Pattern Probability with EMA FilterThe provided code is a custom indicator that identifies specific price patterns on a chart and uses a 14-period Exponential Moving Average (EMA) as a filter to display only certain patterns based on the EMA trend direction. These code identifies patterns display them as upward and downward arrows indicates potential price corrections and short term trend reversals in the direction of the arrow. Use with indicators such as RSI that inform overbought and oversold condition to add reliability and confluence.
Code Explanation:
The code first calculates three values 'a', 'b', and 'c' based on the difference between the current high, low, and close prices, respectively, and their respective previous moving average values.
Binary values are then assigned to 'a', 'b', and 'c', where each value is set to 1 if it's greater than 0, and 0 otherwise.
The 'pattern_type' is determined based on the binary values of 'a', 'b', and 'c', combining them into a single number (ranging from 0 to 7) to represent different price patterns.
The code calculates a 14-period Exponential Moving Average (EMA) of the closing price.
It determines the EMA trend direction by comparing the current EMA value with the previous EMA value, setting 'ema_going_up' to true if the EMA is going up and 'ema_going_down' to true if the EMA is going down.
The indicator then plots arrows on the chart for specific pattern_type values while considering the EMA trend direction as a filter. It displays different colored arrows for each pattern_type.
The 14-period EMA is also plotted on the chart, with the color changing to green when the EMA is going up and red when the EMA is going down.
Concept:
pattern_type = 0: H- L- C- (Downward trend continuation) - Indicates a continuation of the downward trend, suggesting further losses ahead.
pattern_type = 1: H- L- C+ (Likely trend change: Downwards to upwards) - Implies the upward trend or price movement change.
pattern_type = 2: H- L+ C- (Likely trend change: Upwards to downwards) - Suggests a potential reversal from an uptrend to a downtrend, but further confirmation is needed.
pattern_type = 3: H- L+ C+ (Trend uncertainty: Potential reversal) - Indicates uncertainty in the trend, potential for a reversal, but further price action confirmation is required.
pattern_type = 4: H+ L- C- (Downward trend continuation with lower volatility) - Suggests the downward trend may continue, but with reduced price swings or lower volatility.
pattern_type = 5: H+ L- C+ (Likely trend change: Downwards to upwards) - Implies a potential reversal from a downtrend to an uptrend, with buying interest increasing.
(pattern_type = 6: H+ L+ C- (Likely trend change: Upwards to downwards) - Suggests a potential reversal from an uptrend to a downtrend, with selling pressure increasing.
pattern_type = 7: H+ L+ C+ (Upward trend continuation) - Indicates a continuation of the upward trend, suggesting further gains ahead.
In the US market, when analyzing a 15-minute chart, we observe the following proportions of the different pattern_type occurrences: The code will plot the low frequency patterns (P1 - P6)
P0 (H- L- C-): 37.60%
P1 (H- L- C+): 3.60%
P2 (H- L+ C-): 3.10%
P3 (H- L+ C+): 3.40%
P4 (H+ L- C-): 2.90%
P5 (H+ L- C+): 2.70%
P6 (H+ L+ C-): 3.50%
P7 (H+ L+ C+): 43.50%
When analyzing higher time frames, such as daily or weekly charts, the occurrence of these patterns is expected to be even lower, but they may carry more significant implications due to their rarity and potential impact on longer-term trends.
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DCA Liquidation Calculation [ChartPrime]The DCA Liquidation Calculator is a powerful table indicator designed for both manual and bot-assisted traders who practice Dollar Cost Averaging (DCA). Its primary objective is to help traders avoid getting liquidated and make informed decisions when managing their positions. This comprehensive table indicator provides essential information to DCA traders, enabling them to plan their trades effectively and mitigate potential risks of liquidation.
Key Features:
Liquidation Price Awareness: The DCA Liquidation Calculator calculates and displays the liquidation price for each trade within your position. This critical information empowers traders to set appropriate stop-loss levels and avoid being liquidated in adverse market conditions, especially in leveraged trading scenarios.
DCA Recommendations: Whether you are executing DCA manually or using a trading bot, the DCA Liquidation Calculator offers valuable guidance. It suggests optimal entry prices and provides insights into the percentage deviation from the current market price, helping traders make well-timed and well-informed DCA decisions.
