Simple RSI stock Strategy [1D] The "Simple RSI Stock Strategy " is designed to long-term traders. Strategy uses a daily time frame to capitalize on signals generated by the Relative Strength Index (RSI) and the Simple Moving Average (SMA). This strategy is suitable for low-leverage trading environments and focuses on identifying potential buy opportunities when the market is oversold, while incorporating strong risk management with both dynamic and static Stop Loss mechanisms.
This strategy is recommended for use with a relatively small amount of capital and is best applied by diversifying across multiple stocks in a strong uptrend, particularly in the S&P 500 stock market. It is specifically designed for equities, and may not perform well in other markets such as commodities, forex, or cryptocurrencies, where different market dynamics and volatility patterns apply.
Indicators Used in the Strategy:
1. RSI (Relative Strength Index):
- The RSI is a momentum oscillator used to identify overbought and oversold conditions in the market.
- This strategy enters long positions when the RSI drops below the oversold level (default: 30), indicating a potential buying opportunity.
- It focuses on oversold conditions but uses a filter (SMA 200) to ensure trades are only made in the context of an overall uptrend.
2. SMA 200 (Simple Moving Average):
- The 200-period SMA serves as a trend filter, ensuring that trades are only executed when the price is above the SMA, signaling a bullish market.
- This filter helps to avoid entering trades in a downtrend, thereby reducing the risk of holding positions in a declining market.
3. ATR (Average True Range):
- The ATR is used to measure market volatility and is instrumental in setting the Stop Loss.
- By multiplying the ATR value by a custom multiplier (default: 1.5), the strategy dynamically adjusts the Stop Loss level based on market volatility, allowing for flexibility in risk management.
How the Strategy Works:
Entry Signals:
The strategy opens long positions when RSI indicates that the market is oversold (below 30), and the price is above the 200-period SMA. This ensures that the strategy buys into potential market bottoms within the context of a long-term uptrend.
Take Profit Levels:
The strategy defines three distinct Take Profit (TP) levels:
TP 1: A 5% from the entry price.
TP 2: A 10% from the entry price.
TP 3: A 15% from the entry price.
As each TP level is reached, the strategy closes portions of the position to secure profits: 33% of the position is closed at TP 1, 66% at TP 2, and 100% at TP 3.
Visualizing Target Points:
The strategy provides visual feedback by plotting plotshapes at each Take Profit level (TP 1, TP 2, TP 3). This allows traders to easily see the target profit levels on the chart, making it easier to monitor and manage positions as they approach key profit-taking areas.
Stop Loss Mechanism:
The strategy uses a dual Stop Loss system to effectively manage risk:
ATR Trailing Stop: This dynamic Stop Loss adjusts based on the ATR value and trails the price as the position moves in the trader’s favor. If a price reversal occurs and the market begins to trend downward, the trailing stop closes the position, locking in gains or minimizing losses.
Basic Stop Loss: Additionally, a fixed Stop Loss is set at 25%, limiting potential losses. This basic Stop Loss serves as a safeguard, automatically closing the position if the price drops 25% from the entry point. This higher Stop Loss is designed specifically for low-leverage trading, allowing more room for market fluctuations without prematurely closing positions.
to determine the level of stop loss and target point I used a piece of code by RafaelZioni, here is the script from which a piece of code was taken
Together, these mechanisms ensure that the strategy dynamically manages risk while offering robust protection against significant losses in case of sharp market downturns.
The position size has been estimated by me at 75% of the total capital. For optimal capital allocation, a recommended value based on the Kelly Criterion, which is calculated to be 59.13% of the total capital per trade, can also be considered.
Enjoy !
Cerca negli script per "TAKE"
Follow LineFollow Line is a common MT4 FX indicator based on trend following.
The main idea behind the calculation is volatility:
-Indicator Line increases as price goes above Bollinger Bands but with 1 standard deviation.
-Likewise when price moves below the lower Bollinger Band with 1 Standard deviation, Follow -Line decreases down.
-As you can imagine, indicator stays as a flat line when price moves between the bands.
There are two critical settings about the indicator:
1- Bollinger Bands Deviation is set to 1 as default but if you want to have early signals you have to decrease that amount. Also you'd better increase that to have flat values on sideways market conditions for not getting chopped by the early but false signals.
2- ATR Filter is activated in default settings and the indicator follows the trend with a distance from Highs and Lows considering ATR (default length 5) values. If you turn off the ATR filter, the indicator line only takes into account the Highs and the Lows. Indicator will get more agile but the risk of choppy signals can be taken that time. I personally advise you to increase the Bollinger Band Deviation from 1 to between 1.5-2 to stabilize the fake signals when ATR filter is turned off.
Signals can be shown on the graph:
BUY: when Follow Line changes direction from red to blue.(which means Price is above Bollinger Upper Band with 1 standard deviation)
SELL: when Follow Line changes direction from blue to red. (which means Price moves below Bollinger Lower Band with 1 standard deviation)
Finally, some of you may know there are also several Follow Line indicators on TradingView but unfortunately they don't show the same exact values (close but not same) comparing with original version of MT4 and the Metastock version that I've coded recently. So, I shared this stuff to have the exact same values on graphs on all platforms.
MM Relative Volume (RVOL)What this script does:
This script shows you the "Relative Volume" (RVOL) value up to the current minute. RVOL is the volume from market open up to the current minute today, compared to the average of the same over the last n (30 by default) days.
How this script works:
There are a lot of indicators out there for RVOL, but they all take shortcuts that result in sub-par data. This indicator goes the distance to store data for every minute for the last n days for the current chart, then in sums the volume up to the current minute today along with the average of the same up-to-the-minute data from the prior n days to calculate the relative volume of the stock. It's super important to get this data up to the current minute, because most traders use this information primarily during the first 90 minutes of trading, and need to know if this value is going up or down.
How to use this script:
Relative volume can be used to gauge how "In Play" a stock is. If RVOL is less than 1 it is not "In Play" on this trading day and you might not want to trade it. If RVOL is above 2, it is "In Play" and you may want to trade it. When stocks are very "In Play", you can see an RVOL of 5 and above. The higher the RVOL the more "In Play" the stock is. You can also used RVOL for position sizing. If RVOL is <1 you may decide not to take a large position in the name. If RVOL is >3, this may give you more confidence to take a larger position as more reward and more liquidity should be present.
What makes this script original:
This particular implementation of RVOL has never been done before on TradingView to my knowledge. Most other indicators use a rolling average of the prior 30 days which is much easier to do, but this doesn't actually work properly because instead of getting large volume spikes from prior days filtered out correctly, it takes a LOT longer for those to even out as the rolling average eventually smooths down. Instead, with this indicator, any large/small volume days will truly drop off after the moving average length and the calculated average daily volume (ADV) will be accurate up to the minute. For more details on the original concept behind this indicator, check out the blog linked on my profile.
Daily Moving Average for Intraday TimeframesThis indicator provides a dynamic tool for visualizing the Daily Moving Average (DMA) on intraday timeframes.
It allows you to analyze how the price behaves in relation to the daily moving average in timeframes from 1 minute up to 1 day.
KEY FEATURES
DMA on Intraday timeframes only : This indicator is designed to work exclusively on intraday charts with timeframes between 1 minute and 1 day. It will not function on tick, second-based, or daily-and-above charts.
Color-Coded Zones for Trend Identification :
Green Zone: The price is above a rising DMA, signaling a bullish momentum.
Red Zone: The price is below a falling DMA, signaling a bearish momentum.
Yellow Zone: Signaling uncertainty or mixed conditions, where either the price is above a falling DMA or below a rising/flat DMA.
Configurable DMA Period : You can adjust the number of days over which the DMA is calculated (default is 5 days). This can be customized based on your trading strategy or market preferences.
24/7 Market Option : For assets that trade continuously (e.g., cryptocurrencies), activate the "Is trading 24/7?" setting to ensure accurate calculations.
WHAT IS THE DMA AND WHY USE IT INTRADAY?
The Daily Moving Average is a Simple Moving Average indicator used to smooth out price fluctuations over a specified period (in days) and reveal the underlying trend.
Typically, a SMA takes price value for the current timeframe and reveal the trend for this timeframe. It gives you the average price for the last N candles for the given timeframe.
But what makes the Intraday DMA interesting is that it shows the underlying trend of the Daily timeframe on a chart set on a shorter timeframe . This helps to align intraday trades with broader market movements.
HOW IS THE DMA CALCULATED?
If we are to build a N-day Daily Moving Average using a Simple Moving Average, we need to take the amount of candles A needed in that timeframe to account for a period of a day and multiply it by the number of days N of the desired DMA.
So for instance, let say we want to compute the 5-Day DMA on the 10 minute timeframe :
In the 10 minute timeframe there are 39 candles in a day in the regular session.
We would take the 39 candles per day and then multiply that by 5 days. 39 x 5 = 195.
So a 5-day moving average is represented by a simple moving average with a period of 195 when looking at a 10 minute timeframe.
So for each period, to create a 5-day DMA, you would have to set the period of your simple moving average like so :
- 195 minutes = 10 period
- 130 minutes = 15 period
- 65 minutes = 30 period
- 30 minutes = 65 period
- 15 minutes = 130 period
- 10 minutes = 195 period
- 5 minutes = 390 period
and so on.
This indicator attempts to do this calculation for you on any intraday timeframe and whatever the period you want to use is for your DMA. You can create a 10-day moving average, a 30-day moving average, etc.
Stochastic RSI Strategy with Inverted Trend LogicOverview:
The Stochastic RSI Strategy with Inverted Trend Logic is a custom-built Pine Script indicator that leverages the Stochastic RSI and a 200-period moving average to generate precise buy and sell signals. It is specifically designed for traders looking to capture opportunities during short-term market movements while factoring in broader trend conditions.
Key Components:
Stochastic RSI:
Stochastic RSI is a momentum indicator that applies stochastic calculations to the standard Relative Strength Index (RSI), rather than price data. This makes it particularly sensitive to market momentum changes, which is essential for timing entries and exits.
