlights potential support and resistance zones.
2. Entry Rules:
- Long Entry: When the price closes above the high-based EMA (crossover).
- Short Entry: When the price closes below the low-based EMA (crossunder).
These entries ensure trades are taken in the direction of momentum.
3. Stop Loss (SL) and Take Profit (TP):
- Stop Loss:
- For long positions, the SL is set at the previous bar's low.
- For short positions, the SL is set at the previous bar's high.
- Take Profit:
- TP is automatically calculated using the Risk-to-Reward Ratio (RTR) you define.
- Example: If RTR = 2, the TP will be 2x the risk distance.
4. Exit Rules:
- Positions are closed at either the stop loss or the take profit level.
- The strategy manages exits automatically to enforce disciplined risk management.
Visual Features
1. EMA Channels:
- The high and low EMAs are dynamically color-coded:
- Green: Price is above the EMA (bullish condition).
- Red: Price is below the EMA (bearish condition).
- The area between the EMAs is shaded for better visual clarity.
2. Stop Loss and Take Profit Zones:
- SL and TP levels are plotted for both long and short positions.
- Zones are filled with:
- Red: Stop Loss area.
- Green: Take Profit area.
Be sure to manage your risk and position size properly.
Cerca negli script per "stop loss"
MicuRobert EMA Cross StrategyThis is a repost of a old strategy that cant be updated anymore, it was a request for a user made in Oct, 6, 2015
Here's a possible engaging description for the tradingview script:
**MicuRobert EMA Cross V2: A Powerful Trading Strategy**
Join the ranks of successful traders with this advanced strategy, designed to help you profit from market trends. The MicuRobert EMA Cross V2 combines two essential indicators - Exponential Moving Average (EMA) and Divergence EMA (DEMA) - to generate buy and sell signals.
**Key Features:**
* **Trading Session Filter**: Only trade during your preferred session, ensuring you're in sync with market conditions.
* **Trailing Stop**: Automatically adjust stop-loss levels to lock in profits or limit losses.
* **Customizable Trade Size**: Set the size of each trade based on your risk tolerance and trading goals.
**How it Works:**
The script uses two EMAs (5-period and 34-period) to identify trends. When the shorter EMA crosses above the longer one, a buy signal is generated. Conversely, when the shorter EMA falls below the longer one, a sell signal is triggered. The strategy also incorporates divergence analysis between price action and the EMAs.
**Visual Aids:**
* **EMA Plots**: Visualize the two EMAs on your chart to gauge market momentum.
* **Buy/Sell Signals**: See when buy or sell signals are generated, along with their corresponding entry prices.
* **Trailing Stop Lines**: Monitor stop-loss levels as they adjust based on price action.
**Get Started:**
Download this script and start trading like a pro! With its robust features and customizable settings, the MicuRobert EMA Cross V2 is an excellent addition to any trader's arsenal.
~Llama3
TheHorsyAlgoPROThe Horsy algo is an automated strategy that uses any minute Higher timeframe range as reference and search for a purge of liquidity on the HTF high or low where buyside or sell side liquidity is, the algo only search this at specific desired times that can be configured according to the time you usually trade, the strategy is known as Turtle soup purge and reverse or lately as CRT.
Why is useful?
The purpose of this Algorithm is to help turtle soup traders to quickly identify when the market is likely to reverse the algo evaluates if the opportunity is worth it, base on risk reward and other desired filters. Also this strategy can help to quickly backtest the trader strategy it can be configured in different timeframes and adapt to the trader personality, they can easily see the results and statistics and notice if its profitable or not.
This algo is useful for intraday traders looking for a purge and reverse at a key times and at key HTF price levels this only looks the previous HTF highs and lows but is important to also monitor Order blocks, FVGs, gaps, or wicks to have the best results.
How it works and how it does it?
The Horsy algo simply Jumps from one type of liquidity to another one buyside to sell side or vice versa. In order for the algo to trigger an entry it has to meet these conditions
1. Take HTF liquidity, trade above a HTF high or below a HTF low in the selected time window
2. Make a change in the state of delivery with a close below the previous candle low for shorts and close above previous candle high for longs.
3. Allow for a reasonable risk reward, it will use the highest high for shorts and the lowest low for longs. The default take profit is the opposite side of the range.
4. Validate others user filters this include enter only trades aligned with the HTF bias, or trades aligned with the LTF bias or booth. The algo have the option to enter only premium and discount entries. And finally, an option to allow for different contract sizes depending of the maximum percent of the account we want to risk default is 1%. For this last option is important to check the initial balance and leverage are configured correctly, is disable by default because it requires more capital to perform well.
We can see the algo performing in the picture below with a short trade, notice there are some white lines, they are the high or the low of HTF candle that start generating inside candles in the HTF meaning a possible consolidation. The algo plots the HTF ranges in a shaded boxes as you can see below
The HTF bias as you can see in the picture is calculated based on the last close of the HTF meaning close above previous HTF high is bullish close below previous HTF low is bearish. This HTF bias level is also the last HTF mid-price or 50%. By default, this line is enabled.
The LTF bias is calculated based on the range created from the expansion outside the previous HTF range is also the mid-price. If the LTF close above previous HTF high is bullish and if the LTF close below previous HTF low is bearish. By default this LTF bias line is disable.
This strategy includes an original and personal developed code that uses dealing ranges to recognize if the market is expanding, retracing, reversing or consolidating. This allow the algo to exit the position when it detects a retracement or at the end of the expansion. This is the default exit type.
You can monitor the previous dealing ranges created in history with an option than can be enable, by default is disable, this ranges are created after price takes buyside and then sell side or vice versa. So this dealing ranges can be useful also to identify minor pools of liquidity and premium and discount in the lower timeframe.
The picture below is a long example, the exit in this case is just at the high of the range. The normal take profit is in a blue line for longs.
How to use it?
First select the desired HTF timeframe recommended is from 30min to 240min then you setup the chart on the lower timeframe you want to trade recommended is from 1min to 15min to enter. By default This strategy is designed to work for intraday during key times when price take stops and then moves quickly away from them. You can select as much as 6 different times or just one. After you select the desired time window where the algo will look for the purge and reverse, They are highlighted in the candles that change colors excluding the gray ones that indicates consolidation.
Then the Algo allow to performs several additional filters in the entries you can select if you want to trade only longs or shorts trades, you can select when to move the stop loss to Break even. In deviations of the risk or you can just select to remove risk when price hits the 50% of previous HTF range.
You can select the minimum desired risk reward of the trade before is allow to be taken. Once is configured correctly the algo should trigger signals with a triangle up or down plus the strategy entry.
At the beginning of the picture there are some blue lines in the HTF high low and close, this is to easily identify that the market is in the Asia session, the time can be configured by the user, these lines are normally gray.
On the right top of the screen you can see some statistics about the strategy how many trades it took, ARR is an approximated value of the accumulated total risk reward of all the trades when they get closed in the simulation.
Profit factor and percent profitable are also shown should be green it means that the strategy makes money over time. But apart from that is important to notice how it makes money it is stable over time? it is a roller coaster? that why I Include this other measurements MxcsTps is the maximum consecutives take profits and Mxcsls is the maximum consecutive stop losses it takes, the slash number after it is the consecutive Break evens. So this way you know what to expect and what is normal in the strategy.
The algo shows all the times the stop loss, take profit and break even level if enable in the colored red lines for short and blue lines for longs. You can also select how price will manage the profit or stoploss point meaning that you can choose to wait for the candle to close to invalidate your idea or to take profit. This is good to avoid liquidity sweeps but can also lead to mayor loses if the idea is wrong. The default setting is to close the trade when price takes the high or low where the stoploss is, the take profit is taken after a retracement to allow to profit on expansions. You can select also to exit on a reversal if you want to ride all the move. This last option has to be used with caution because sometimes price just retrace or reverse very fast decreasing the trade profit and overall strategy performance.
The algo have the option to use standard deviation from the normal risk if you prefer to prevent liquidity sweeps near the stop level this make wider stops but can lead to increased loses so it has to be used carefully.
Below is a picture that show the entry stop and take profit levels with an exit on a retracement activated.
Strategy Results
The backtesting results are obtained simulating a 2000usd account in the Micro Nasdaq using 1 contract per trade. Commission are set to 2usd per contract, slippage to 1tick. You can see in list of trades we are not risking more than 1 % percent of the account. The backtested range is from august to November 2024. This strategy doesn’t generate too much trades because of the time filters and conditions that has to be meet to take an entry but you can see the results of the last 4months with the available data that are around 32 trades.
The default settings for this strategy is HTF as 240min designed to work on a LTF 5min chart, the default purge times are 245-300, 745-800, 845-900, 1045-1100 and 1245-1300 UTC-4, the algo will look for shorts or longs, with a minimum risk reward of 2.0. With an additional filter of the HTFBias. The take profit is by default taken on the first retracement after hitting the target. The default settings are optimized to work on the Nasdaq or Spy, but can also perform well in other assets with the correct adjustments.
Remember entries constitute only a small component of a complete winning strategy. Other factors like risk management, position-sizing, trading frequency, trading fees, and many others must also be properly managed to achieve profitability. Past performance doesn’t guarantee future results. To really take advantage of this strategy you have to study turtle soup and the HTF key levels use this only as a confirmation that your overall idea will play out and use it to backtest your model.
Summary of features
·Adaptable strategy to different HTF timeframes from 1-1440min
· Select up to 6 different purge time windows UTC-4, UTC-5
· Choose desired Risk Reward per trade
· Easily see the HTF high low close and 50% key levels in the LTF
· Identify HTF consolidations that generate key major liquidity pools
· HTF/LTF bias filters to trade in favor of the big trend or in sync
· Shaded boxes that indicate if the market is bullish, bearish or consolidating
· See the current midpoint of the last expansion move
· Optimal trade entry filter to trade only in a discount or premium
· Customizable trade management take profit, stop, breakeven level
· Option to exit on a close, retracement or reversal after hitting the take profit level
· Option to exit on a close or reversal after hitting stop loss
· Configurable breakeven point with standard deviations or at 50% of the HTF
· Calculate different contract sizes depending of a percentage of the initial balance
· Standard deviations from normal risk can be used to prevent liquidity sweeps
· See dealing ranges history to check minor pools of liquidity and premium or discount
· Dashboard with instant statistics about the strategy current settings
SMB MagicSMB Magic
Overview: SMB Magic is a powerful technical strategy designed to capture breakout opportunities based on price movements, volume spikes, and trend-following logic. This strategy works exclusively on the XAU/USD symbol and is optimized for the 15-minute time frame. By incorporating multiple factors, this strategy identifies high-probability trades with a focus on risk management.