Position Sizing: Proper position sizing is essential for risk management. The DCA Liquidation Calculator helps traders determine the percentage of capital to allocate to each trade based on the provided insights. By using the recommended position sizing, traders can protect their capital and potentially maximize profits.
Profit and Loss Visualization: Gain real-time visibility into your Profit and Loss (PnL) with the DCA Liquidation Calculator. This feature allows you to monitor your trades' performance, enabling you to adapt your strategies as needed and make data-driven decisions.
Margin Call Indicators: Anticipating potential margin calls is crucial for maintaining a healthy trading account. The DCA Liquidation Calculator's smart analysis helps you identify and manage potential margin call situations, reducing the risk of account liquidation.
Capital Requirements: Before entering a trade, it's vital to know the required capital. The DCA Liquidation Calculator provides you with this information, ensuring you are adequately prepared to execute your trades without overextending your resources.
Maximum Trade Limit: Considering your available capital, the DCA Liquidation Calculator helps you determine the maximum number of trades you can enter. This feature ensures you maintain a disciplined and sustainable trading approach aligned with your financial capabilities.
Color-Coded Risk Indicators:
Green Liquidation Price Cell: Indicates that the position is considered safe from liquidation at the given parameters.
Yellow Liquidation Price Cell: Warns traders of potential liquidation risk. Exercise caution and monitor the trade closely to avoid undesirable outcomes.
Purple Liquidation Price Cell: Shows the liquidation price, but it does not necessarily indicate an imminent liquidation. Use this information to make prudent risk management decisions.
Red Row: Signals that the trade cannot be executed due to insufficient capital. Consider alternative strategies or ensure adequate capitalization before proceeding.
Settings explained:
In conclusion, the DCA Liquidation Calculator equips traders with essential tools to make well-calculated decisions, minimize liquidation risks, and optimize their Dollar Cost Averaging strategy. By offering comprehensive insights into your trading position, this indicator empowers you to navigate the markets with confidence and increase your potential for successful and sustainable trading.
RibboNN Machine Learning [ChartPrime]The RibboNN ML indicator is a powerful tool designed to predict the direction of the market and display it through a ribbon-like visual representation, with colors changing based on the prediction outcome from a conditional class. The primary focus of this indicator is to assist traders in trend following trading strategies.
The RibboNN ML in action
Prediction Process:
Conditional Class: The indicator's predictive model relies on a conditional class, which combines information from both longcon (long condition) and short condition. These conditions are determined using specific rules and criteria, taking into account various market factors and indicators.
Direction Prediction: The conditional class provides the basis for predicting the direction of the market move. When the prediction value is greater than 0, it indicates an upward trend, while a value less than 0 suggests a downward trend.
Nearest Neighbor (NN): To attempt to enhance the accuracy of predictions, the RibboNN ML indicator incorporates a Nearest Neighbor algorithm. This algorithm analyzes historical data from the Ribbon ML's predictive model (RMF) and identifies patterns that closely resemble the current conditional prediction class, thereby offering more robust trend forecasts.
Ribbon Visualization:
The Ribbon ML indicator visually represents its predictions through a ribbon-like display. The ribbon changes colors based on the direction predicted by the conditional class. An upward trend is represented by a green color, while a downward trend is depicted by a red color, allowing traders to quickly identify potential market directions.
The introduction of the Nearest Neighbor algorithm provides the Ribbon ML indicator with unique and adaptive behaviors. By dynamically analyzing historical patterns and incorporating them into predictions, the indicator can adapt to changing market conditions and offer more reliable signals for trend following trading strategies.
Manipulation of the NN Settings:
Smaller Value of Neighbours Count:
When the value of "Neighbours Count" is small, the algorithm considers only a few nearest neighbors for making predictions.
A smaller value of "Neighbours Count" leads to more flexible decision boundaries, which can result in a more granular and sensitive model.
However, using a very small value might lead to overfitting, especially if the training data contains noise or outliers.
Larger Value of "Neighbours Count":
When the value of "Neighbours Count" is large, the algorithm considers a larger number of nearest neighbors for making predictions.