K Line and D Line: The indicator calculates and smooths both the K and D lines to capture momentum shifts more accurately.
200-Period Moving Average:
The 200-period Simple Moving Average (SMA) is used as a trend filter.
If the price is above the 200-period SMA, the trend is considered bullish.
If the price is below the 200-period SMA, the trend is considered bearish.
Inverted Trading Logic:
The trading logic is inverted from traditional strategies:
Long trades are executed only when the market is in a bearish trend (price below the 200-period moving average).
Short trades are executed only when the market is in a bullish trend (price above the 200-period moving average).
This inversion allows traders to take advantage of potential trend reversals by entering positions in the opposite direction of the prevailing trend.
Trading Rules:
Long Trade Conditions (Buy Signal):
The Stochastic RSI K line must be below 5 for 4 consecutive candles (oversold condition).
The price must be below the 200-period SMA (indicating a bearish trend).
Once these conditions are met, the indicator will generate a buy signal on the close of the 4th candle.
Exit Condition: The long position is exited when the Stochastic RSI K line crosses above 50 (neutral level).
Short Trade Conditions (Sell Signal):
The Stochastic RSI K line must be above 95 for 4 consecutive candles (overbought condition).
The price must be above the 200-period SMA (indicating a bullish trend).
Once these conditions are met, the indicator will generate a sell signal on the close of the 4th candle.
Exit Condition: The short position is exited when the Stochastic RSI K line crosses below 50.
Visual Signals on the Chart:
Buy Signal:
A green triangle below the bar is displayed on the chart when a buy condition is met, indicating a potential long trade opportunity.
The text "BUY" is displayed for further clarity.
Sell Signal:
A red triangle above the bar is displayed on the chart when a sell condition is met, indicating a potential short trade opportunity.
The text "SELL" is displayed for further clarity.
How to Use the Indicator:
Attach the Indicator: Apply the indicator to your desired chart (works on any time frame, but is optimized for short- to medium-term trading).
Monitor Signals: Watch for buy and sell signals on the chart:
Buy Signal: Enter long positions when a green triangle appears below the candle.
Sell Signal: Enter short positions when a red triangle appears above the candle.
Exit Positions: Exit long positions when the Stochastic RSI crosses above the 50 level, and exit short positions when the Stochastic RSI crosses below the 50 level.
Indicator Display:
Stochastic RSI: A visual representation of the Stochastic RSI (K and D lines) is plotted below the price chart, with overbought (100), midpoint (50), and oversold (0) levels clearly marked.
200-period SMA: The 200-period moving average is plotted on the price chart, giving a clear indication of the broader trend direction (orange line).
Key Benefits:
Reversal Opportunities: This strategy allows traders to capture reversal trades by using an inverted logic where longs are taken in bearish conditions and shorts are taken in bullish conditions. This can help capitalize on potential trend exhaustion and reversals.
Clear and Simple Rules: The use of Stochastic RSI and the 200-period moving average ensures the strategy remains simple yet effective, making it easy for traders to follow.
Visual Alerts: The indicator provides clear buy and sell signals, making it easy for traders to spot trading opportunities in real-time without needing to monitor multiple conditions manually.
Limitations and Considerations:
Trend Changes: Since the strategy is designed to work during trend reversals, it might not perform as well during strong, prolonged trends where price continues moving in one direction without significant pullbacks.
Time Frame Suitability: While the indicator works on any time frame, shorter time frames may result in more frequent signals and higher trade frequency, whereas higher time frames will provide fewer but potentially stronger signals.
Conclusion:
The Stochastic RSI Strategy with Inverted Trend Logic is a powerful tool for traders looking to capture market reversals by entering trades against the prevailing trend direction based on momentum exhaustion. Its simple and clear logic, combined with easy-to-understand visual signals, makes it a versatile indicator for both novice and experienced traders.
Password Generator by Chervolino [CHE]Enhancing Password Security with Pine Script: A Deep Dive into Brute-Force Attack Prevention
1. Introduction: The Importance of Password Security
Why Password Security Matters:
In today’s digital age, protecting sensitive information through strong passwords is vital. Weak passwords are vulnerable to brute-force attacks, where attackers try every possible character combination until they guess the correct one.
What is Pine Script?
Pine Script is a scripting language developed by TradingView. While mainly used for financial analysis and strategy creation, its versatility allows us to explore other domains, such as password generation and security analysis.
2. Understanding Brute-Force Attacks
What is a Brute-Force Attack?
A brute-force attack systematically tries every possible combination of characters until the correct password is found. The longer and more complex the password, the more secure it is.
Types of Characters in Passwords:
Lowercase Letters (26 characters): Examples include 'a' to 'z'.
Uppercase Letters (26 characters): Examples include 'A' to 'Z'.
Digits (10 characters): Examples include '0' to '9'.
Special Characters: Characters such as '!@#$%^&*' add further complexity to a password.
3. The Role of Password Length in Security
Why Does Password Length Matter?
The number of possible combinations grows exponentially as the length of the password increases.
For example, a password made of only lowercase letters has 26 possible characters. A 7-character password in this case has 26 raised to the power of 7 possible combinations, which equals about 8 billion possibilities.
In comparison, if uppercase letters are included, the possible combinations jump to 52 raised to the power of 7, resulting in over 1 trillion combinations.
Time to Crack a Password:
Assuming a computer can test 2.15 billion passwords per second:
A 7-character password with only lowercase letters can be cracked in about 3.74 seconds.
If uppercase letters are added, it takes approximately 8 minutes.
Adding numbers and special characters makes the cracking time increase further to hours or even days.
4. Password Strength Analysis Using Pine Script
How Pine Script Helps in Password Analysis:
Pine Script can simulate password strength by generating random passwords and calculating how long it would take for a brute-force attack to crack them based on different character combinations and lengths.
We can experiment with using different types of characters (uppercase, lowercase, digits, special characters) and varying the length of the password to estimate the security.
For example:
A password consisting only of lowercase letters would take just a few seconds to crack.
By adding uppercase letters, the time increases to several minutes.
Including digits and special characters can make a password secure for many hours, or even days, depending on the length.
5. Results: Time to Crack Passwords
Here’s a textual summary of how different passwords can be cracked based on their composition and length:
Password with Lowercase Letters Only:
Length: 8 characters
Time to Crack: Less than 1 second.
Password with Uppercase and Lowercase Letters:
Length: 8 characters
Time to Crack: Approximately 24 hours.
Password with Uppercase, Lowercase, and Digits:
Length: 8 characters
Time to Crack: Around 27 minutes.
Password with Uppercase, Lowercase, Digits, and Special Characters:
Length: 12 characters
Time to Crack: Several hundred years.
From these examples, you can see that adding complexity to a password by using a variety of character types and increasing its length exponentially increases the time required to crack it.
6. Best Practices for Password Security
Use a mix of character types: Include lowercase and uppercase letters, digits, and special characters to increase complexity.
Increase the password length: The longer the password, the more difficult it is to crack.
Avoid predictable patterns: Refrain from using common words, dates, or sequential characters like "123456" or "password123".
Use a password manager: Tools like 1Password or LastPass can help store and manage complex passwords securely, so you only need to remember one master password.
7. Conclusion
Password length and complexity are the two most important factors in protecting against brute-force attacks.
Pine Script offers a powerful way to simulate password generation and security analysis, giving you insights into how secure your password is and how long it would take to crack it.
By applying these techniques, you can ensure that your passwords are strong and secure, making brute-force attacks infeasible.
Z-Score AggregatorOverview:
This indicator is designed to take multiple other indicators as inputs, calculate their respective Z-scores, and then aggregate these Z-scores to provide a comprehensive measure. By transforming the inputs into Z-scores, this indicator standardizes the data, enabling a more accurate comparison across different indicators, each of which may have different scales and distributions.
This indicator is beneficial for Mean-Reversion style trading and investing as it standardizes indicators and lets them work together in one system.
The Z-score, which represents how many standard deviations an element is from the mean, is a crucial statistical tool in this process. It allows the indicator to normalize the varying data points, ensuring that each indicator's contribution to the aggregate score is proportional to its deviation from the average performance.
Inputs:
Z-score length: How far Back it will take into account the inputs
Number Of Sources: This is to set the number of inputs the indicator uses so it calculates them properly and uses only the number of indicators you want.
Source Inputs: 1-10 inputs (no need to use them all as long as you set the number of used indicators beforehand).
Note:
There are three indicators used in this example which are CCI, RSI and Sharpe Ratio. The indicator calculates their individual Z-scores and takes an average. Because Number Of Sources is set to 3 it only uses the first 3 indicators in use.
ka66: Bar Range BandsThis tool takes a bar's range, and reflects it above the high and below the low of that bar, drawing upper and lower bands around the bar. Repeated for each bar. There's an option to then multiply that range by some multiple. Use a value greater than 1 to get wider bands, and less than one to get narrower bands.
This tool stems out of my frustration from the use of dynamic bands (like Keltner Channels, or Bollinger Bands), in particular for estimating take profit points.
Dynamic bands work great for entries and stop loss, but their dynamism is less useful for a future event like taking profit, in my experience. We can use a smaller multiple, but then we can often lose out on a bigger chunk of gains unnecessarily.
The inspiration for this came from a friend explaining an ICT/SMC concept around estimating the magnitude of a trend, by calculating the Asian Session Range, and reflecting it above or below on to the New York and London sessions. He described this as standard deviation of the Asian Range, where the range can thus be multiplied by some multiple for a wider or narrower deviation.
This, in turn, also reminded me of the Measured Move concept in Technical Analysis. We then consider that the market is fractal in nature, and this is why patterns persist in most timeframes. Traders exist across the spectrum of timeframes. Thus, a single bar on a timeframe, is made up of multiple bars on a lower timeframe . In other words, when we reflect a bar's range above or below itself, in the event that in a lower timeframe, that bar fit a pattern whose take profit target could be estimated via a Measured Move , then the band's value becomes a more valid estimate of a take profit point .