Key Features:
Breakout Confirmation:
This strategy looks for price breakouts above the previous high or below the previous low, with a significant volume increase. A breakout is considered valid when it is supported by strong volume, confirming the strength of the price move.
Price Movement Filter:
The strategy ensures that only significant price movements are considered for trades, helping to avoid low-volatility noise. This filter targets larger price swings to maximize potential profits.
Exponential Moving Average (EMA):
A long-term trend filter is applied to ensure that buy trades occur only when the price is above the moving average, and sell trades only when the price is below it.
Fibonacci Levels:
Custom Fibonacci retracement levels are drawn based on recent price action. These levels act as dynamic support and resistance zones and help determine the exit points for trades.
Take Profit/Stop Loss:
The strategy incorporates predefined take profit and stop loss levels, designed to manage risk effectively. These levels are automatically applied to trades and are adjusted based on the market's volatility.
Volume Confirmation:
A volume multiplier confirms the strength of the breakout. A trade is only considered when the volume exceeds a certain threshold, ensuring that the breakout is supported by sufficient market participation.
How It Works:
Entry Signals:
Buy Signal: A breakout above the previous high, accompanied by significant volume and price movement, occurs when the price is above the trend-following filter (e.g., EMA).
Sell Signal: A breakout below the previous low, accompanied by significant volume and price movement, occurs when the price is below the trend-following filter.
Exit Strategy:
Each position (long or short) has predefined take-profit and stop-loss levels, which are designed to protect capital and lock in profits at key points in the market.
Fibonacci Levels:
Fibonacci levels are drawn to identify potential areas of support or resistance, which can be used to guide exits and stop-loss placements.
Important Notes:
Timeframe Restriction: This strategy is designed specifically for the 15-minute time frame.
Symbol Restriction: The strategy works exclusively on the XAU/USD (Gold) symbol and is not recommended for use with other instruments.
Best Performance in Trending Markets: It works best in trending conditions where breakouts occur frequently.
Disclaimer:
Risk Warning: Trading involves risk, and past performance is not indicative of future results. Always conduct your own research and make informed decisions before trading.
Candle Range Theory [Advanced] - AlgoVisionUnderstanding Candle Range Theory (CRT) in the AlgoVision Indicator
Candle Range Theory (CRT) is a structured approach to analyzing market movements within the price ranges of candlesticks. CRT is founded on the idea that each candlestick on a chart, regardless of timeframe, represents a distinct range of price action, marked by the candle's open, high, low, and close. This range gives insights into market dynamics, and when analyzed in lower timeframes, reveals patterns that indicate underlying market sentiment and institutional behaviors.
Key Concepts of Candle Range Theory
Candlestick Range: The range of a candlestick is simply the distance between its high and low. Across timeframes, this range highlights significant price behavior, with each candlestick representing a snapshot of price movement. The body (distance between open and close) shows the primary price action, while wicks (shadows) reflect price fluctuations or "noise" around this movement.
Multi-Timeframe Analysis: A higher-timeframe (HTF) candlestick can be dissected into smaller, structured price movements in lower timeframes (LTFs). By analyzing these smaller movements, traders gain a detailed view of the market’s progression within the HTF candlestick’s range. Each HTF candlestick’s high and low provide support and resistance levels on the LTF, where the price can "sweep," break out, or retest these levels.
Market Behavior within the Range: Price action within a range doesn’t move randomly; it follows structured behavior, often revealing patterns. By analyzing these patterns, CRT provides insights into the market’s intention to accumulate, manipulate, or distribute assets within these ranges. This behavior can indicate future market direction and increase the probability of accurate trading signals.
CRT and ICT Power of 3: Accumulation, Manipulation, and Distribution (AMD)
A foundational element of our CRT indicator is its combination with ICT’s Power of 3 (Accumulation, Manipulation, and Distribution or AMD). This approach identifies three stages of market movement:
Accumulation: During this phase, institutions accumulate positions within a tight price range, often leading to sideways movement. Here, price consolidates as institutions carefully enter or exit positions, erasing traces of their intent from public view.
Manipulation: Institutions often use manipulation to create false breakouts, targeting retail traders who enter the market on perceived breakouts or reversals. Manipulation is characterized by liquidity grabs, false breakouts, or stop hunts, as price momentarily moves outside the established range before quickly returning.
Distribution: Following accumulation and manipulation, the distribution phase aligns with the true market direction. Institutions now allow the market to move with the trend, initiating a stronger and more sustained price movement that aligns with their intended position.
This AMD cycle is often observed across multiple timeframes, allowing traders to refine entries and exits by identifying accumulation, manipulation, and distribution phases on smaller timeframes within the range of a higher-timeframe candle. CRT views this cycle as the "heartbeat" of the market—a continuous loop of price movements. With our indicator, you can identify this cycle on your current timeframe, with the signal candle acting as the "manipulation" candle.
How to Use the Premium AlgoVision CRT Indicator
1. Indicator Display Options
Bullish/Bearish Plot Indication: Toggles the display of bullish or bearish CRT signals. Turn this on to display signals on your chart or off to reduce screen clutter.
Order Block Indication: Highlights the order block entry price, which is the preferred entry point for CRT trades.
Purge Time Indication: Shows when the low or high of Candle 1 is purged by Candle 2, helping to identify potential manipulation points.
2. Filter Options
Match Indicator Candle with Signal: Ensures that only bullish Candle 2s (for longs) or bearish Candle 2s (for shorts) are signaled. This filter helps eliminate signals where the candlestick’s direction does not align with the CRT model.
Take Profit Already Reached: When enabled, this filter removes CRT signals if take profit levels are reached within Candle 2. This helps focus on setups where there’s still room for price movement.
Midnight Price Filter: Filters signals based on midnight price levels:
Longs: Only signals if the order block entry price is below the midnight price.
Shorts: Only signals if the order block entry price is above the midnight price.
3. Entry and Exit Settings
Wick out prevention: Allows positions to stay open and prevent getting wicked out. Positions will still be able to close if determined by the algorithm.
Buy/Sell: This allows you to set you daily bias. You can select to only see buys or sells.
Custom Stop Loss: Sets a custom stop loss distance from the entry price (e.g., $100 or $200 away) if the predefined stop loss based on Candle 2’s low/high doesn’t suit your preference.
Take Profit Levels: Choose from three take profit levels:
Optimized Take Profit: Uses an optimized take profit level based on CRT’s recommended exit point.
Take Profit 1: Sets an initial take profit level.
Take Profit 2: Sets a secondary take profit level for a more extended exit target.
Timeframe of Order Block: Select the timeframe of the order block entry, which can be tailored based on the timeframe of the CRT signal.
Risk-to-Reward Filter: Filters trades based on a specified risk-to-reward ratio, using the indicator’s stop loss as the base. This helps to ensure trades meet minimum reward criteria.
4. Risk Management
Fixed Entry QTY: This will allow you to open all positions with a fixed QTY
Risk to Reward Ratio: This allows you to set a minimum risk to reward ratio, the strategy will only take trades if this risk to reward is met.
Risk Type:
Fixed Amount: Allows you to risk a fixed $ amount.
% of account: Allows you to risk % of account equity.
5. Day and Time Filters
Filter by Days: Specify the days of the week for CRT signals to appear. For instance, you could enable signals only on Thursdays. This setting can be adjusted to any day or combination of days.
Purge Time Filter: Filters CRT signals based on specific purge times when Candle 1’s low/high is breached by Candle 2, as CRT setups are observed to work best during certain times.
Hour Filters for CRT Signals:
1-Hour CRT Times: Allows filtering CRT signals based on specific 1-hour time intervals.
4-Hour CRT Times: Filter 4-hour CRT signals based on specified times.
Forex and Futures Conversion: Adjusts times based on standard sessions for Forex (e.g., 9:00 AM 4-hour candle) and Futures (e.g., 10 PM candle for Futures or 8 AM for Crypto).
6. Currency and Asset-Specific Filters
Crypto vs. Forex Mode: This setting adjusts the indicator’s timing to match market sessions specific to either crypto or Forex/Futures, ensuring the CRT model aligns with the asset type.
Additional Notes
Backtesting Options: Adjust these to test risk management, such as risking a fixed amount or a percentage of the account, for historical performance insights.
Optimized Settings: This version includes all features and optimized settings, with the most refined data analysis.
Conclusion By combining CRT with ICT Power of 3, the AlgoVision Indicator allows traders to leverage the CRT candlestick as a versatile tool for identifying potential market moves. This method provides beginners and seasoned traders alike with a robust framework to understand market dynamics and refine trade strategies across timeframes. Setting alerts on the higher timeframe to catch bullish or bearish CRT signals allows you to plan and execute trades on the lower timeframe, aligning your strategy with the broader market flow.
CCI Threshold StrategyThe CCI Threshold Strategy is a trading approach that utilizes the Commodity Channel Index (CCI) as a momentum indicator to identify potential buy and sell signals in financial markets. The CCI is particularly effective in detecting overbought and oversold conditions, providing traders with insights into possible price reversals. This strategy is designed for use in various financial instruments, including stocks, commodities, and forex, and aims to capitalize on price movements driven by market sentiment.
Commodity Channel Index (CCI)
The CCI was developed by Donald Lambert in the 1980s and is primarily used to measure the deviation of a security's price from its average price over a specified period.
The formula for CCI is as follows:
CCI=(TypicalPrice−SMA)×0.015MeanDeviation
CCI=MeanDeviation(TypicalPrice−SMA)×0.015
where:
Typical Price = (High + Low + Close) / 3
SMA = Simple Moving Average of the Typical Price
Mean Deviation = Average of the absolute deviations from the SMA
The CCI oscillates around a zero line, with values above +100 indicating overbought conditions and values below -100 indicating oversold conditions (Lambert, 1980).
Strategy Logic
The CCI Threshold Strategy operates on the following principles:
Input Parameters:
Lookback Period: The number of periods used to calculate the CCI. A common choice is 9, as it balances responsiveness and noise.
Buy Threshold: Typically set at -90, indicating a potential oversold condition where a price reversal is likely.
Stop Loss and Take Profit: The strategy allows for risk management through customizable stop loss and take profit points.
Entry Conditions:
A long position is initiated when the CCI falls below the buy threshold of -90, indicating potential oversold levels. This condition suggests that the asset may be undervalued and due for a price increase.
Exit Conditions:
The long position is closed when the closing price exceeds the highest price of the previous day, indicating a bullish reversal. Additionally, if the stop loss or take profit thresholds are hit, the position will be exited accordingly.
Risk Management:
The strategy incorporates optional stop loss and take profit mechanisms, which can be toggled on or off based on trader preference. This allows for flexibility in risk management, aligning with individual risk tolerances and trading styles.
Benefits of the CCI Threshold Strategy
Flexibility: The CCI Threshold Strategy can be applied across different asset classes, making it versatile for various market conditions.
Objective Signals: The use of quantitative thresholds for entry and exit reduces emotional bias in trading decisions (Tversky & Kahneman, 1974).
Enhanced Risk Management: By allowing traders to set stop loss and take profit levels, the strategy aids in preserving capital and managing risk effectively.
Limitations
Market Noise: The CCI can produce false signals, especially in highly volatile markets, leading to potential losses (Bollinger, 2001).
Lagging Indicator: As a lagging indicator, the CCI may not always capture rapid market movements, resulting in missed opportunities (Pring, 2002).
Conclusion
The CCI Threshold Strategy offers a systematic approach to trading based on well-established momentum principles. By focusing on overbought and oversold conditions, traders can make informed decisions while managing risk effectively. As with any trading strategy, it is crucial to backtest the approach and adapt it to individual trading styles and market conditions.
References
Bollinger, J. (2001). Bollinger on Bollinger Bands. New York: McGraw-Hill.
Lambert, D. (1980). Commodity Channel Index. Technical Analysis of Stocks & Commodities, 2, 3-5.
Pring, M. J. (2002). Technical Analysis Explained. New York: McGraw-Hill.
Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124-1131.
Price Action StrategyThe **Price Action Strategy** is a tool designed to capture potential market reversals by utilizing classic reversal candlestick patterns such as Hammer, Shooting Star, Doji, and Pin Bar near dinamic support and resistance levels.
***Note to moderators
- The moving average was removed from the strategy because it was not suitable for the strategy and not participating in the entry or exit criteria.
- The moving average length has been replaced/renamed by the support/resistance lenght.
- The bullish engulfing and bearish engulfing patterns were also removed because in practice they were not working as entry criteria, since the candle price invariably closes far from the support/resistance level even considering the sensitivity range. There was no change in the backtest results after removing these patterns.
### Key Elements of the Strategy
1. Support and Resistance Levels
- Support and resistance are pivotal price levels where the asset has previously struggled to move lower (support) or higher (resistance). These levels act as psychological barriers where buying interest (at support) or selling interest (at resistance) often increases, potentially causing price reversals.
- In this strategy, support is calculated as the lowest low and resistance as the highest high over a 16-period length. When the price nears these levels, it indicates possible zones for a reversal, and the strategy looks for specific candlestick patterns to confirm an entry.
2. Candlestick Patterns
- This strategy uses classic reversal patterns, including:
- **Hammer**: Indicates a buy signal, suggesting rejection of lower prices.
- **Shooting Star**: Suggests a sell signal, showing rejection of higher prices.
- **Doji**: Reflects indecision and potential reversal.
- **Pin Bar**: Represents price rejection with a long shadow, often signaling a reversal.
By combining these reversal patterns with the proximity to dinamic support or resistance levels, the strategy aims to capture potential reversal movements.
3. Sensitivity Level
- The sensitivity parameter adjusts the acceptable range (Default 0.018 = 1.8%) around support and resistance levels within which reversal patterns can trigger trades (i.e. the closing price of the candle must occur within the specified range defined by the sensitivity parameter). A higher sensitivity value expands this range, potentially leading to less accurate signals, as it may allow for more false positives.
4. Entry Criteria
- **Buy (Long)**: A Hammer, Doji, or Pin Bar pattern near support.
- **Sell (Short)**: A Shooting Star, Doji, or Pin Bar near resistance.
5. Exit criteria
- Take profit = 9.5%
- Stop loss = 16%
6. No Repainting
- The Price Action Strategy is not subject to repainting.
7. Position Sizing by Equity and risk management
- This strategy has a default configuration to operate with 35% of the equity. The stop loss is set to 16% from the entry price. This way, the strategy is putting at risk about 16% of 35% of equity, that is, around 5.6% of equity for each trade. The percentage of equity and stop loss can be adjusted by the user according to their risk management.
8. Backtest results
- This strategy was subjected to deep backtest and operations in replay mode on **1000000MOGUSDT.P**, with the inclusion of transaction fees at 0.12% and slipagge of 5 ticks, and the past results have shown consistent profitability. Past results are no guarantee of future results. The strategy's backtest results may even be due to overfitting with past data.
9. Chart Visualization
- Support and resistance levels are displayed as green (support) and red (resistance) lines.
- Only the candlestick pattern that generated the entry signal to triger the trade is identified and labeled on the chart. During the operation, the occurrence of new Doji, Pin Bar, Hammer and Shooting Star patterns will not be demonstrated on the chart, since the exit criteria are based on percentage take profit and stop loss.
Doji:
Pin Bar and Doji
Shooting Star and Doji
Hammer
10. Default settings
Chart timeframe: 20 min
Moving average lenght: 16
Sensitivity: 0.018
Stop loss (%): 16
Take Profit (%): 9.5
BYBIT:1000000MOGUSDT.P
E9 Shark-32 Pattern Strategy The E9 Shark-32 Pattern is a powerful trading tool designed to capitalize on the Shark-32 pattern—a specific Candlestick pattern.
The Shark-32 Pattern: What Is It?
The Shark-32 pattern is a technical formation that occurs when the following conditions are met:
Higher Highs and Lower Lows: The low of two bars ago is lower than the previous bar, and the previous bar's low is lower than the current bar. At the same time, the high of two bars ago is higher than the previous bar, and the previous bar’s high is higher than the current bar.
This unique setup forms the "Shark-32" pattern, which signals potential volume squeezes and trend changes in the market.
How Does the Strategy Work?
The E9 Shark-32 Pattern Strategy builds upon this pattern by defining clear entry and exit rules based on the pattern's confirmation. Here's a breakdown of how the strategy operates:
1. Identifying the Shark-32 Pattern
When the Shark-32 pattern is confirmed, the strategy "locks" the high and low prices from the initial bar of the pattern. These locked prices serve as key levels for future trade entries and exits.
2. Entry Conditions
The strategy waits for the price to cross the pattern's locked high or low, signaling potential market direction.
Long Entry: A long trade is triggered when the closing price crosses above the locked pattern high (green line).
Short Entry: A short trade is triggered when the closing price crosses below the locked pattern low (red line).
The strategy ensures that only one trade is taken for each Shark-32 pattern, preventing overtrading and allowing traders to focus on high-probability setups.
3. Stop Loss and Take Profit Levels
The strategy has built-in risk management through stop-loss and take-profit levels, which are visually represented by the lines on the chart:
Stop Loss:
Stop loss can be adjusted in settings.
Take Profit:
For long trades: The take-profit target is set at the upper white dotted line, which is projected above the pattern high.
For short trades: The take-profit target is set at the lower white dotted line, which is projected below the pattern low.
These clearly defined levels help traders to manage risk effectively while maximizing potential returns.
4. Visual Cues
To make trading decisions even easier, the strategy provides helpful visual cues:
Green Line (Pattern High): This line represents the high of the Shark-32 pattern and serves as a resistance level and short entry signal.
Red Line (Pattern Low): This line represents the low of the Shark-32 pattern and serves as a support level and long entry signal.
White Dotted Lines: These lines represent potential profit targets, projected both above and below the pattern. They help traders define where the market might go next.
Additionally, the strategy highlights the pattern formation with color-coded bars and background shading to draw attention to the Shark-32 pattern when it is confirmed. This adds a layer of visual confirmation, making it easier to spot opportunities in real-time.
5. No Repeated Trades
An important aspect of the strategy is that once a trade is taken (either long or short), no additional trades are executed until a new Shark-32 pattern is identified. This ensures that only valid and confirmed setups are acted upon.
TradeCreator Pro - Moving Averages, RSI, Volume, Trends, Levels█ Overview
TradeCreator Pro is designed to help you build successful trades by streamlining the processes of trade planning, evaluation, and execution. With a focus on data accuracy, speed, precision, and ease of use, this all-in-one tool assists in identifying optimal entry and exit points, calculating risk/reward ratios, and executing trades efficiently. Whether you’re a beginner or an experienced trader, TradeCreator Pro empowers you to make informed, data-driven decisions with real-time signals and fully customizable settings.
█ Key Benefits & Use Cases
TradeCreator Pro is designed to help you effortlessly discover profitable trades by evaluating and testing multiple setups across different assets and timeframes. Key use cases include:
Quick Strategy Testing: Rapidly test multiple setups and strategies, gaining immediate insights into their potential outcomes.
Risk/Reward Evaluation: Quickly identify which trade ideas are worth pursuing based on their profitability and associated risk.
Multi-Timeframe Testing: Seamlessly test the same trading setup across various timeframes and tickers.
Backtesting: Analyze the historical performance of specific setups to gauge their effectiveness.
Key Level Identification: Instantly spot critical support and resistance levels, improving your decision-making process.
Custom Alerts: Set personalized notifications for key levels, ensuring timely action on potential trade opportunities.
█ Core Features
Dashboard: A real-time view of critical metrics such as trend strength, support/resistance levels, volume profiles, RSI divergence, and trade scoring. Designed to provide a comprehensive snapshot of your trading environment and potential trading outcome.
Trend Analysis: Detect prevailing trends by analyzing multiple moving averages, support/resistance zones, volume profile and linear regressions for RSI and closing prices.
Support & Resistance Identification: Automatically identify support and resistance levels.
Volume Profile: Visualize volume profile and its point of control across support/resistance ranges, helping you spot key consolidation areas.
RSI & Price Divergence Detection: Identify potential divergences between RSI and price through linear regressions, providing valuable trade signals.
Risk Management Tools: Set equity loss levels based on specified leverage, allowing you to manage risk effectively for both long and short trades.
Entry & Exit Recommendations: Identify multiple options for optimal entry and exit levels based on current market conditions.
Trade Scoring: Score each trade setup on a 0-100 scale, factoring in potential ROI, ROE, P&L, and Risk-Reward Ratios to ensure high-quality trade execution.
Dynamic Execution & Monitoring: Benefit from multi-stage exit strategies, dynamic trailing stop losses, and the ability to backtest setups with historical data.