Yet another way to think about it, by way of the fractal nature above, is that it is essentially a simplified dynamic support and resistance mechanism , even simpler than say the various Pivot calculations (e.g. Classical, Camarilla, etc.).
This tool in general, can also be used by those who manually backtest setups (and certainly can be used in an automated setting too!). It is a research tool in that regard, applicable to various setups.
One of the pitfalls of manual backtesting is that it requires more discipline to really determine an exit point, because it's easy to say "oh, I'll know more or less where to exit when I go live, I just want to see that the entry tends to work". From experience, this is a bad idea, because our mind subconsciously knows that we haven't got a trained reflex on where to exit. The setup may be decent, but without an exit point, we will never have truly embraced and internalised trading it. Again, I speak from experience!
Thus, to use this to research take profit/exit points:
Have a setup in mind, with all the entry rules.
Plot your setup's indicators, mark your signals.
Use this indicator to get an idea of where to exit after taking an entry based on your signal.
Credits:
@ICT_ID for providing the idea of using ranges to estimate how far a trend move might go, in particular he used the Asian Range projected on to the London and New York market sessions.
All the technicians who came up with the idea of the Measured Move.
Qty CalculatorThis Pine Script indicator, titled "Qty Calculator," is a customizable tool designed to assist traders in managing their trades by calculating key metrics related to risk management. It takes into account your total capital, entry price, stop-loss level, and desired risk percentage to provide a comprehensive overview of potential trade outcomes.
Key Features:
User Inputs:
Total Capital: The total amount of money available for trading.
Entry Price: The price at which the trader enters the trade.
Stop Loss: The price level at which the trade will automatically close to prevent further losses.
Risk Percentage: The percentage of the total capital that the trader is willing to risk on a single trade.
Customizable Table:
Position: The indicator allows you to choose the position of the table on the chart, with options including top-left, top-center, top-right, bottom-left, bottom-center, and bottom-right.
Size: You can adjust the number of rows and columns in the table to fit your needs.
Risk Management Calculations:
Difference Calculation: The difference between the entry price and the stop-loss level.
Risk Per Trade: Calculated as a percentage of your total capital.
Risk Levels: The indicator evaluates multiple risk levels (0.10%, 0.25%, 0.50%, 1.00%) and calculates the quantity, capital per trade, percentage of total capital, and the risk amount associated with each level.
R-Multiples Calculation:
The indicator calculates potential profit levels at 2x, 3x, 4x, and 5x the risk (R-Multiples), showing the potential gains if the trade moves in your favor by these multiples.
Table Display:
The table includes the following columns:
CapRisk%: Displays the risk percentage.
Qty: The quantity of the asset you should trade.
Cap/Trade: The capital allocated per trade.
%OfCapital: The percentage of total capital used in the trade.
Risk Amount: The monetary risk taken on each trade.
R Gains: Displays potential gains at different R-Multiples.
This indicator is particularly useful for traders who prioritize risk management and want to ensure that their trades are aligned with their capital and risk tolerance. By providing a clear and customizable table of critical metrics, it helps traders make informed decisions and better manage their trading strategies.
AB_Bnf_Selling_5minThe Mathematical Level Reversal Strategy is designed to identify potential reversal points in the market using mathematical levels combined with price action on a 5-minute chart. This strategy is particularly effective for intraday traders who seek to capitalize on precise entry and exit points based on calculated levels rather than traditional indicators like moving averages or Bollinger Bands.
Creators' Mathematical Levels Explanation
Mathematical levels are predetermined price points calculated based on various factors such as previous high/low points, Fibonacci retracements, or other arithmetic calculations. These levels are used to anticipate areas where the price might reverse or experience significant support or resistance.
higher threshold: A predefined level where the price is expected to experience resistance, leading to a potential reversal downward.
Lower Threshold: A predefined level where the price might find support, leading to a potential upward reversal.
In this strategy, we focus on price movements around the upper mathematical level, where prices are likely to reverse downwards.
Strategy Logic
Setup:
The strategy is applied on a 5-minute chart.
Mathematical levels are calculated based on your preferred method, such as Fibonacci levels, pivot points, or custom calculations. For this strategy, let's assume we are using a specific predefined upper level.
Sell Signal Criteria:
A 5-minute candle must cross above the predefined upper mathematical level or close entirely above it (open and close both above the level).
The following candle must break below the low of the candle that crossed the upper level and close below that low. This confirms a bearish reversal.
Once these conditions are met, a sell signal is triggered.
Stop Loss:
The stop loss is placed at the high of the candle that crossed above the upper mathematical level.
This level represents the point where the trade setup would be invalidated.
Take Profit:
Target 1: The first take profit is set at a level that offers a 1:5 risk-to-reward ratio.
Target 2: An alternative take profit level is set at a 1:3 risk-to-reward ratio, providing flexibility based on market conditions.
Trade Management:
Once a trade is initiated, no new trades will be taken until the current trade hits either the stop loss or the first take profit level. This prevents overlapping signals and helps in managing risk effectively.
Originality and Usefulness
This strategy offers a unique approach by using mathematical levels instead of traditional indicators. It provides traders with a clear framework for identifying and executing high-probability reversal trades, particularly in intraday markets.
Originality:
The strategy's originality lies in its reliance on mathematical levels combined with a multi-candle confirmation pattern. This approach reduces the chances of false signals and offers a robust method for identifying potential reversals.
Usefulness:
The strategy is particularly useful for traders who prefer a more quantitative approach, relying on calculated price levels rather than indicators. The clear rules for entry, stop loss, and take profit make it easier to execute consistently.
The inclusion of both 1:5 and 1:3 risk-to-reward targets allows for flexibility depending on market conditions, ensuring that traders can adapt to varying levels of volatility.
Chart Signals and Examples
To demonstrate the effectiveness of this strategy, let's look at a few hypothetical examples on a 5-minute chart:
Example 1: Clear Reversal Signal
The price steadily rises and crosses above the predefined upper mathematical level. The next candle breaks below the low of this candle and closes lower, triggering a sell signal.
A red dotted line is drawn at the stop loss level (the high of the candle that crossed the upper level).
Two green dashed lines are drawn to indicate the first and second take profit levels.
Example 2: No Signal Due to Ongoing Trade
After an initial sell signal is triggered, the price fluctuates but does not hit either the stop loss or the first take profit target. During this period, the strategy refrains from issuing any new signals, adhering to the trade management rule.
Example 3: Trade Reaches Target 1
In another scenario, the price moves sharply in favor of the trade after the signal is triggered. The first take profit level is hit, securing a profit. The trade is then considered closed, and the strategy is ready to issue a new signal when conditions are met.
Correlation Clusters [LuxAlgo]The Correlation Clusters is a machine learning tool that allows traders to group sets of tickers with a similar correlation coefficient to a user-set reference ticker.
The tool calculates the correlation coefficients between 10 user-set tickers and a user-set reference ticker, with the possibility of forming up to 10 clusters.
🔶 USAGE
Applying clustering methods to correlation analysis allows traders to quickly identify which set of tickers are correlated with a reference ticker, rather than having to look at them one by one or using a more tedious approach such as correlation matrices.
Tickers belonging to a cluster may also be more likely to have a higher mutual correlation. The image above shows the detailed parts of the Correlation Clusters tool.
The correlation coefficient between two assets allows traders to see how these assets behave in relation to each other. It can take values between +1.0 and -1.0 with the following meaning
Value near +1.0: Both assets behave in a similar way, moving up or down at the same time
Value close to 0.0: No correlation, both assets behave independently
Value near -1.0: Both assets have opposite behavior when one moves up the other moves down, and vice versa
There is a wide range of trading strategies that make use of correlation coefficients between assets, some examples are:
Pair Trading: Traders may wish to take advantage of divergences in the price movements of highly positively correlated assets; even highly positively correlated assets do not always move in the same direction; when assets with a correlation close to +1.0 diverge in their behavior, traders may see this as an opportunity to buy one and sell the other in the expectation that the assets will return to the likely same price behavior.
Sector rotation: Traders may want to favor some sectors that are expected to perform in the next cycle, tracking the correlation between different sectors and between the sector and the overall market.
Diversification: Traders can aim to have a diversified portfolio of uncorrelated assets. From a risk management perspective, it is useful to know the correlation between the assets in your portfolio, if you hold equal positions in positively correlated assets, your risk is tilted in the same direction, so if the assets move against you, your risk is doubled. You can avoid this increased risk by choosing uncorrelated assets so that they move independently.
Hedging: Traders may want to hedge positions with correlated assets, from a hedging perspective, if you are long an asset, you can hedge going long a negatively correlated asset or going short a positively correlated asset.
Grouping different assets with similar behavior can be very helpful to traders to avoid over-exposure to those assets, traders may have multiple long positions on different assets as a way of minimizing overall risk when in reality if those assets are part of the same cluster traders are maximizing their risk by taking positions on assets with the same behavior.
As a rule of thumb, a trader can minimize risk via diversification by taking positions on assets with no correlations, the proposed tool can effectively show a set of uncorrelated candidates from the reference ticker if one or more clusters centroids are located near 0.
🔶 DETAILS
K-means clustering is a popular machine-learning algorithm that finds observations in a data set that are similar to each other and places them in a group.
The process starts by randomly assigning each data point to an initial group and calculating the centroid for each. A centroid is the center of the group. K-means clustering forms the groups in such a way that the variances between the data points and the centroid of the cluster are minimized.
It's an unsupervised method because it starts without labels and then forms and labels groups itself.
🔹 Execution Window
In the image above we can see how different execution windows provide different correlation coefficients, informing traders of the different behavior of the same assets over different time periods.
Users can filter the data used to calculate correlations by number of bars, by time, or not at all, using all available data. For example, if the chart timeframe is 15m, traders may want to know how different assets behave over the last 7 days (one week), or for an hourly chart set an execution window of one month, or one year for a daily chart. The default setting is to use data from the last 50 bars.
🔹 Clusters
On this graph, we can see different clusters for the same data. The clusters are identified by different colors and the dotted lines show the centroids of each cluster.
Traders can select up to 10 clusters, however, do note that selecting 10 clusters can lead to only 4 or 5 returned clusters, this is caused by the machine learning algorithm not detecting any more data points deviating from already detected clusters.
Traders can fine-tune the algorithm by changing the 'Cluster Threshold' and 'Max Iterations' settings, but if you are not familiar with them we advise you not to change these settings, the defaults can work fine for the application of this tool.
🔹 Correlations
Different correlations mean different behaviors respecting the same asset, as we can see in the chart above.
All correlations are found against the same asset, traders can use the chart ticker or manually set one of their choices from the settings panel. Then they can select the 10 tickers to be used to find the correlation coefficients, which can be useful to analyze how different types of assets behave against the same asset.
🔶 SETTINGS
Execution Window Mode: Choose how the tool collects data, filter data by number of bars, time, or no filtering at all, using all available data.
Execute on Last X Bars: Number of bars for data collection when the 'Bars' execution window mode is active.
Execute on Last: Time window for data collection when the `Time` execution window mode is active. These are full periods, so `Day` means the last 24 hours, `Week` means the last 7 days, and so on.
🔹 Clusters
Number of Clusters: Number of clusters to detect up to 10. Only clusters with data points are displayed.
Cluster Threshold: Number used to compare a new centroid within the same cluster. The lower the number, the more accurate the centroid will be.
Max Iterations: Maximum number of calculations to detect a cluster. A high value may lead to a timeout runtime error (loop takes too long).
🔹 Ticker of Reference
Use Chart Ticker as Reference: Enable/disable the use of the current chart ticker to get the correlation against all other tickers selected by the user.
Custom Ticker: Custom ticker to get the correlation against all the other tickers selected by the user.
🔹 Correlation Tickers
Select the 10 tickers for which you wish to obtain the correlation against the reference ticker.
🔹 Style
Text Size: Select the size of the text to be displayed.
Display Size: Select the size of the correlation chart to be displayed, up to 500 bars.
Box Height: Select the height of the boxes to be displayed. A high height will cause overlapping if the boxes are close together.
Clusters Colors: Choose a custom colour for each cluster.
Three Drive Pattern Detector [LuxAlgo]The Three Drives Pattern Detector indicator focuses on detecting and displaying completed Three Drives patterns on the user chart. This harmonic pattern is characterized by successive higher highs / lower lows following specific ratios.
The script uses a multi-length swing detection approach, as well as adjusting ratios to ensure flexibility and a maximum number of visible Three Drives patterns.
🔶 USAGE
The bullish/bearish Three Drives pattern is commonly interpreted as a reversal pattern and is characterized by three extensions (drives) and two intermediary retracements creating consecutive higher lows (for a bullish case) or lower highs (for a bearish case).
The multi-length swing detection approach taken by the indicator allows for detecting shorter-term alongside medium/longer-term patterns simultaneously, allowing to increase in the amount of detected patterns.
Users can set a Minimum Swing length (for example 2) and a Maximum Swing length (for example 100) which defines the range of the swing point detection length, higher values for these settings will detect longer-term Three-Drives patterns, while a larger range will allow for the detection of a larger number of patterns.
Sometimes multiple dashed lines as the last segment can be observed. This means multiple Three Drives patterns sharing multiple swing points have formed, with only the last segment being different.
🔹 Retracement/Extension Ratios
The Three Drives pattern often associates the retracement/extension to Fibonacci ratios of respectively 0.618/1.272.
Some sources specify a maximum retracement/extension level of 0.786/1.618, which means the retracement should be within the 0.618-0.786 range and the extension between 1.272-1.618.
Since finding a pattern where the retracement/extension is precisely at the 0.618/1.272 levels, or even between 0.618-0.786/1.272-1.618 is rare, the script allows users to adjust those ratios, which ensures more flexibility. Depending on the widening/tightening of the ratios, allowing users to find more patterns (but potentially less valid) or more valid (but fewer patterns).
In the example above, " Show Ratios " is set to " Ratios With Margin ", showing the ideal retracement/extension level together with the margin, while in the example below, " Show Ratios " is set to " Ratios ", which shows only a line where the price should ideally reverse.
While setting the ratios wider will result in more frequent but less valid patterns, it can also create good trading opportunities.
🔹 Best Practices
The indicator doesn't include Stop Loss (SL) or Take Profit (TP) levels, however, the 1.618 Fibonacci Extension level of the last leg can commonly be used as stop loss.
Typical Take Profit areas include:
Starting point of the pattern
Each retracement level (2x)
The 0.618 retracement level of the complete pattern
In the above bullish examples, the price was lower than the lowest point of the pattern. The price reversed and attained all TP levels without hitting the SL level.
In the above bearish example, the price went above the highest point of the pattern but did not hit the SL level, after which two TP levels were hit. Then, the price quickly went up, just missing the SL level before it came back down again, hitting the last 2 TP levels.
This example shows that other Fibonacci levels an also be effective when combined with the Three Drives pattern, even in the longer term.
🔶 DETAILS
🔹 Multi Length
The core of this publication is the multi-length swing detection. To ensure the maximum amount of Three Drives patterns are found, up to 99 different swing length periods can be used to detect swing points which are then tested for valid patterns.
Using a wider variety of swing points also ensures that patterns visible only with specific Swing settings can be found on the same chart without the user needing to constantly adjust the Swing settings to find other patterns.
The user only needs to set the desired minimum and maximum Swing Length.
In this case, swing detection using swing Lengths from 3 to 100 (97 different) are computed and evaluated for patterns. Three different patterns were found on the same chart, with swing lengths 3, 4, and 6.
Note: The Maximum Swing length should be equal to or higher than the Minimum Swing Length . If the maximum value is lower than the minimum, the script will automatically take the minimum value as the maximum to prevent errors.
🔹 Width Margin %
Users can filter out patterns based on the duration of each extension/retracement segment. When the users want segments of the detected patterns to be of a similar duration, the width percentage should be set lower. When the focus is on detecting more patterns the width percentage can be set higher.
🔹 Retracement/Extension Settings
Show Ratios , set to Ratios , show the ideal Fibonacci retracement/extension level, while Ratios With Margin (example below) show the additional margins for retracement/extension.
The upper and lower limits can be visualized while hovering over the calculated ratio label.
The dashed line shows an older pattern, where the last leg has been updated.
🔹 Last Known Pattern
The included dashboard highlights the date of the most recently detected pattern; the text will show " None " if no pattern is found.
🔹 Calculated Bars
The "Calculated Bars" setting makes use of the recently introduced calc_bars_count parameter, making it possible to effectively reduce the number of historical bars during the computation of the script, which significantly improves the loading speed of the script.
Users wishing to see the most recent patterns can set this setting to 1000 for example, where only the most recent 1000 bars are used to find patterns. If every bar must be used for pattern detection, set " Calculated bars " at 0.
🔶 SETTINGS
Minimum Swing Length: Minimum length used for the swing detection.
Maximum Swing Length: Maximum length used for the swing detection.
Retracement: Range of required ratios used for testing retracements.
Extension: Range of required ratios used for testing extensions.
Width Margin: Influences the symmetry of the pattern; with a higher number allowing for less symmetry.
🔹 Style
Text Size: Text size of the ratio labels.
Show Ratios: Show the ideal ratio, upper/lower limit of ratios, or none.
🔹 Dashboard
Show Dashboard: Toggle dashboard which shows the date of the last found pattern.
Location: Location of the dashboard on the chart.
Size: Text size.
🔹 Calculation
Calculated Bars: Allows the usage of fewer bars for performance/speed improvement.
Multiple Naked LevelsPURPOSE OF THE INDICATOR
This indicator autogenerates and displays naked levels and gaps of multiple types collected into one simple and easy to use indicator.
VALUE PROPOSITION OF THE INDICATOR AND HOW IT IS ORIGINAL AND USEFUL
1) CONVENIENCE : The purpose of this indicator is to offer traders with one coherent and robust indicator providing useful, valuable, and often used levels - in one place.
2) CLUSTERS OF CONFLUENCES : With this indicator it is easy to identify levels and zones on the chart with multiple confluences increasing the likelihood of a potential reversal zone.
THE TYPES OF LEVELS AND GAPS INCLUDED IN THE INDICATOR
The types of levels include the following:
1) PIVOT levels (Daily/Weekly/Monthly) depicted in the chart as: dnPIV, wnPIV, mnPIV.
2) POC (Point of Control) levels (Daily/Weekly/Monthly) depicted in the chart as: dnPoC, wnPoC, mnPoC.
3) VAH/VAL STD 1 levels (Value Area High/Low with 1 std) (Daily/Weekly/Monthly) depicted in the chart as: dnVAH1/dnVAL1, wnVAH1/wnVAL1, mnVAH1/mnVAL1
4) VAH/VAL STD 2 levels (Value Area High/Low with 2 std) (Daily/Weekly/Monthly) depicted in the chart as: dnVAH2/dnVAL2, wnVAH2/wnVAL2, mnVAH1/mnVAL2
5) FAIR VALUE GAPS (Daily/Weekly/Monthly) depicted in the chart as: dnFVG, wnFVG, mnFVG.
6) CME GAPS (Daily) depicted in the chart as: dnCME.
7) EQUILIBRIUM levels (Daily/Weekly/Monthly) depicted in the chart as dnEQ, wnEQ, mnEQ.
HOW-TO ACTIVATE LEVEL TYPES AND TIMEFRAMES AND HOW-TO USE THE INDICATOR
You can simply choose which of the levels to be activated and displayed by clicking on the desired radio button in the settings menu.
You can locate the settings menu by clicking into the Object Tree window, left-click on the Multiple Naked Levels and select Settings.
You will then get a menu of different level types and timeframes. Click the checkboxes for the level types and timeframes that you want to display on the chart.