Alerts & Automation: Customize alerts for key market movements and opt for manual or automated trading through TradingView’s supported partners.
█ How to Use
Installation: Add TradeCreator Pro to your TradingView chart.
Trend Adjustment: The system automatically detects the current market trend, but you can fine-tune all trend detection parameters as needed.
Trading Parameter Configuration: Customize entry, exit, profitability, and risk-reward settings to match your trading style.
Entry and Exit Level Refinement: Use the automated suggestions, or choose from conceptual or arbitrary levels for greater control.
Stop Loss and Profit Target Fine-Tuning: Apply the system’s recommendations or adjust them by selecting from multiple available options.
Backtest Setup: Run the backtester to analyze past performance and assess how the strategy would have performed historically.
Set Alerts: Stay informed by setting alerts to notify you when a trade setup is triggered.
█ Notes
The first time you apply the indicator to a chart, it may take a few moments to compile. If it takes too long, switch timeframes temporarily to restart the process.
█ Risk Disclaimer
Trading in financial markets involves significant risk and is not suitable for all investors. The use of TradeCreator Pro, as well as any other tools provided by AlgoTrader Pro, is purely for informational and educational purposes. These tools are not intended to provide financial advice, and past performance is not indicative of future results. It is essential to do your own research, practice proper risk management, and consult with a licensed financial advisor before making any trading decisions. AlgoTrader Pro is not responsible for any financial losses you may incur through the use of these tools.
Intramarket Difference Index StrategyHi Traders !!
The IDI Strategy:
In layman’s terms this strategy compares two indicators across markets and exploits their differences.
note: it is best the two markets are correlated as then we know we are trading a short to long term deviation from both markets' general trend with the assumption both markets will trend again sometime in the future thereby exhausting our trading opportunity.
📍 Import Notes:
This Strategy calculates trade position size independently (i.e. risk per trade is controlled in the user inputs tab), this means that the ‘Order size’ input in the ‘Properties’ tab will have no effect on the strategy. Why ? because this allows us to define custom position size algorithms which we can use to improve our risk management and equity growth over time. Here we have the option to have fixed quantity or fixed percentage of equity ATR (Average True Range) based stops in addition to the turtle trading position size algorithm.
‘Pyramiding’ does not work for this strategy’, similar to the order size input togeling this input will have no effect on the strategy as the strategy explicitly defines the maximum order size to be 1.
This strategy is not perfect, and as of writing of this post I have not traded this algo.
Always take your time to backtests and debug the strategy.
🔷 The IDI Strategy:
By default this strategy pulls data from your current TV chart and then compares it to the base market, be default BINANCE:BTCUSD . The strategy pulls SMA and RSI data from either market (we call this the difference data), standardizes the data (solving the different unit problem across markets) such that it is comparable and then differentiates the data, calling the result of this transformation and difference the Intramarket Difference (ID). The formula for the the ID is
ID = market1_diff_data - market2_diff_data (1)
Where
market(i)_diff_data = diff_data / ATR(j)_market(i)^0.5,
where i = {1, 2} and j = the natural numbers excluding 0
Formula (1) interpretation is the following
When ID > 0: this means the current market outperforms the base market
When ID = 0: Markets are at long run equilibrium
When ID < 0: this means the current market underperforms the base market
To form the strategy we define one of two strategy type’s which are Trend and Mean Revesion respectively.
🔸 Trend Case:
Given the ‘‘Strategy Type’’ is equal to TREND we define a threshold for which if the ID crosses over we go long and if the ID crosses under the negative of the threshold we go short.
The motivating idea is that the ID is an indicator of the two symbols being out of sync, and given we know volatility clustering, momentum and mean reversion of anomalies to be a stylised fact of financial data we can construct a trading premise. Let's first talk more about this premise.
For some markets (cryptocurrency markets - synthetic symbols in TV) the stylised fact of momentum is true, this means that higher momentum is followed by higher momentum, and given we know momentum to be a vector quantity (with magnitude and direction) this momentum can be both positive and negative i.e. when the ID crosses above some threshold we make an assumption it will continue in that direction for some time before executing back to its long run equilibrium of 0 which is a reasonable assumption to make if the market are correlated. For example for the BTCUSD - ETHUSD pair, if the ID > +threshold (inputs for MA and RSI based ID thresholds are found under the ‘‘INTRAMARKET DIFFERENCE INDEX’’ group’), ETHUSD outperforms BTCUSD, we assume the momentum to continue so we go long ETHUSD.
In the standard case we would exit the market when the IDI returns to its long run equilibrium of 0 (for the positive case the ID may return to 0 because ETH’s difference data may have decreased or BTC’s difference data may have increased). However in this strategy we will not define this as our exit condition, why ?
This is because we want to ‘‘let our winners run’’, to achieve this we define a trailing Donchian Channel stop loss (along with a fixed ATR based stop as our volatility proxy). If we were too use the 0 exit the strategy may print a buy signal (ID > +threshold in the simple case, market regimes may be used), return to 0 and then print another buy signal, and this process can loop may times, this high trade frequency means we fail capture the entire market move lowering our profit, furthermore on lower time frames this high trade frequencies mean we pay more transaction costs (due to price slippage, commission and big-ask spread) which means less profit.
By capturing the sum of many momentum moves we are essentially following the trend hence the trend following strategy type.
Here we also print the IDI (with default strategy settings with the MA difference type), we can see that by letting our winners run we may catch many valid momentum moves, that results in a larger final pnl that if we would otherwise exit based on the equilibrium condition(Valid trades are denoted by solid green and red arrows respectively and all other valid trades which occur within the original signal are light green and red small arrows).
another example...
Note: if you would like to plot the IDI separately copy and paste the following code in a new Pine Script indicator template.
indicator("IDI")
// INTRAMARKET INDEX
var string g_idi = "intramarket diffirence index"
ui_index_1 = input.symbol("BINANCE:BTCUSD", title = "Base market", group = g_idi)
// ui_index_2 = input.symbol("BINANCE:ETHUSD", title = "Quote Market", group = g_idi)
type = input.string("MA", title = "Differrencing Series", options = , group = g_idi)
ui_ma_lkb = input.int(24, title = "lookback of ma and volatility scaling constant", group = g_idi)
ui_rsi_lkb = input.int(14, title = "Lookback of RSI", group = g_idi)
ui_atr_lkb = input.int(300, title = "ATR lookback - Normalising value", group = g_idi)
ui_ma_threshold = input.float(5, title = "Threshold of Upward/Downward Trend (MA)", group = g_idi)
ui_rsi_threshold = input.float(20, title = "Threshold of Upward/Downward Trend (RSI)", group = g_idi)
//>>+----------------------------------------------------------------+}
// CUSTOM FUNCTIONS |
//<<+----------------------------------------------------------------+{
// construct UDT (User defined type) containing the IDI (Intramarket Difference Index) source values
// UDT will hold many variables / functions grouped under the UDT
type functions
float Close // close price
float ma // ma of symbol
float rsi // rsi of the asset
float atr // atr of the asset
// the security data
getUDTdata(symbol, malookback, rsilookback, atrlookback) =>
indexHighTF = barstate.isrealtime ? 1 : 0
= request.security(symbol, timeframe = timeframe.period,
expression = [close , // Instentiate UDT variables
ta.sma(close, malookback) ,
ta.rsi(close, rsilookback) ,
ta.atr(atrlookback) ])
data = functions.new(close_, ma_, rsi_, atr_)
data
// Intramerket Difference Index
idi(type, symbol1, malookback, rsilookback, atrlookback, mathreshold, rsithreshold) =>
threshold = float(na)
index1 = getUDTdata(symbol1, malookback, rsilookback, atrlookback)
index2 = getUDTdata(syminfo.tickerid, malookback, rsilookback, atrlookback)
// declare difference variables for both base and quote symbols, conditional on which difference type is selected
var diffindex1 = 0.0, var diffindex2 = 0.0,
// declare Intramarket Difference Index based on series type, note
// if > 0, index 2 outpreforms index 1, buy index 2 (momentum based) until equalibrium
// if < 0, index 2 underpreforms index 1, sell index 1 (momentum based) until equalibrium
// for idi to be valid both series must be stationary and normalised so both series hae he same scale
intramarket_difference = 0.0
if type == "MA"
threshold := mathreshold
diffindex1 := (index1.Close - index1.ma) / math.pow(index1.atr*malookback, 0.5)
diffindex2 := (index2.Close - index2.ma) / math.pow(index2.atr*malookback, 0.5)
intramarket_difference := diffindex2 - diffindex1
else if type == "RSI"
threshold := rsilookback
diffindex1 := index1.rsi
diffindex2 := index2.rsi
intramarket_difference := diffindex2 - diffindex1
//>>+----------------------------------------------------------------+}
// STRATEGY FUNCTIONS CALLS |
//<<+----------------------------------------------------------------+{
// plot the intramarket difference
= idi(type,
ui_index_1,
ui_ma_lkb,
ui_rsi_lkb,
ui_atr_lkb,
ui_ma_threshold,
ui_rsi_threshold)
//>>+----------------------------------------------------------------+}
plot(intramarket_difference, color = color.orange)
hline(type == "MA" ? ui_ma_threshold : ui_rsi_threshold, color = color.green)
hline(type == "MA" ? -ui_ma_threshold : -ui_rsi_threshold, color = color.red)
hline(0)
Note it is possible that after printing a buy the strategy then prints many sell signals before returning to a buy, which again has the same implication (less profit. Potentially because we exit early only for price to continue upwards hence missing the larger "trend"). The image below showcases this cenario and again, by allowing our winner to run we may capture more profit (theoretically).
This should be clear...
🔸 Mean Reversion Case:
We stated prior that mean reversion of anomalies is an standerdies fact of financial data, how can we exploit this ?
We exploit this by normalizing the ID by applying the Ehlers fisher transformation. The transformed data is then assumed to be approximately normally distributed. To form the strategy we employ the same logic as for the z score, if the FT normalized ID > 2.5 (< -2.5) we buy (short). Our exit conditions remain unchanged (fixed ATR stop and trailing Donchian Trailing stop)
🔷 Position Sizing:
If ‘‘Fixed Risk From Initial Balance’’ is toggled true this means we risk a fixed percentage of our initial balance, if false we risk a fixed percentage of our equity (current balance).
Note we also employ a volatility adjusted position sizing formula, the turtle training method which is defined as follows.