You can then go into the chart and check out which naked levels that have appeared. You can then use those levels as part of your technical analysis.
The levels displayed on the chart can serve as additional confluences or as part of your overall technical analysis and indicators.
In order to back-test the impact of the different naked levels you can also enable tapped levels to be depicted on the chart. Do this by toggling the 'Show tapped levels' checkbox.
Keep in mind however that Trading View can not shom more than 500 lines and text boxes so the indocator will not be able to give you the complete history back to the start for long duration assets.
In order to clean up the charts a little bit there are two additional settings that can be used in the Settings menu:
- Selecting the price range (%) from the current price to be included in the chart. The default is 25%. That means that all levels below or above 20% will not be displayed. You can set this level yourself from 0 up to 100%.
- Selecting the minimum gap size to include on the chart. The default is 1%. That means that all gaps/ranges below 1% in price difference will not be displayed on the chart. You can set the minimum gap size yourself.
BASIC DESCRIPTION OF THE INNER WORKINGS OF THE INDICTATOR
The way the indicator works is that it calculates and identifies all levels from the list of levels type and timeframes above. The indicator then adds this level to a list of untapped levels.
Then for each bar after, it checks if the level has been tapped. If the level has been tapped or a gap/range completely filled, this level is removed from the list so that the levels displayed in the end are only naked/untapped levels.
Below is a descrition of each of the level types and how it is caluclated (algorithm):
PIVOT
Daily, Weekly and Monthly levels in trading refer to significant price points that traders monitor within the context of a single trading day. These levels can provide insights into market behavior and help traders make informed decisions regarding entry and exit points.
Traders often use D/W/M levels to set entry and exit points for trades. For example, entering long positions near support (daily close) or selling near resistance (daily close).
Daily levels are used to set stop-loss orders. Placing stops just below the daily close for long positions or above the daily close for short positions can help manage risk.
The relationship between price movement and daily levels provides insights into market sentiment. For instance, if the price fails to break above the daily high, it may signify bearish sentiment, while a strong breakout can indicate bullish sentiment.
The way these levels are calculated in this indicator is based on finding pivots in the chart on D/W/M timeframe. The level is then set to previous D/W/M close = current D/W/M open.
In addition, when price is going up previous D/W/M open must be smaller than previous D/W/M close and current D/W/M close must be smaller than the current D/W/M open. When price is going down the opposite.
POINT OF CONTROL
The Point of Control (POC) is a key concept in volume profile analysis, which is commonly used in trading.
It represents the price level at which the highest volume of trading occurred during a specific period.
The POC is derived from the volume traded at various price levels over a defined time frame. In this indicator the timeframes are Daily, Weekly, and Montly.
It identifies the price level where the most trades took place, indicating strong interest and activity from traders at that price.
The POC often acts as a significant support or resistance level. If the price approaches the POC from above, it may act as a support level, while if approached from below, it can serve as a resistance level. Traders monitor the POC to gauge potential reversals or breakouts.
The way the POC is calculated in this indicator is by an approximation by analysing intrabars for the respective timeperiod (D/W/M), assigning the volume for each intrabar into the price-bins that the intrabar covers and finally identifying the bin with the highest aggregated volume.
The POC is the price in the middle of this bin.
The indicator uses a sample space for intrabars on the Daily timeframe of 15 minutes, 35 minutes for the Weekly timeframe, and 140 minutes for the Monthly timeframe.
The indicator has predefined the size of the bins to 0.2% of the price at the range low. That implies that the precision of the calulated POC og VAH/VAL is within 0.2%.
This reduction of precision is a tradeoff for performance and speed of the indicator.
This also implies that the bigger the difference from range high prices to range low prices the more bins the algorithm will iterate over. This is typically the case when calculating the monthly volume profile levels and especially high volatility assets such as alt coins.
Sometimes the number of iterations becomes too big for Trading View to handle. In these cases the bin size will be increased even more to reduce the number of iterations.
In such cases the bin size might increase by a factor of 2-3 decreasing the accuracy of the Volume Profile levels.
Anyway, since these Volume Profile levels are approximations and since precision is traded for performance the user should consider the Volume profile levels(POC, VAH, VAL) as zones rather than pin point accurate levels.
VALUE AREA HIGH/LOW STD1/STD2
The Value Area High (VAH) and Value Area Low (VAL) are important concepts in volume profile analysis, helping traders understand price levels where the majority of trading activity occurs for a given period.
The Value Area High/Low is the upper/lower boundary of the value area, representing the highest price level at which a certain percentage of the total trading volume occurred within a specified period.
The VAH/VAL indicates the price point above/below which the majority of trading activity is considered less valuable. It can serve as a potential resistance/support level, as prices above/below this level may experience selling/buying pressure from traders who view the price as overvalued/undervalued
In this indicator the timeframes are Daily, Weekly, and Monthly. This indicator provides two boundaries that can be selected in the menu.
The first boundary is 70% of the total volume (=1 standard deviation from mean). The second boundary is 95% of the total volume (=2 standard deviation from mean).
The way VAH/VAL is calculated is based on the same algorithm as for the POC.
However instead of identifying the bin with the highest volume, we start from range low and sum up the volume for each bin until the aggregated volume = 30%/70% for VAL1/VAH1 and aggregated volume = 5%/95% for VAL2/VAH2.
Then we simply set the VAL/VAH equal to the low of the respective bin.
FAIR VALUE GAPS
Fair Value Gaps (FVG) is a concept primarily used in technical analysis and price action trading, particularly within the context of futures and forex markets. They refer to areas on a price chart where there is a noticeable lack of trading activity, often highlighted by a significant price movement away from a previous level without trading occurring in between.
FVGs represent price levels where the market has moved significantly without any meaningful trading occurring. This can be seen as a "gap" on the price chart, where the price jumps from one level to another, often due to a rapid market reaction to news, events, or other factors.
These gaps typically appear when prices rise or fall quickly, creating a space on the chart where no transactions have taken place. For example, if a stock opens sharply higher and there are no trades at the prices in between the two levels, it creates a gap. The areas within these gaps can be areas of liquidity that the market may return to “fill” later on.
FVGs highlight inefficiencies in pricing and can indicate areas where the market may correct itself. When the market moves rapidly, it may leave behind price levels that traders eventually revisit to establish fair value.
Traders often watch for these gaps as potential reversal or continuation points. Many traders believe that price will eventually “fill” the gap, meaning it will return to those price levels, providing potential entry or exit points.
This indicator calculate FVGs on three different timeframes, Daily, Weekly and Montly.
In this indicator the FVGs are identified by looking for a three-candle pattern on a chart, signalling a discrete imbalance in order volume that prompts a quick price adjustment. These gaps reflect moments where the market sentiment strongly leans towards buying or selling yet lacks the opposite orders to maintain price stability.
The indicator sets the gap to the difference from the high of the first bar to the low of the third bar when price is moving up or from the low of the first bar to the high of the third bar when price is moving down.
CME GAPS (BTC only)
CME gaps refer to price discrepancies that can occur in charts for futures contracts traded on the Chicago Mercantile Exchange (CME). These gaps typically arise from the fact that many futures markets, including those on the CME, operate nearly 24 hours a day but may have significant price movements during periods when the market is closed.
CME gaps occur when there is a difference between the closing price of a futures contract on one trading day and the opening price on the following trading day. This difference can create a "gap" on the price chart.
Opening Gaps: These usually happen when the market opens significantly higher or lower than the previous day's close, often influenced by news, economic data releases, or other market events occurring during non-trading hours.
Gaps can result from reactions to major announcements or developments, such as earnings reports, geopolitical events, or changes in economic indicators, leading to rapid price movements.
The importance of CME Gaps in Trading is the potential for Filling Gaps: Many traders believe that prices often "fill" gaps, meaning that prices may return to the gap area to establish fair value.
This can create potential trading opportunities based on the expectation of gap filling. Gaps can act as significant support or resistance levels. Traders monitor these levels to identify potential reversal points in price action.
The way the gap is identified in this indicator is by checking if current open is higher than previous bar close when price is moving up or if current open is lower than previous day close when price is moving down.
EQUILIBRIUM
Equilibrium in finance and trading refers to a state where supply and demand in a market balance each other, resulting in stable prices. It is a key concept in various economic and trading contexts. Here’s a concise description:
Market Equilibrium occurs when the quantity of a good or service supplied equals the quantity demanded at a specific price level. At this point, there is no inherent pressure for the price to change, as buyers and sellers are in agreement.
Equilibrium Price is the price at which the market is in equilibrium. It reflects the point where the supply curve intersects the demand curve on a graph. At the equilibrium price, the market clears, meaning there are no surplus goods or shortages.
In this indicator the equilibrium level is calculated simply by finding the midpoint of the Daily, Weekly, and Montly candles respectively.
NOTES
1) Performance. The algorithms are quite resource intensive and the time it takes the indicator to calculate all the levels could be 5 seconds or more, depending on the number of bars in the chart and especially if Montly Volume Profile levels are selected (POC, VAH or VAL).
2) Levels displayed vs the selected chart timeframe. On a timeframe smaller than the daily TF - both Daily, Weekly, and Monthly levels will be displayed. On a timeframe bigger than the daily TF but smaller than the weekly TF - the Weekly and Monthly levels will be display but not the Daily levels. On a timeframe bigger than the weekly TF but smaller than the monthly TF - only the Monthly levels will be displayed. Not Daily and Weekly.
CREDITS
The core algorithm for calculating the POC levels is based on the indicator "Naked Intrabar POC" developed by rumpypumpydumpy (https:www.tradingview.com/u/rumpypumpydumpy/).
The "Naked intrabar POC" indicator calculates the POC on the current chart timeframe.
This indicator (Multiple Naked Levels) adds two new features:
1) It calculates the POC on three specific timeframes, the Daily, Weekly, and Monthly timeframes - not only the current chart timeframe.
2) It adds functionaly by calculating the VAL and VAH of the volume profile on the Daily, Weekly, Monthly timeframes .
Bollinger Bands Enhanced StrategyOverview
The common practice of using Bollinger bands is to use it for building mean reversion or squeeze momentum strategies. In the current script Bollinger Bands Enhanced Strategy we are trying to combine the strengths of both strategies types. It utilizes Bollinger Bands indicator to buy the local dip and activates trailing profit system after reaching the user given number of Average True Ranges (ATR). Also it uses 200 period EMA to filter trades only in the direction of a trend. Strategy can execute only long trades.
Unique Features
Trailing Profit System: Strategy uses user given number of ATR to activate trailing take profit. If price has already reached the trailing profit activation level, scrip will close long trade if price closes below Bollinger Bands middle line.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Major Trend Filter: Strategy utilizes 100 period EMA to take trades only in the direction of a trend.
Flexible Risk Management: Users can choose number of ATR as a stop loss (by default = 1.75) for trades. This is flexible approach because ATR is recalculated on every candle, therefore stop-loss readjusted to the current volatility.
Methodology
First of all, script checks if currently price is above the 200-period exponential moving average EMA. EMA is used to establish the current trend. Script will take long trades on if this filtering system showing us the uptrend. Then the strategy executes the long trade if candle’s low below the lower Bollinger band. To calculate the middle Bollinger line, we use the standard 20-period simple moving average (SMA), lower band is calculated by the substruction from middle line the standard deviation multiplied by user given value (by default = 2).
When long trade executed, script places stop-loss at the price level below the entry price by user defined number of ATR (by default = 1.75). This stop-loss level recalculates at every candle while trade is open according to the current candle ATR value. Also strategy set the trailing profit activation level at the price above the position average price by user given number of ATR (by default = 2.25). It is also recalculated every candle according to ATR value. When price hit this level script plotted the triangle with the label “Strong Uptrend” and start trail the price at the middle Bollinger line. It also started to be plotted as a green line.
When price close below this trailing level script closes the long trade and search for the next trade opportunity.
Risk Management
The strategy employs a combined and flexible approach to risk management:
It allows positions to ride the trend as long as the price continues to move favorably, aiming to capture significant price movements. It features a user-defined ATR stop loss parameter to mitigate risks based on individual risk tolerance. By default, this stop-loss is set to a 1.75*ATR drop from the entry point, but it can be adjusted according to the trader's preferences.
There is no fixed take profit, but strategy allows user to define user the ATR trailing profit activation parameter. By default, this stop-loss is set to a 2.25*ATR growth from the entry point, but it can be adjusted according to the trader's preferences.
Justification of Methodology
This strategy leverages Bollinger bangs indicator to open long trades in the local dips. If price reached the lower band there is a high probability of bounce. Here is an issue: during the strong downtrend price can constantly goes down without any significant correction. That’s why we decided to use 200-period EMA as a trend filter to increase the probability of opening long trades during major uptrend only.
Usually, Bollinger Bands indicator is using for mean reversion or breakout strategies. Both of them have the disadvantages. The mean reversion buys the dip, but closes on the return to some mean value. Therefore, it usually misses the major trend moves. The breakout strategies usually have the issue with too high buy price because to have the breakout confirmation price shall break some price level. Therefore, in such strategies traders need to set the large stop-loss, which decreases potential reward to risk ratio.
In this strategy we are trying to combine the best features of both types of strategies. Script utilizes ate ATR to setup the stop-loss and trailing profit activation levels. ATR takes into account the current volatility. Therefore, when we setup stop-loss with the user-given number of ATR we increase the probability to decrease the number of false stop outs. The trailing profit concept is trying to add the beat feature from breakout strategies and increase probability to stay in trade while uptrend is developing. When price hit the trailing profit activation level, script started to trail the price with middle line if Bollinger bands indicator. Only when candle closes below the middle line script closes the long trade.
Backtest Results
Operating window: Date range of backtests is 2020.10.01 - 2024.07.01. 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.
Initial capital: 10000 USDT
Percent of capital used in every trade: 30%
Maximum Single Position Loss: -9.78%
Maximum Single Profit: +25.62%
Net Profit: +6778.11 USDT (+67.78%)
Total Trades: 111 (48.65% win rate)
Profit Factor: 2.065
Maximum Accumulated Loss: 853.56 USDT (-6.60%)
Average Profit per Trade: 61.06 USDT (+1.62%)
Average Trade Duration: 76 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.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 4h BTC/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
Algo Market Structure (Nephew_Sam_)This indicator takes a different approach into reading market structure.
The key difference between this logic compared to the pivot logic is; we read highs and lows based on bullish and bearish candles. Ie:
Pivot method - highest/lowest point in previous and next X candles
Algo method - Bullish candle(s) followed by a bearish candle and vice versa
More explanation in each of the key feature below.
Here are all of the concepts and features included in the indicator:
Timeframe
- You can select the timeframe of the indicator (has to be higher or equal to the chart timeframe)
- Min option is the minimum timeframe to show the indicator. If you show daily structure on 1m chart, you can run into a timeout error so keep it close to the chart timeframe.
- Recommended timeframe for no bugs is the current chart timeframe.
Structure
The structure is calculated using a combination of candle patterns (ie. pivot top = Bullish x3-Bearish-Bullish) and marks out circle labels after a new HH or LL
Structure high = 1 or more consecutive bull candles followed by a bear candle
Structure low = 1 or more consecutive bear candles followed by a bull candle
Structure direction change = when the second previous H/L is taken out (TLQ)
ILQ - Inducement Liquidity concept
In a bearish example this is the most recent structure high.
TLQ
In a bearish example this is the second most recent structure high.
This is also what helps define our structure direction. If broken, the structure changes (bullish / bearish) and plots a bos line.
EPA - Efficient price action
When price returns back to previous structure point after bos. Similar to an ICT breaker.
Note: It might be a little, just a little buggy if you have set your indicator timeframe to higher than the chart timeframe.
Extremes Zones
The final zone to find a trade entry before a structural shift. These are wick of the TLQ candle. This is select the wick of the current timeframe candle even if indicator is set to higher timeframe.
MSU
Tiny arrow labels at the bottom of your chart. Plots the arrows when price is between an ILQ and TLQ
VTA
Valid trading range. This is when we get some sort of a structure pattern. Plots a box when price induces previous structure point and then breaks structure in the opposite direction. Here are the patterns:
Bull VTA - HH-LL-HH
Bear VTA - LL-HH-LL
Bull Strict VTA - LL-HH-LL-HH
Bear Strict VTA - HH-LL-HH-LL
Bar colors
Changes the bar color based on the structure to all green/red.
Note: for this to work, you will have to right click on the indicator, then under visual order select 'bring to front'
Table
This table plots the structure stats/data
1. If structure is bullish / bearish
2. If price is efficient or not
3. If there is an MSU
4. If price is inside a VTA
Disclaimer: This indicator is fully written from scratch by me, the idea behind the concepts come from AlgoHub material on Youtube. Do NOT use this code for reselling purposes and if anything is created using any part of this code, the source code should be public.
Moving Average Crossover Swing StrategyMoving Average Crossover Swing Strategy
**Overview:**
The basic concept of this strategy is to generate a signal when a faster/shorter length moving average crosses over (for Longs) or crosses under (for Shorts) a medium/longer length moving average. All of which are customizable. This strategy can work on any timeframe, however the daily is the timeframe used for the default settings and screenshots, as it was designed to be a multi-day swing strategy. Once a signal has been confirmed with a candle close, based on user options, the strategy will enter the trade on the open of the next candle.
The crossover strategy is nothing new to trading, but what can make this strategy unique and helpful, is the addition of further confirmation points, ATR based stop loss and take profit targets, optional early exit criteria, customizable to your needs and style, and just about everything visual can be toggled on/off. This strategy is based on a Trend (MA) indicator and a Momentum (MACD) indicator. While a Volume-based indicator is not shown here, one could consider using their favorite from that category to further compliment the signal idea.
It should be noted that depending on the time frame, direction(s) chosen, the signal options, confirmation options, and exit options selected, that a ticker may not produce more than 100 trades on the back test. Depending on your style and frequency, one could consider adjusting options and/or testing multiple tickers. It should also be noted that this strategy simply tests the underlying stock prices, not options contracts. And of course, testing this strategy against historical data does not assume that the same results will occur in future price action.
Shoutout given to Ripster's Clouds Indicator as pieces of that code were taken and modified to create both the Cloud visualization effects, and the Moving Average Pair Plots that are implemented in this strategy.
BASIC DEFAULTS
All can be changed as normal
Initial capital = 10,000
Order Sizing = 25% of equity (use the "Inputs" tab to modify this)
Pyramiding = 0
Commission = 0.65 USD per order
Price Verification = 1 tick
Slippage = 1 tick
RISK MANAGMENT
You will notice two different percentage options and ATR multipliers. This strategy will adjust position sizing by not exceeding either one of those % values based on the ATR (Average True Range) of the symbol and the multipliers selected, should the stock hit the stop loss price.
For Example, lets assume these values are true:
Account size = $10,000,
Max Risk = 1% of account size
Max Position Size = 25% of the account size
Stock Price = 23.45
ATR = 3.5
ATR Stop Loss Multiplier = 1.4
Then the formulas would be:
ACCT_SIZE * MaxRisk_% = 10000 * .01 = $100 (MaxCashRisk)
-----
MaxCashRisk / (ATR * ATR_SL_MULTIPLIER) = 100 / (3.5 * 1.4) = 20.4 Shares based on Max Cash Risk
-----
(ACCT_SIZE * MaxEquity_%) / STOCK_PRICE = (10000 * .25) / 23.45 = 106.61 Shares based on Max Equity Allocation
The minimum value of each of those options is then used, which in this case would be to purchase 20 shares so as not to exceed the max dollar risk should the stock reach the stop loss target. Likewise, if the ATR were to be much lower, say 0.48 cents, and all else the same, then the strategy would purchase the 106 shares based on Max Equity Allocation because the Max Cash Risk would require 149.25 shares.