Turtle position size = (1/ r * ATR * DV) * C
Where,
r = risk factor coefficient (default is 20)
ATR(j) = risk proxy, over j times steps
DV = Dollar Volatility, where DV = (1/Asset Price) * Capital at Risk
🔷 Risk Management:
Correct money management means we can limit risk and increase reward (theoretically). Here we employ
Max loss and gain per day
Max loss per trade
Max number of consecutive losing trades until trade skip
To read more see the tooltips (info circle).
🔷 Take Profit:
By defualt the script uses a Donchain Channel as a trailing stop and take profit, In addition to this the script defines a fixed ATR stop losses (by defualt, this covers cases where the DC range may be to wide making a fixed ATR stop usefull), ATR take profits however are defined but optional.
ATR SL and TP defined for all trades
🔷 Hurst Regime (Regime Filter):
The Hurst Exponent (H) aims to segment the market into three different states, Trending (H > 0.5), Random Geometric Brownian Motion (H = 0.5) and Mean Reverting / Contrarian (H < 0.5). In my interpretation this can be used as a trend filter that eliminates market noise.
We utilize the trending and mean reverting based states, as extra conditions required for valid trades for both strategy types respectively, in the process increasing our trade entry quality.
🔷 Example model Architecture:
Here is an example of one configuration of this strategy, combining all aspects discussed in this post.
Future Updates
- Automation integration (next update)
Multi-Factor StrategyThis trading strategy combines multiple technical indicators to create a systematic approach for entering and exiting trades. The goal is to capture trends by aligning several key indicators to confirm the direction and strength of a potential trade. Below is a detailed description of how the strategy works:
Indicators Used
MACD (Moving Average Convergence Divergence):
MACD Line: The difference between the 12-period and 26-period Exponential Moving Averages (EMAs).
Signal Line: A 9-period EMA of the MACD line.
Usage: The strategy looks for crossovers between the MACD line and the Signal line as entry signals. A bullish crossover (MACD line crossing above the Signal line) indicates a potential upward movement, while a bearish crossover (MACD line crossing below the Signal line) signals a potential downward movement.
RSI (Relative Strength Index):
Usage: RSI is used to gauge the momentum of the price movement. The strategy uses specific thresholds: below 70 for long positions to avoid overbought conditions and above 30 for short positions to avoid oversold conditions.
ATR (Average True Range):
Usage: ATR measures market volatility and is used to set dynamic stop-loss and take-profit levels. A stop loss is set at 2 times the ATR, and a take profit at 3 times the ATR, ensuring that risk is managed relative to market conditions.
Simple Moving Averages (SMA):
50-day SMA: A short-term trend indicator.
200-day SMA: A long-term trend indicator.
Usage: The strategy uses the relationship between the 50-day and 200-day SMAs to determine the overall market trend. Long positions are taken when the price is above the 50-day SMA and the 50-day SMA is above the 200-day SMA, indicating an uptrend. Conversely, short positions are taken when the price is below the 50-day SMA and the 50-day SMA is below the 200-day SMA, indicating a downtrend.
Entry Conditions
Long Position:
-MACD Crossover: The MACD line crosses above the Signal line.
-RSI Confirmation: RSI is below 70, ensuring the asset is not overbought.
-SMA Confirmation: The price is above the 50-day SMA, and the 50-day SMA is above the 200-day SMA, indicating a strong uptrend.
Short Position:
MACD Crossunder: The MACD line crosses below the Signal line.
RSI Confirmation: RSI is above 30, ensuring the asset is not oversold.
SMA Confirmation: The price is below the 50-day SMA, and the 50-day SMA is below the 200-day SMA, indicating a strong downtrend.
Opposite conditions for shorts
Exit Strategy
Stop Loss: Set at 2 times the ATR from the entry price. This dynamically adjusts to market volatility, allowing for wider stops in volatile markets and tighter stops in calmer markets.
Take Profit: Set at 3 times the ATR from the entry price. This ensures a favorable risk-reward ratio of 1:1.5, aiming for higher rewards on successful trades.
Visualization
SMAs: The 50-day and 200-day SMAs are plotted on the chart to visualize the trend direction.
MACD Crossovers: Bullish and bearish MACD crossovers are highlighted on the chart to identify potential entry points.
Summary
This strategy is designed to align multiple indicators to increase the probability of successful trades by confirming trends and momentum before entering a position. It systematically manages risk with ATR-based stop loss and take profit levels, ensuring that trades are exited based on market conditions rather than arbitrary points. The combination of trend indicators (SMAs) with momentum and volatility indicators (MACD, RSI, ATR) creates a robust approach to trading in various market environments.
Bitcoin Futures vs. Spot Tri-Frame - Strategy [presentTrading]Prove idea with a backtest is always true for trading.
I developed and open-sourced it as an educational material for crypto traders to understand that the futures and spot spread may be effective but not be as effective as they might think. It serves as an indicator of sentiment rather than a reliable predictor of market trends over certain periods. It is better suited for specific trading environments, which require further research.
█ Introduction and How it is Different
The "Bitcoin Futures vs. Spot Tri-Frame Strategy" utilizes three different timeframes to calculate the Z-Score of the spread between BTC futures and spot prices on Binance and OKX exchanges. The strategy executes long or short trades based on composite Z-Score conditions across the three timeframes.
The spread refers to the difference in price between BTC futures and BTC spot prices, calculated by taking a weighted average of futures prices from multiple exchanges (Binance and OKX) and subtracting a weighted average of spot prices from the same exchanges.
BTCUSD 1D L/S Performance
█ Strategy, How It Works: Detailed Explanation
🔶 Calculation of the Spread
The spread is the difference in price between BTC futures and BTC spot prices. The strategy calculates the spread by taking a weighted average of futures prices from multiple exchanges (Binance and OKX) and subtracting a weighted average of spot prices from the same exchanges. This spread serves as the primary metric for identifying trading opportunities.
Spread = Weighted Average Futures Price - Weighted Average Spot Price
🔶 Z-Score Calculation
The Z-Score measures how many standard deviations the current spread is from its historical mean. This is calculated for each timeframe as follows:
Spread Mean_tf = SMA(Spread_tf, longTermSMA)
Spread StdDev_tf = STDEV(Spread_tf, longTermSMA)
Z-Score_tf = (Spread_tf - Spread Mean_tf) / Spread StdDev_tf
Local performance
🔶 Composite Entry Conditions
The strategy triggers long and short entries based on composite Z-Score conditions across all three timeframes:
- Long Condition: All three Z-Scores must be greater than the long entry threshold.
Long Condition = (Z-Score_tf1 > zScoreLongEntryThreshold) and (Z-Score_tf2 > zScoreLongEntryThreshold) and (Z-Score_tf3 > zScoreLongEntryThreshold)
- Short Condition: All three Z-Scores must be less than the short entry threshold.
Short Condition = (Z-Score_tf1 < zScoreShortEntryThreshold) and (Z-Score_tf2 < zScoreShortEntryThreshold) and (Z-Score_tf3 < zScoreShortEntryThreshold)
█ Trade Direction
The strategy allows the user to specify the trading direction:
- Long: Only long trades are executed.
- Short: Only short trades are executed.
- Both: Both long and short trades are executed based on the Z-Score conditions.
█ Usage
The strategy can be applied to BTC or Crypto trading on major exchanges like Binance and OKX. By leveraging discrepancies between futures and spot prices, traders can exploit market inefficiencies. This strategy is suitable for traders who prefer a statistical approach and want to diversify their timeframes to validate signals.
█ Default Settings
- Input TF 1 (60 minutes): Sets the first timeframe for Z-Score calculation.
- Input TF 2 (120 minutes): Sets the second timeframe for Z-Score calculation.
- Input TF 3 (180 minutes): Sets the third timeframe for Z-Score calculation.
- Long Entry Z-Score Threshold (3): Defines the threshold above which a long trade is triggered.
- Short Entry Z-Score Threshold (-3): Defines the threshold below which a short trade is triggered.
- Long-Term SMA Period (100): The period used to calculate the simple moving average for the spread.
- Use Hold Days (true): Enables holding trades for a specified number of days.
- Hold Days (5): Number of days to hold the trade before exiting.
- TPSL Condition (None): Defines the conditions for taking profit and stop loss.
- Take Profit (%) (30.0): The percentage at which the trade will take profit.
- Stop Loss (%) (20.0): The percentage at which the trade will stop loss.
By fine-tuning these settings, traders can optimize the strategy to suit their risk tolerance and trading style, enhancing overall performance.
Double Vegas SuperTrend Enhanced - Strategy [presentTrading]
█ Introduction and How It Is Different
The "Double Vegas SuperTrend Enhanced" strategy is a sophisticated trading system that combines two Vegas SuperTrend Enhanced. Very Powerful!
Let's celebrate the joy of Children's Day on June 1st! Enjoyyy!
BTCUSD LS performance
The strategy aims to pinpoint market trends with greater accuracy and generate trades that align with the overall market direction.
This approach differentiates itself by integrating volatility adjustments and leveraging the Vegas Channel's width to refine the SuperTrend calculations, resulting in a dynamic and responsive trading system.
Additionally, the strategy incorporates customizable take-profit and stop-loss levels, providing traders with a robust framework for risk management.
-> check Vegas SuperTrend Enhanced - Strategy
█ Strategy, How It Works: Detailed Explanation
🔶 Vegas Channel and SuperTrend Calculations
The strategy initiates by calculating the Vegas Channel, which is derived from a simple moving average (SMA) and the standard deviation (STD) of the closing prices over a specified window length. This channel helps in measuring market volatility and forms the basis for adjusting the SuperTrend indicator.
Vegas Channel Calculation:
- vegasMovingAverage = SMA(close, vegasWindow)
- vegasChannelStdDev = STD(close, vegasWindow)
- vegasChannelUpper = vegasMovingAverage + vegasChannelStdDev
- vegasChannelLower = vegasMovingAverage - vegasChannelStdDev
SuperTrend Multiplier Adjustment:
- channelVolatilityWidth = vegasChannelUpper - vegasChannelLower
- adjustedMultiplier = superTrendMultiplierBase + volatilityAdjustmentFactor * (channelVolatilityWidth / vegasMovingAverage)
The adjusted multiplier enhances the SuperTrend's sensitivity to market volatility, making it more adaptable to changing market conditions.
BTCUSD Local picture.
🔶 Average True Range (ATR) and SuperTrend Values
The ATR is computed over a specified period to measure market volatility. Using the ATR and the adjusted multiplier, the SuperTrend upper and lower levels are determined.
ATR Calculation:
- averageTrueRange = ATR(atrPeriod)
**SuperTrend Calculation:**
- superTrendUpper = hlc3 - (adjustedMultiplier * averageTrueRange)
- superTrendLower = hlc3 + (adjustedMultiplier * averageTrueRange)
The SuperTrend levels are continuously updated based on the previous values and the current market trend direction. The market trend is determined by comparing the closing prices with the SuperTrend levels.
Trend Direction:
- If close > superTrendLowerPrev, then marketTrend = 1 (bullish)
- If close < superTrendUpperPrev, then marketTrend = -1 (bearish)
🔶 Trade Entry and Exit Conditions
The strategy generates trade signals based on the alignment of both SuperTrends. Trades are executed only when both SuperTrends indicate the same market direction.
Entry Conditions:
- Long Position: Both SuperTrends must signal a bullish trend.
- Short Position: Both SuperTrends must signal a bearish trend.
Exit Conditions:
- Positions are exited if either SuperTrend reverses its trend direction.
- Additional conditions include holding periods and configurable take-profit and stop-loss levels.
█ Trade Direction
The strategy allows traders to specify the desired trade direction through a customizable input setting. Options include:
- Long: Only enter long positions.
- Short: Only enter short positions.
- Both: Enter both long and short positions based on the market conditions.
█ Usage
To utilize the "Double Vegas SuperTrend Enhanced" strategy, traders need to configure the input settings according to their trading preferences and market conditions. The strategy includes parameters for ATR periods, Vegas Channel window lengths, SuperTrend multipliers, volatility adjustment factors, and risk management settings such as hold days, take-profit, and stop-loss percentages.
█ Default Settings
The strategy comes with default settings that can be adjusted to fit individual trading styles:
- trade Direction: Both (allows trading in both long and short directions for maximum flexibility).
- ATR Periods: 10 for SuperTrend 1 and 5 for SuperTrend 2 (shorter ATR period results in more sensitivity to recent price movements).
- Vegas Window Lengths: 100 for SuperTrend 1 and 200 for SuperTrend 2 (longer window length results in smoother moving averages and less sensitivity to short-term volatility).
- SuperTrend Multipliers: 5 for SuperTrend 1 and 7 for SuperTrend 2 (higher multipliers lead to wider SuperTrend channels, reducing the frequency of trades).
- Volatility Adjustment Factors: 5 for SuperTrend 1 and 7 for SuperTrend 2 (higher adjustment factors increase the responsiveness to changes in market volatility).
- Hold Days: 5 (defines the minimum duration a position is held, ensuring trades are not exited prematurely).
- Take Profit: 30% (sets the target profit level to lock in gains).
- Stop Loss: 20% (sets the maximum acceptable loss level to mitigate risk).
market slayerInput Parameters:
Various input parameters allow customization of the strategy, including options to show trend confirmation, specify trend timeframes and values, set SMA lengths, enable take profit and stop loss, and define their respective values.
Calculations:
Simple Moving Averages (SMAs) are calculated based on the specified lengths.
Buy and sell signals are generated based on the crossover and crossunder of the short and long SMAs.
Confirmation Bars:
Functions are defined to determine bullish or bearish confirmation bars based on certain conditions.
These confirmation bars are used to confirm trend direction and generate additional signals.
Plotting:
SMAs are plotted on the chart.
Trend labels and signal markers are plotted based on the calculated conditions.
Trade Signals:
Buy and sell conditions are defined based on the crossover/crossunder of SMAs and confirmation of trend direction.
Strategy entries and exits are executed accordingly.
Take Profit and Stop Loss:
Optional take profit and stop loss functionality is included.
Trades are automatically closed when profit or loss thresholds are reached.
Closing Trades:
Trades are also closed based on changes in trend confirmation bars to ensure alignment with the overall market direction.
Alerts:
Alert conditions are defined for opening and closing trades, providing notifications when certain conditions are met.
Overall, this script aims to provide a systematic approach to trading by combining moving average crossovers with trend confirmation bars, along with options for risk management through take profit and stop loss orders. Users can customize various parameters to adapt the strategy to different market conditions and trading preferences.
The script uses the request.security() function with the lookahead parameter set to barmerge.lookahead_on to access data from a higher timeframe within the Pine Script on TradingView. Let's break down why it's used:
Higher Timeframe Analysis:
By default, Pine Script operates on the timeframe of the chart it's applied to. However, in trading strategies, it's common to incorporate signals or data from higher timeframes to confirm or validate signals generated on lower timeframes. This helps traders to align their trades with the broader market trend.
Trend Confirmation:
In this script, the confirmationTrendTimeframe parameter allows users to specify a higher timeframe for trend confirmation. The request.security() function fetches the data from this higher timeframe and applies the defined conditions to confirm the trend direction.
Lookahead Behavior:
The lookahead parameter set to barmerge.lookahead_on ensures that the script considers the most up-to-date information available on the higher timeframe when making trading decisions on the lower timeframe. This prevents the script from lagging behind or using outdated data, enhancing the accuracy of trend confirmation.
Usage in confirmationTrendBullish and confirmationTrendBearish:
These variables are assigned the values returned by the request.security() function, which represents the bullish or bearish trend confirmation based on the conditions applied to the data from the higher timeframe.
Wunder False Breakout1. The basic concept for this strategy is to use false breakout logic based on price levels.
2. We will enter a trade when the price exhibits a false breakout, where it initially breaks a level but then reverses direction.
3. The main concept of this strategy is to capitalize on false breakouts of price levels. The strategy involves building levels based on the highs and lows over a certain period. When these price levels appear to break out but then reverse, we use these false breakouts as entry points. You can adjust the period to find setups that suit your trading pair and timeframe.
4. A function for calculating risk on the portfolio (your deposit) has been added to the Wunder False Breakout. When this option is enabled, you get a calculation of the entry amount in dollars relative to your Stop Loss. In the settings, you can select the risk percentage on your portfolio. The loss will be calculated from the amount that will be displayed on the chart.
5. For example, if your deposit is $1000 and you set the risk to 1%, with a Stop Loss of 5%, the entry volume will be $200. The loss at SL will be $10. 10$, which is your 1% risk or 1% of the deposit.
Important! The risk per trade must be less than the Stop Loss value. If the risk is greater than SL, then you should use leverage.
The amount of funds entering the trade is calculated in dollars. This option was created if you want to send the dollar amount from Tradingview to the exchange. However, putting your volume in dollars you get the incorrect net profit and drawdown indication in the backtest results, as TradingView calculates the backtest volume in contracts.
To display the correct net profit and drawdown values in Tradingview Backtest results, use the ”Volume in contract” option.
Multi-Timeframe Trend Following with 200 EMA Filter - Longs OnlyOverview
This strategy is designed to trade long positions based on multiple timeframe Exponential Moving Averages (EMAs) and a 200 EMA filter. The strategy ensures that trades are only entered in strong uptrends and aims to capitalize on sustained upward movements while minimizing risk with a defined stop-loss and take-profit mechanism.
Key Components
Initial Capital and Position Sizing
Initial Capital: $1000.
Lot Size: 1 unit per trade.
Inputs
Fast EMA Length (fast_length): The period for the fast EMA.
Slow EMA Length (slow_length): The period for the slow EMA.
200 EMA Length (filter_length_200): Set to 200 periods for the primary trend filter.
Stop Loss Percentage (stop_loss_perc): Set to 1% of the entry price.
Take Profit Percentage (take_profit_perc): Set to 3% of the entry price.
Timeframes and EMAs
EMAs are calculated for the following timeframes using the request.security function:
5-minute: Short-term trend detection.
15-minute: Intermediate-term trend detection.
30-minute: Long-term trend detection.
The strategy also calculates a 200-period EMA on the 5-minute timeframe to serve as a primary trend filter.
Trend Calculation
The strategy determines the trend for each timeframe by comparing the fast and slow EMAs:
If the fast EMA is above the slow EMA, the trend is considered positive (1).
If the fast EMA is below the slow EMA, the trend is considered negative (-1).
Combined Trend Signal
The combined trend signal is derived by summing the individual trends from the 5-minute, 15-minute, and 30-minute timeframes.
A combined trend value of 3 indicates a strong uptrend across all timeframes.
Any combined trend value less than 3 indicates a weakening or negative trend.
Entry and Exit Conditions
Entry Condition:
A long position is entered if:
The combined trend signal is 3 (indicating a strong uptrend across all timeframes).
The current close price is above the 200 EMA on the 5-minute timeframe.
Exit Condition:
The long position is exited if:
The combined trend signal is less than 3 (indicating a weakening trend).
The current close price falls below the 200 EMA on the 5-minute timeframe.
Stop Loss and Take Profit
Stop Loss: Set at 1% below the entry price.
Take Profit: Set at 3% above the entry price.
These levels are automatically set when entering a trade using the strategy.entry function with stop and limit parameters.
Plotting
The strategy plots the fast and slow EMAs for the 5-minute timeframe and the 200 EMA for visual reference on the chart:
Fast EMA (5-min): Plotted in blue.
Slow EMA (5-min): Plotted in red.
200 EMA (5-min): Plotted in green.
Wunder OI breakout1. The basic concept for this strategy is to breakout open interest levels.
2. Open interest indicates the total number of active positions in the market a sharp increase in which we will use to enter a trade.
3. The main concept of this strategy is to break open interest levels.The strategy is based on building levels based on the highs and lows over a certain period. The breakdown of the set levels is used for entry. You can change the period as well as the percentage of change in open interest to find setups based on your pair and timeframe.
4. A function for calculating risk on the portfolio (your deposit) has been added to the Wunder OI breakout. When this option is enabled, you get a calculation of the entry amount in dollars relative to your Stop Loss. In the settings, you can select the risk percentage on your portfolio. The loss will be calculated from the amount that will be displayed on the chart.
5. For example, if your deposit is $1000 and you set the risk to 1%, with a Stop Loss of 5%, the entry volume will be $200. The loss at SL will be $10. 10$, which is your 1% risk or 1% of the deposit.
Important! The risk per trade must be less than the Stop Loss value. If the risk is greater than SL, then you should use leverage.
The amount of funds entering the trade is calculated in dollars. This option was created if you want to send the dollar amount from Tradingview to the exchange. However, putting your volume in dollars you get the incorrect net profit and drawdown indication in the backtest results, as TradingView calculates the backtest volume in contracts.