MOVING AVERAGE OPTIONS
Select between and change the length & type of up to 5 pairs (10 total) of moving averages
The "Show Cloud-x" option will display a fill color between the "a" and "b" pairs
All moving averages lines can be toggled on/off in the "Style" tab, as well as adjusting their colors.
Visualization features do not affect calculations, meaning you could have all or nothing on the chart and the strategy will still produce results
SIGNAL CHOICES
Choose the fast/shorter length MA and the medium/longer length MA to determine the entry signal
CONFIRMATION OPTIONS
Both of these have customizable values and can be toggled on/off
A candle close over a slower/much longer length moving average
An additional cross-over (cross-under for Shorts) on the MACD indicator using default MACD values. While the MACD indicator is not necessary to have on the chart, it can help to add that for visualization. The calculations will perform whether the indicator is on the chart or not.
EARLY EXIT CRITERIA
Both can be toggled on/off with customizable values
MA Cross Exit will exit the trade early if the select moving averages cross-under (for longs) or cross-over (for shorts), indicating a potential reversal.
Max Bars in Trades will act as a last-resort exit by simply calculating the amount of full bars the trade has been open, and exiting on the opening of the next bar. For example: the default value is 8 bars, so after 8 full bars in the trade, if no other exit has been triggered (Stop Loss, Take Profit, or MA Cross(if enabled)), then the trade will exit at the opening of the 9th bar.
Finally, there is a table displaying the amount of trades taken for each side, and the amount & percent of both early exits. This table can be turned off in the "Style" tab
ADDITIONAL PLOTS
MACD (Moving Average Convergence/Divergence):
- The MACD is an optional confirmation indicator for this strategy.
- Plotting the indicator is not necessary for the strategy to work, but it can be helpful to visually see the status and position of the MACD if this feature is enabled in the strategy
- This helps to identify if there is also momentum behind the entry signal
Smart Money Setup 06 [TradingFinder] Liquidity Sweeps + OB Swing🔵 Introduction
Smart Money, managed by large investors, injects significant capital into financial markets by entering real capital markets.
Capital entering the market by this group of individuals is called smart money. Traders can profit from financial markets by following such individuals.
Therefore, smart money can be considered one of the effective methods for analyzing financial markets.
Sometimes, before a market movement, fluctuation movements that create price movement cause many traders' "Stop Loss" to be triggered. These movements are created in various patterns.
One of these patterns is similar to an "Expanding Triangle", which touches the stop loss of individuals who have placed their stop loss in the cash area in the form of 5 consecutive openings.
To better understand this setup, pay attention to the images below.
Bullish Setup Details :
Bearish Setup Details :
🔵 How to Use
After adding the indicator to the chart, wait for trading opportunities to appear. By changing the "Time Frame" and "Pivot Period", you can see different trading positions.
In general, the smaller the "Time Frame" and "Pivot Period", the more likely trading opportunities will appear.
Bullish Setup Details on Chart :
Bearish Setup Details on Chart :
🔵 Settings
You have access to "Pivot Period", "Order Block Refine", and "Refine Mode" through settings.
By changing the "Pivot Period", you can change the range of zigzag that identifies the setup.
Through "Order Block Refine", you can specify whether you want to refine the width of the order blocks or not. It is set to "On" by default.
Through "Refine Mode", you can specify how to improve order blocks.
If you are "risk-averse", you should set it to "Defensive" mode because in this mode, the width of the order blocks decreases, the number of your trades decreases, and the "reward-to-risk ratio "increases.
If you are on the opposite side and are "risk-taker", you can set it to "Aggressive" mode. In this mode, the width of the order blocks increases, and the likelihood of losing positions decreases.
Relative Average Extrapolation [ChartPrime]Relative Average Extrapolation (ChartPrime) is a new take on session averages, like the famous vwap . This indicator leverages patterns in the market by leveraging average-at-time to get a footprint of the average market conditions for the current time. This allows for a great estimate of market conditions throughout the day allowing for predictive forecasting. If we know what the market conditions are at a given time of day we can use this information to make assumptions about future market conditions. This is what allows us to estimate an entire session with fair accuracy. This indicator works on any intra-day time frame and will not work on time frames less than a minute, or time frames that are a day or greater in length. A unique aspect of this indicator is that it allows for analysis of pre and post market sessions independently from regular hours. This results in a cleaner and more usable vwap for each individual session. One drawback of this is that the indicator utilizes an average for the length of a session. Because of this, some after hour sessions will only have a partial estimation. The average and deviation bands will work past the point where it has been extrapolated to in this instance however. On low time frames due to the limited number of data points, the indicator can appear noisy.
Generally crypto doesn't have a consistent footprint making this indicator less suitable in crypto markets. Because of this we have implemented other weighting schemes to allow for more flexibility in the number of use cases for this indicator. Besides volume weighting we have also included time, volatility, and linear (none) weighting. Using any one of these weighting schemes will transform the vwap into a wma, volatility adjusted ma, or a simple moving average. All of the style are still session period and will become longer as the session progresses.
Relative Average Extrapolation (ChartPrime) works by storing data for each time step throughout the day by utilizing a custom indexing system. It takes the a key , ie hour/minute, and transforms it into an array index to stor the current data point in its unique array. From there we can take the current time of day and advance it by one step to retrieve the data point for the next bar index. This allows us to utilize the footprint the extrapolate into the future. We use the relative rate of change for the average, the relative deviation, and relative price position to extrapolate from the current point to the end of the session. This process is fast and effective and possibly easier to use than the built in map feature.
If you have used vwap before you should be familiar with the general settings for this indicator. We have made a point to make it as intuitive for anyone who is already used to using the standard vwap. You can pick the source for the average and adjust/enable the deviation bands multipliers in the settings group. The average period is what determines the number of days to use for the average-at-time. When it is set to 0 it will use all available data. Under "Extrapolation" you will find the settings for the estimation. "Direction Sensitivity" adjusts how sensitive the indicator is to the direction of the vwap. A higher number will allow it to change directions faster, where a lower number will make it more stable throughout the session. Under the "Style" section you will find all of the color and style adjustments to customize the appearance of this indicator.
Relative Average Extrapolation (ChartPrime) is an advanced and customizable session average indicator with the ability to estimate the direction and volatility of intra-day sessions. We hope you will find this script fascinating and useful in your trading and decision making. With its unique take on session weighting and forecasting, we believe it will be a secret weapon for traders for years to come.
Enjoy
HTF FVG and Wick Fill trackingImbalances in the charts are some of the clearest and most traded price areas. Two of the best and most used are fair value gaps FVGs and large candle wicks. In both of these price appears to move in such a way that most are left behind having 'missed' the move. But in reality price will often come back to these price points to re-balance and absorb the liquidity that was left behind.
This indicator takes these areas and makes viewing and tracking them clearer than ever. It does this, by first allowing the user to overlay a higher timeframe candle on the current chart. This in itself provides an in depth look at a higher timeframe candle both as it forms and in its final form.
Next the indicator identifies either the FVG or large wicks, on the chosen higher timeframe, all while the chart remains on a lower timeframe. As seen here the fair value gaps are clearly highlighted, taken from a 4 hour timeframe, while the actual chart is on 15 minutes. This allows the user even greater accuracy in identifying their key trading areas.
Utilizing the indicators unique feature, these areas can optionally be extended forward to the current timeframe and 'filled' in realtime. Areas that are filled to the users defined level, will be removed from the chart.
With supplementary settings for how much history to show, how large of a wick should be highlighted and complete control over the colour scheme, users will be able to track and understand the filling of imbalances like never before.
TTrades Daily Bias [TFO]Inspired by @TTrades_edu video on daily bias, this indicator aims to develop a higher timeframe bias and collect data on its success rate. While a handful of concepts were introduced in said video, this indicator focuses on one specific method that utilizes previous highs and lows. The following description will outline how the indicator works using the daily timeframe as an example, but the weekly timeframe is also an included option that functions in the exact same manner.
On the daily timeframe, there are a handful of possible scenarios that we consider: if price closes above its previous day high (PDH), the following day's bias will target PDH; if price trades above its PDH but closes back below it, the following day's bias will target its previous day low (PDL).
Similarly, if price closes below its PDL, the following day's bias will target PDL. If price trades below its PDL but closes back above it, the following day's bias will target PDH.
If price trades as an inside bar that doesn't take either PDH or PDL, it will refer to the previous candle for bias. If the previous day closed above its open, it will target PDH and vice versa. If price trades as an outside bar that takes both PDH and PDL, but closes inside that range, no bias is assigned.
With a rigid framework in place, we can apply it to the charts and observe the results.
As shown above, each new day starts by drawing out the PDH and PDL levels. They start out as blue and turn red once traded through (these are the default colors which can be changed in the indicator's settings). The triangles you see are plotted to indicate the time at which PDH or PDL was traded through. This color scheme is also applied to the table in the top right; once a bias is determined, that cell's color starts out as blue and turns red once the level is traded through.
The table indicates the success rate of price hitting the levels provided by each period's bias, followed by the success rate of price closing through said levels after reaching them, as well as the sample size of data collected for each scenario.
In the above crude oil futures (CL1!) 30m chart, we can glean a lot of information from the table in the top right. First we may note that the "PDH" cell is red, which indicates that the current day's bias was targeting PDH and it has already traded through that level. We might also note that the "PWH" cell is blue, which indicates that the weekly bias is targeting the previous week high (PWH) but price has yet to reach that level.
As an example of how to read the table's data, we can look at the "PDH" row of the crude oil chart above. The sample size here indicates that there were 279 instances where the daily bias was assigned as PDH. From this sample size, 76.7% of instances did go on to trade through PDH, and only 53.7% of those instances actually went on to close through PDH after hitting that level.
Of course, greater sample sizes and therefore greater statistical significance may be derived from higher timeframe charts that may go further back in time. The amount of data you can observe may also depend on your TradingView plan.