To display the correct net profit and drawdown values in Tradingview Backtest results, use the ”Volume in contract” option.
Bitcoin Momentum StrategyThis is a very simple long-only strategy I've used since December 2022 to manage my Bitcoin position.
I'm sharing it as an open-source script for other traders to learn from the code and adapt it to their liking if they find the system concept interesting.
General Overview
Always do your own research and backtesting - this script is not intended to be traded blindly (no script should be) and I've done limited testing on other markets beyond Ethereum and BTC, it's just a template to tweak and play with and make into one's own.
The results shown in the strategy tester are from Bitcoin's inception so as to get a large sample size of trades, and potential returns have diminished significantly as BTC has grown to become a mega cap asset, but the script includes a date filter for backtesting and it has still performed solidly in recent years (speaking from personal experience using it myself - DYOR with the date filter).
The main advantage of this system in my opinion is in limiting the max drawdown significantly versus buy & hodl. Theoretically much better returns can be made by just holding, but that's also a good way to lose 70%+ of your capital in the inevitable bear markets (also speaking from experience).
In saying all of that, the future is fundamentally unknowable and past results in no way guarantee future performance.
System Concept:
Capture as much Bitcoin upside volatility as possible while side-stepping downside volatility as quickly as possible.
The system uses a simple but clever momentum-style trailing stop technique I learned from one of my trading mentors who uses this approach on momentum/trend-following stock market systems.
Basically, the system "ratchets" up the stop-loss to be much tighter during high bearish volatility to protect open profits from downside moves, but loosens the stop loss during sustained bullish momentum to let the position ride.
It is invested most of the time, unless BTC is trading below its 20-week EMA in which case it stays in cash/USDT to avoid holding through bear markets. It only trades one position (no pyramiding) and does not trade short, but can easily be tweaked to do whatever you like if you know what you're doing in Pine.
Default parameters:
HTF: Weekly Chart
EMA: 20-Period
ATR: 5-period
Bar Lookback: 7
Entry Rule #1:
Bitcoin's current price must be trading above its higher-timeframe EMA (Weekly 20 EMA).
Entry Rule #2:
Bitcoin must not be in 'caution' condition (no large bearish volatility swings recently).
Enter at next bar's open if conditions are met and we are not already involved in a trade.
"Caution" Condition:
Defined as true if BTC's recent 7-bar swing high minus current bar's low is > 1.5x ATR, or Daily close < Daily 20-EMA.
Trailing Stop:
Stop is trailed 1 ATR from recent swing high, or 20% of ATR if in caution condition (ie. 0.2 ATR).
Exit on next bar open upon a close below stop loss.
I typically use a limit order to open & exit trades as close to the open price as possible to reduce slippage, but the strategy script uses market orders.
I've never had any issues getting filled on limit orders close to the market price with BTC on the Daily timeframe, but if the exchange has relatively low slippage I've found market orders work fine too without much impact on the results particularly since BTC has consistently remained above $20k and highly liquid.
Cost of Trading:
The script uses no leverage and a default total round-trip commission of 0.3% which is what I pay on my exchange based on their tier structure, but this can vary widely from exchange to exchange and higher commission fees will have a significantly negative impact on realized gains so make sure to always input the correct theoretical commission cost when backtesting any script.
Static slippage is difficult to estimate in the strategy tester given the wide range of prices & liquidity BTC has experienced over the years and it largely depends on position size, I set it to 150 points per buy or sell as BTC is currently very liquid on the exchange I trade and I use limit orders where possible to enter/exit positions as close as possible to the market's open price as it significantly limits my slippage.
But again, this can vary a lot from exchange to exchange (for better or worse) and if BTC volatility is high at the time of execution this can have a negative impact on slippage and therefore real performance, so make sure to adjust it according to your exchange's tendencies.
Tax considerations should also be made based on short-term trade frequency if crypto profits are treated as a CGT event in your region.
Summary:
A simple, but effective and fairly robust system that achieves the goals I set for it.
From my preliminary testing it appears it may also work on altcoins but it might need a bit of tweaking/loosening with the trailing stop distance as the default parameters are designed to work with Bitcoin which obviously behaves very differently to smaller cap assets.
Good luck out there!
arpit bollinger bandStrategy Overview:
This strategy utilizes Bollinger Bands based on a 20-period Exponential Moving Average (EMA) with a standard deviation multiplier of 1.5. It is designed to generate early trading signals based on the relationship between the price action and the Bollinger Bands.
Bollinger Bands Calculation:
The upper Bollinger Band is calculated as the 20-period EMA of the closing prices plus 1.5 times the standard deviation of the same period.
The lower Bollinger Band is calculated as the 20-period EMA of the closing prices minus 1.5 times the standard deviation.
Entry Criteria:
Buy Signal: A buy signal is generated when the current candle's high exceeds the high of the candle two periods ago, which had closed below the lower Bollinger Band. This condition implies an anticipation of a bullish reversal.
Sell Signal: A sell signal is generated when the current candle's low falls below the low of the candle two periods ago, which had closed above the upper Bollinger Band. This condition suggests an anticipated bearish reversal.
Stop Loss and Take Profit:
The stop loss for a buy order is set slightly below the low of the current candle, and for a sell order, it is set slightly above the high of the current candle.
The take profit level is determined based on a predefined risk-reward ratio of 1:3. This means the take profit target is set at a distance three times greater than the distance between the entry price and the stop loss.
Risk Management:
The strategy includes an input option to adjust the risk-reward ratio, allowing for flexibility in managing the trade's potential risk versus reward.
Trade Execution:
The strategy automatically plots the buy and sell signals on the chart and executes the trades according to the defined conditions. It also visually indicates the stop loss levels for each trade.
Usage Notes:
This strategy is designed for use in the TradingView platform using Pine Script version 5.
It is important to backtest and paper trade the strategy before using it in live trading to understand its performance characteristics and risk profile.
The strategy should be used as part of a comprehensive trading plan, considering market conditions, trader risk tolerance, and personal trading goals.
Long EMA Strategy with Advanced Exit OptionsThis strategy is designed for traders seeking a trend-following system with a focus on precision and adaptability.
**Core Strategy Concept**
The essence of this strategy lies in use of Exponential Moving Averages (EMAs) to identify potential long (buy) positions based on the relative positions of short-term, medium-term, and long-term EMAs. The use of EMAs is a classic yet powerful approach to trend detection, as these indicators smooth out price data over time, emphasizing the direction of recent price movements and potentially signaling the beginning of new trends.
**Customizable Parameters**
- **EMA Periods**: Users can define the periods for three EMAs - long-term, medium-term, and short-term - allowing for a tailored approach to capture trends based on individual trading styles and market conditions.
- **Volatility Filter**: An optional Average True Range (ATR)-based volatility filter can be toggled on or off. When activated, it ensures that trades are only entered when market volatility exceeds a user-defined threshold, aiming to filter out entries during low-volatility periods which are often characterized by indecisive market movements.
- **Trailing Stop Loss**: A trailing stop loss mechanism, expressed as a percentage of the highest price achieved since entry, provides a dynamic way to manage risk by allowing profits to run while cutting losses.
- **EMA Exit Condition**: This advanced exit option enables closing positions when the short-term EMA crosses below the medium-term EMA, serving as a signal that the immediate trend may be reversing.
- **Close Below EMA Exit**: An additional exit condition, which is disabled by default, allows positions to be closed if the price closes below a user-selected EMA. This provides an extra layer of flexibility and risk management, catering to traders who prefer to exit positions based on specific EMA thresholds.
**Operational Mechanics**
Upon activation, the strategy evaluates the current price in relation to the set EMAs. A long position is considered when the current price is above the long-term EMA, and the short-term EMA is above the medium-term EMA. This setup aims to identify moments where the price momentum is strong and likely to continue.
The strategy's versatility is further enhanced by its optional settings:
- The **Volatility Filter** adjusts the sensitivity of the strategy to market movements, potentially improving the quality of the entries during volatile market conditions.
The Average True Range (ATR) is a key component of this filter, providing a measure of market volatility by calculating the average range between the high and low prices over a specified number of periods. Here's how you can adjust the volatility filter settings for various market conditions, focusing on filtering out low-volatility markets:
Setting Examples for Volatility Filter
1. High Volatility Markets (e.g., Cryptocurrencies, Certain Forex Pairs):
ATR Periods: 14 (default)
ATR Multiplier: Setting the multiplier to a lower value, such as 1.0 or 1.2, can be beneficial in high-volatility markets. This sensitivity allows the strategy to react to volatility changes more quickly, ensuring that you're entering trades during periods of significant movement.
2. Medium Volatility Markets (e.g., Major Equity Indices, Medium-Volatility Forex Pairs):
ATR Periods: 14 (default)
ATR Multiplier: A multiplier of 1.5 (default) is often suitable for medium volatility markets. It provides a balanced approach, ensuring that the strategy filters out low-volatility conditions without being overly restrictive.
3. Low Volatility Markets (e.g., Some Commodities, Low-Volatility Forex Pairs):
ATR Periods: Increasing the ATR period to 20 or 25 can smooth out the volatility measure, making it less sensitive to short-term fluctuations. This adjustment helps in focusing on more significant trends in inherently stable markets.
ATR Multiplier: Raising the multiplier to 2.0 or even 2.5 increases the threshold for volatility, effectively filtering out low-volatility conditions. This setting ensures that the strategy only triggers trades during periods of relatively higher volatility, which are more likely to result in significant price movements.
How to Use the Volatility Filter for Low-Volatility Markets
For traders specifically interested in filtering out low-volatility markets, the key is to adjust the ATR Multiplier to a higher level. This adjustment increases the threshold required for the market to be considered sufficiently volatile for trade entries. Here's a step-by-step guide:
Adjust the ATR Multiplier: Increase the ATR Multiplier to create a higher volatility threshold. A multiplier of 2.0 to 2.5 is a good starting point for very low-volatility markets.
Fine-Tune the ATR Periods: Consider lengthening the ATR calculation period if you find that the strategy is still entering trades in undesirable low-volatility conditions. A longer period provides a more averaged-out measure of volatility, which might better suit your needs.
Monitor and Adjust: Volatility is not static, and market conditions can change. Regularly review the performance of your strategy in the context of current market volatility and adjust the settings as necessary.
Backtest in Different Conditions: Before applying the strategy live, backtest it across different market conditions with your adjusted settings. This process helps ensure that your approach to filtering low-volatility conditions aligns with your trading objectives and risk tolerance.
By fine-tuning the volatility filter settings according to the specific characteristics of the market you're trading in, you can enhance the performance of this strategy
- The **Trailing Stop Loss** and **EMA Exit Conditions** provide two layers of exit strategies, focusing on capital preservation and profit maximization.
**Visualizations**
For clarity and ease of use, the strategy plots the three EMAs and, if enabled, the ATR threshold on the chart. These visual cues not only aid in decision-making but also help in understanding the market's current trend and volatility state.
**How to Use**
Traders can customize the EMA periods to fit their trading horizon, be it short, medium, or long-term trading. The volatility filter and exit options allow for further customization, making the strategy adaptable to different market conditions and personal risk tolerance levels.
By offering a blend of trend-following principles with advanced risk management features, this strategy aims to cater to a wide range of trading styles, from cautious to aggressive. Its strength lies in its flexibility, allowing traders to fine-tune settings to their specific needs, making it a potentially valuable tool in the arsenal of any trader looking for a disciplined approach to navigating the markets.
MACD + MA HTF Strategy - Dynamic SmoothingMACD + MA HTF Strategy - Dynamic Smoothing
The MACD alone generally gives too many false signals and is therefore often used in combination with different indicators. The basic idea to combine the MACD with a moving average on a higher time frame is a commonly used technique to only enter Longs in a uptrend and only Shorts in a downtrend while trading on lower timeframe charts. However, the main issue in many strategy scripts is that the HTF indicator is not visible on lower timecharts. With this strategy example I used the Dynamic Smoothing code to visualise the HTF MA filter to display on you lower timechart. This way it is easier to optimize the strategy settings to the instrument chart.
Orginality and Usefulness - Dynamic Smoothing
Visualizing a higher time frame on a lower timechart often gives jagged lines on your chart. As the calculation is done on less bars, compared to the bars you have open on your timechart. The dynamic smoothing factor is derived by taking the ratio of minutes of the higher time frame to the current time frame. This ensures the moving average remains fluid and consistent across different time frames, eliminating 'jagged' lines on your chart. This new MA value is then used as HTF filter on top of the MACD entry settings. Always make sure the time chart is equal or lower than the timeframe settings in the configuration settings. The intention of the script is to visualise the higher time frame confirmations while trading on a lower timechart.
Code example how to achieve Dynamic Smoothing:
// Get minutes for current and higher timeframes
// Function to convert a timeframe string to its equivalent in minutes
timeframeToMinutes(tf) =>
multiplier = 1
if (str.endswith(tf, "D"))
multiplier := 1440
else if (str.endswith(tf, "W"))
multiplier := 10080
else if (str.endswith(tf, "M"))
multiplier := 43200
else if (str.endswith(tf, "H"))
multiplier := int(str.tonumber(str.replace(tf, "H", "")))
else
multiplier := int(str.tonumber(str.replace(tf, "m", "")))
multiplier
// Get minutes for current and higher timeframes
currentTFMinutes = timeframeToMinutes(timeframe.period)
higherTFMinutes = timeframeToMinutes(TimeFrame_Trend)
// Calculate the smoothing factor
dynamicSmoothing = math.round(higherTFMinutes / currentTFMinutes)
MA_Value_Smooth = ta.sma(MA_Value_HTF, dynamicSmoothing)
Complete Strategy
The MACD and HTF moving average is used to determine when to enter a new position. However a strategy should consider more factors than only the timing of entering a trade. To complete the strategy I included:
an option to choose from different MA types per indicator
a Risk Management Tool
a Take Profit Logic
a Trailing stop loss
a Hard Stoploss
a visual representation of TP and SL
This is merely an example how to structure a strategy and many different setups are possible.
The features in this script are explained below:
Different MA types
The script supports various MA types like EMA, SMA, DEMA, TEMA, WMA and HMA. You can select the MA type and different timeframe to your liking.
Risk Management Tool
Traders can choose to allocate their position size based on a percentage of equity or a fixed number of contracts. This feature ensures prudent risk management and helps traders align their position sizes with their risk tolerance. In the strategy -0.5 is equal to 50% of equity and 1.5 is 150% of equity used. Make sure to align the % of equity with your maxdrawn results with backtesting. Personally I don't want higher max drawdowns than 15%. For the strategy results the script considers 0.05 commission rate on each trade, to stay conservative. For a more detailed explanation I refer to my earlier published tradingviewblog about risk management:
Take Profit Logic
The take profit logic in this script is designed for optimization, offering three distinct exit levels. Traders can customize these levels based on their risk appetite. The script allows adjustment of both the percentage take profit level and the position size, catering to individual trading strategies and objectives. The default settings closes 33% of the position when TP target is hit. The TP levels are simply calculated by inputting a % of of the entryprice.
Trailing Stop and Hard Stoploss
To mitigate downside risks and protect profits, the script incorporates a well-thought-out trailing stop mechanism based on the Average True Range (ATR). This dynamic trailing stop adapts to market volatility, allowing traders to secure gains while letting profitable positions run. Additionally, to prevent significant losses, a fixed stop loss is implemented, providing an added layer of protection.
Visual Representation of Take Profit and Stoploss Levels
For enhanced visualization, take profit and stoploss levels are displayed on the chart. Take profit levels are depicted with green lines, providing a clear indication of potential exit points. Conversely, the trailing stop loss is presented by the red line, serving as visual cues for risk management. Visualizing indicators makes is easier to optimize settings to your liking.
Ideal Settings and Accessibility
This script is intended to be used on lower timeframe charts like 10 to 30 minutes. You can Align the MACD entry settings equal to your opened timechart or use a slightly higher timeframe. For the MA trend filters, higher timeframe settings such as 30 min, 1 hour, 4 hours, or 1 day are recommended for trading the trend.
Disclaimer
Trading involves significant risk and may not be suitable for all investors. The information provided in this script is for educational purposes only and should not be considered as financial advice. Past performance is not indicative of future results. By using this script, you acknowledge that you understand and accept these risks.
Four WMA Strategy with TP and SLBasically I read a research paper on how they used different moving averages for long entries and short entries, and it kind of dawned on me that I always used the same one for long entry or exit, or even swing trading. So I smashed this together to see what would happen.
The strategy combines the use of four different WMAs for identifying trade entry points, along with a predefined take profit (TP) and stop loss (SL) for risk management. Here's a detailed description of its features and how it operates:
Main Features
1. **WMAs as the Core Indicator**:
- The strategy uses four WMAs with different lengths. Two WMAs (`longM1` and `longM2`) are used for long entry signals, and the other two (`shortM1` and `shortM2`) for short entry signals.
- The lengths of these WMAs are adjustable through input parameters.
2. **Trade Entry Conditions**:
- A long entry is signaled when the shorter WMA crosses under the longer WMA .
- Conversely, a short entry is signaled when the shorter WMA crosses under the longer WMA.
3. **Take Profit and Stop Loss**:
- The strategy includes a take profit and stop loss mechanism.
- The TP and SL levels are set as a percentage of the entry price, with the percentage values being adjustable through input parameters.
4. **Visual Representation**:
- The WMAs are plotted on the chart for visual aid, each with a distinct color for easy identification.
How It Works
- The strategy continuously monitors the crossing of WMAs to detect potential entry points for long and short positions.
- Upon detecting a long or short condition, it automatically enters a trade and sets the corresponding TP and SL levels based on the current price and the specified percentages.
- The strategy then actively manages the trade, exiting the position when either the TP or SL level is reached.
Drawbacks
- **Overreliance on WMAs**: The strategy heavily relies on WMAs for trade signals. While WMAs are useful for identifying trends, they might not always provide timely entry and exit signals.
- **Market Conditions**: It may not perform well in highly volatile or sideways markets where WMA crossovers could lead to false signals.
- **Risk Management**: The fixed percentage for TP and SL might not be suitable for all market conditions. Traders might need to adjust these values frequently based on market volatility and their risk tolerance.
Apparently I need to emphasize to use brains when using indicators and setting them up to achieve the results you can or want. Also risk of 12% is considered very high so I lowered the numbers to 5%, which tanked the profits, try adjusting them on your own. Check the properties settings for more info on comission and slippage.
Conclusion
The "Four WMA Strategy with TP and SL" is suitable for traders who prefer a moving average-based approach to trading, combined with a straightforward mechanism for risk management through take profit and stop loss. However, like all strategies, it should be used with an understanding of its limitations and ideally tested thoroughly in various market conditions before applying it to live trading.
Ichimoku Clouds Strategy Long and ShortOverview:
The Ichimoku Clouds Strategy leverages the Ichimoku Kinko Hyo technique to offer traders a range of innovative features, enhancing market analysis and trading efficiency. This strategy is distinct in its combination of standard methodology and advanced customization, making it suitable for both novice and experienced traders.
Unique Features:
Enhanced Interpretation: The strategy introduces weak, neutral, and strong bullish/bearish signals, enabling detailed interpretation of the Ichimoku cloud and direct chart plotting.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Dual Trading Modes: Long and Short modes are available, allowing alignment with market trends.
Flexible Risk Management: Offers three styles in each mode, combining fixed risk management with dynamic indicator states for versatile trade management.
Indicator Line Plotting: Enables plotting of Ichimoku indicator lines on the chart for visual decision-making support.
Methodology:
The strategy utilizes the standard Ichimoku Kinko Hyo model, interpreting indicator values with settings adjustable through a user-friendly menu. This approach is enhanced by TradingView's built-in strategy tester for customization and market selection.
Risk Management:
Our approach to risk management is dynamic and indicator-centric. With data from the last year, we focus on dynamic indicator states interpretations to mitigate manual setting causing human factor biases. Users still have the option to set a fixed stop loss and/or take profit per position using the corresponding parameters in settings, aligning with their risk tolerance.
Backtest Results:
Operating window: Date range of backtests is 2023.01.01 - 2024.01.04. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Maximum Single Position Loss: -6.29%
Maximum Single Profit: 22.32%
Net Profit: +10 901.95 USDT (+109.02%)
Total Trades: 119 (51.26% profitability)
Profit Factor: 1.775
Maximum Accumulated Loss: 4 185.37 USDT (-22.87%)
Average Profit per Trade: 91.67 USDT (+0.7%)
Average Trade Duration: 56 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters. Backtest is calculated using deep backtest option in TradingView built-in strategy tester
How to Use:
Add the script to favorites for easy access.
Apply to the desired chart and timeframe (optimal performance observed on the 1H chart, ForEx or cryptocurrency top-10 coins with quote asset USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