If we don't want to see the labels describing why bias is assigned a certain way, we can simply turn off the "Show Bias Reasoning" option. Additionally, if we want to see a visual of what the daily and weekly bias currently is, we can plot that along the top and bottom of the chart, as shown above. Here I have daily bias plotted at the top and weekly bias at the bottom, where the default colors of green and red indicate that the bias logic is expecting price to draw towards the given timeframe's previous high or low, respectively.
For a compact table view that doesn't take up much chart space, simply deselect the "Show Statistics" option. This will only show the color-coded bias column for a quick view of what levels are being anticipated (more user-friendly for mobile and other smaller screens).
Alerts can be configured to indicate the bias for a new period, and/or when price hits its previous highs and lows. Simply enable the alerts you want from the indicator's settings and create a new alert with this indicator as the condition. There will be options to use "Any alert() function call" which will alert whatever is selected from the settings, or you can use more specific alerts for bullish/bearish bias, whether price hit PDH/PDL, etc.
Lastly, while the goal of this indicator was to evaluate the effectiveness of a very specific bias strategy, please understand that past performance does not guarantee future results.
ICT Concept [TradingFinder] Order Block | FVG | Liquidity Sweeps🔵 Introduction
The "ICT" style is one of the subsets of "Price Action" technical analysis. ICT is a method created by "Michael Huddleston", a professional forex trader and experienced mentor. The acronym ICT stands for "Inner Circle Trader".
The main objective of the ICT trading strategy is to combine "Price Action" and the concept of "Smart Money" to identify optimal entry points into trades. However, finding suitable entry points is not the only strength of this approach. With the ICT style, traders can better understand price behavior and adapt their trading approach to market structure accordingly.
Numerous concepts are discussed in this style, but the key practical concepts for trading in financial markets include "Order Block," "Liquidity," and "FVG".
🔵 How to Use
🟣Order Block
Order blocks are a specific type of "Supply and Demand" zones formed when a series of orders are placed in a block. These orders could be created by banks or other major players. Banks typically execute large orders in blocks during their trading sessions. If they were to enter the market directly with a small quantity, significant price movements would occur before the orders are fully executed, resulting in less profit. To avoid this, they divide their orders into smaller, manageable positions. Traders should look for "buy" opportunities in "demand order blocks" areas and "sell" opportunities in "supply order blocks".
🟣Liquidity
These levels are where traders aim to exit their trades. "Market Makers" or smart money usually collects or distributes their trading positions near levels where many retail traders have placed their "Stop Loss" orders. When the liquidity resulting from these losses is collected, the price often reverses direction.
A "Stop Hunt" is a move designed to neutralize liquidity generated by triggered stop losses. Banks often use significant news events to trigger stop hunts and acquire the liquidity released in the market. If, for example, they intend to execute heavy buy orders, they encourage others to sell through stop hunts.
As a result, if there is liquidity in the market before reaching the order block region, the credibility of that order block is higher. Conversely, if liquidity is near the order block, meaning the price reaches the order block before reaching the liquidity area, the credibility of that order block is lower.
🟣FVG (Fair Value Gap)
To identify the "Fair Value Gap" on the chart, one must analyze candle by candle. Focus on candles with large bodies, examining one candle and the one before it. The candles before and after this central candle should have long shadows, and their bodies should not overlap with the body of the central candle. The distance between the shadows of the first and third candles is called the FVG range.
These zone function in two ways :
•Supply and Demand zone: In this case, the price reacts to these zone, and its trend reverses.
•Liquidity zone: In this scenario, the price "fills" the zone and then reaches the order block.
Important Note: In most cases, FVG zone with very small width act as supply and demand zone, while zone with a significant width act as liquidity zone, absorbing the price.
🔵 Setting
🟣Order Block
Refine Order Block : When the option for refining order blocks is Off, the supply and demand zones encompass the entire length of the order block (from Low to High) in their standard state and remain unaltered. On the option for refining order blocks triggers the improvement of supply and demand zones using the error correction algorithm.
Refine Type : The enhancement of order blocks via the error correction algorithm can be executed through two methods: Defensive and Aggressive. In the Aggressive approach, the widest possible range is taken into account for order blocks.
Show High Levels : If major high levels are to be displayed, set the option for showing high level to Yes.
Show Low Levels : If major low levels are to be displayed, set the option for showing low level to Yes.
Show Last Support : If showing the last support is desired, set the option for showing last support to Yes.
Show Last Resistance : If showing the last resistance is desired, set the option for showing last resistance to Yes.
🟣 FVG
FVG Filter : When FVG filtering is activated, the number of FVG areas undergoes filtration based on the specified algorithm.
FVG Filter Types :
1. Very Aggressive : Apart from the initial condition, an additional condition is introduced. For an upward FVG, the maximum price of the last candle should exceed the maximum price of the middle candle. Similarly, for a downward FVG, the minimum price of the last candle should be lower than the minimum price of the middle candle. This mode eliminates a minimal number of FVGs.
2. Aggressive : In addition to the conditions of the Very Aggressive mode, this mode considers the size of the middle candle; it should not be small. Consequently, a larger number of FVGs are eliminated in this mode.
3. Defensive : Alongside the conditions of the Very Aggressive mode, this mode takes into account the size of the middle candle, which should be relatively large with the majority of it comprising the body. Furthermore, to identify upward FVGs, the second and third candles must be positive, whereas for downward FVGs, the second and third candles must be negative. This mode filters out a considerable number of FVGs, retaining only those of suitable quality.
4. Very Defensive : In addition to the conditions of the Defensive mode, the first and third candles should not be very small-bodied doji candles. This mode filters out the majority of FVGs, leaving only the highest quality ones. Show Demand FVG: Enables the display of demand-related boxes, which can be toggled between off and on. Show Supply FVG: Enables the display of supply-related boxes along the path, which can also be toggled between off and on.
🟣 Liquidity
Statics Liquidity Line Sensitivity : A value ranging from 0 to 0.4. Increasing this value reduces the sensitivity of the "Statics Liquidity Line Detection" function and increases the number of identified lines. The default value is 0.3.
Dynamics Liquidity Line Sensitivity : A value ranging from 0.4 to 1.95. Increasing this value enhances the sensitivity of the "Dynamics Liquidity Line Detection" function and decreases the number of identified lines. The default value is 1.
Statics Period Pivot : Default value is set to 8. By adjusting this value, you can specify the period for static liquidity line pivots.
Dynamics Period Pivot : Default value is set to 3. By adjusting this value, you can specify the period for dynamic liquidity line pivots.
You can activate or deactivate liquidity lines as necessary using the buttons labeled "Show Statics High Liquidity Line," "Show Statics Low Liquidity Line," "Show Dynamics High Liquidity Line," and "Show Dynamics Low Liquidity Line".
Quan Channel - Quan DaoI tried several channels, like the supertrend, ATR, Donchian or Bollingers, but they do not seem to fit my needs.
So I created a new channel to PREDICT the next impulse move of a price.
The current value of the top or bottom of the channel is based on 2 previous candles (not the candle itself), and it takes into account:
- The Direction of the previous candles (red or green) and
- The Width of their bodies
In my channel, the top or bottom lines will cover the price movement most of the time. But in some cases, when the price is on a big move, it will go out of the channel. And this is the time we need to consider a buy/sell (or take some profit) as well (not necessarily 100% of the time, though).
Personally, I like to use another oscillator in combination with this channel to predict whether it will reverse after the breakouts or continue to make another peak. If you are a DCA or long-term investor, I guess it would be safe to buy at the blue signals (out of bottom) and take some profits at the orange signals (out of top).
I also added an alert when the price breaks out of the channel for easier tracking.
Trend Channels (MTF) | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Trend Channels (MTF) indicator! Latest trends play an important role for traders and sometimes it can be hard to spot trends in other timeframes. This indicator can plot latest trend channels across different timeframes, so you can spot trends and their channels easier. More info about the process in the "How Does It Work" section.
Features of the new Trend Channels (MTF) indicator :
Plot Trend Channels Across Up To 3 Different Timeframes
Broad Customizability Of Trend Detection
Variety Of Trend Invalidation Options
High Visual Customizability
🚩UNIQUENESS
While the detection of trend channels is a common concept among traders, trend channels across different timeframes can be as crucial as the ones in the current timeframe. This indicator can find them from up to 3 different timeframes. While the general settings will perform well enough most of the time, the indicator also provides fine-tuning options for trend detection and trend invalidation for more experienced traders.
📌 HOW DOES IT WORK ?
Trend channels occur when the price of an asset starts making a strong movement in a bullish or a bearish direction. This indicator detects trend channels using the Simple Moving Average (SMA). When the slope of the SMA line exceeds the user-defined size, a trend channel will occur.
To understand how individual settings work, you can check the "⚙️SETTINGS" section.
⚙️SETTINGS
1. General Configuration
SMA Length -> Determines the length used in the SMA function. Higher values mean that an average of a longer timespan will be taken into account when spotting trends.
Slope Length -> Used while finding the slope of the trend channel. Check this example for slope length :
ATR Size -> This setting is taken into calculation while checking if a trend channel is worth plotting. The higher this setting is, the higher the slope of the trend channel must be to get rendered. You can take a look at the chart provided above for a visual explanation.
Channel Expander -> When a trend channel occurs, the top and the bottom of the channel are initally determined by the latest highest highs / lowest lows. This setting expands the channel vertically by X times Average True Range (ATR). Check this example :
Trend Invalidation -> The trend channel gets invalidated when the bar closes / wicks above the top of the channel, or below the bottom of the channel. With this setting, you can switch the behaviour between bar close / bar wick.
Avoid False Invalidation -> This setting makes it harder for trend channels to get invalidated to prevent false invalidations.
Retries : The trend channel will have 5 chances for invalidation. First 4 invalidations will not invalidate the channel. The trend channel will only invalidate once the 5th invalidation occur.
Volume : The bar that invalidates the trend channel must have a volume higher than 1.5x the average bar volume of the current chart. Otherwise the trend channel will not be invalidated.
None : The trend channel will invalidate at the first invalidation.