A larger value of "Neighbours Count" leads to smoother decision boundaries and helps capture the global patterns in the data.
However, setting a very large value might result in a loss of local patterns and make the model less sensitive to changes in the data.
Trend Channels With Liquidity Breaks [ChartPrime]Trend Channels
This simple trading indicator is designed to quickly identify and visualize support and resistance channels in any market. The primary purpose of the Trend Channels with Liquidity Breaks indicator is to recognize and visualize the dominant trend in a more intuitive and user-friendly manner.
Main Features
Automatically identifies and plots channels based on pivot highs and lows
Option to extend the channel lines
Display breaks of the channels where liquidity is deemed high
Inclusion of volume data within the channel bands (optional)
Market-friendly and customizable colors and settings for easy visual identification
Settings
Length: Adjust the length and lookback of the channels
Show Last Channel: Only shows the last channel
Volume BG: Shade the zones according to the volume detected
How to Interpret
Trend Channels with Liquidity Breaks indicator uses a combination of pivot highs and pivot lows to create support and resistance zones, helping traders to identify potential breakouts, reversals or continuations of a trend.
These support and resistance zones are visualized as upper and lower channel lines, with a dashed center line representing the midpoint of the channel. The indicator also allows you to see the volume data within the channel bands if you choose to enable this functionality. High volume zones can potentially signal strong buying or selling pressure, which may lead to potential breakouts or trend confirmations.
To make the channels more market-friendly and visually appealing, Trend Channels indicator also offers customizable colors for upper and lower lines, as well as the possibility to extend the line lengths for further analysis.
The indicator displays breaks of key levels in the market with higher volume.
Moving Average Trend Sniper [ChartPrime]Today we introducing the Moving Average Trend Sniper (MATS), a unique and powerful multi faceted tool. This moving average is designed to adapt to the ever-changing market conditions. MATS provides the ideal solution for traders looking to capitalize on market trends while accurately identifying support and resistance levels.
Why MATS?
MATS was developed with the trader in mind, focusing on the key factors crucial for a successful trading strategy - trend following, support, and resistance. Its unique moving average calculation not only accounts for market volatility and momentum but also provides a stable yet adaptable foundation for your trading decisions.
MATS employs a range of mathematical techniques to provide a precise and adaptive moving average, offering traders a more effective tool for analyzing market trends and identifying support and resistance levels. One of the primary distinctions of MATS is its use of delta, the change in market conditions, to update the moving average based on the trend's strength. This delta-based updating allows the moving average to adapt to market fluctuations and helps traders make more informed decisions when entering or exiting positions. MATS also focuses on the highs in a downtrend and the lows in an uptrend to provide more reliable support and resistance. By taking these crucial market points into consideration, the moving average delivers a comprehensive and accurate insight into the market's behavior and allows traders to make more precise predictions.
MATS leverages trigonometry to determine the trend angle for the moving average. By calculating this angle, MATS can efficiently pick the correct source (either the high or the low) to provide the best support and resistance analysis. This innovative use of trigonometry ensures that the moving average is better suited to the current market conditions and provides traders with a dynamic yet stable tool to support their trading decisions.
Settings:
Length: The length input for MATS plays a crucial role in determining how responsive the moving average will be to changes in market conditions. A shorter length setting results in a more reactive moving average that closely follows price movements, whereas a longer length setting generates a smoother, less volatile average. By adjusting the length setting, traders can fine-tune the sensitivity of MATS to align with their specific trading strategies and needs.
Glow: MATS offers a customizable and visually engaging display that helps traders effectively identify market trends. The "glow" effect surrounding support and resistance levels, available as an optional feature, enables users to assess these crucial areas more easily.
Example use cases:
In the screenshot below you can see the MATS acting as both a classical support and resistance while the glow and coloring is helped to provide a more classical trend following visualization to a trader. This duel functionality can help in re-entering during market retracements.
Quick Shot[ChartPrime]This indicator plots green and red dots when the trend changes based on a moving average slope. The curved line aims to exponentially increase the slope of the moving average based on the slope at the time of the dots origination as the bars progress. Once the curved line makes contact with the price action, an x shape will be plotted to signify an exit signal.
This indicator is best used in confluence with other indicators in order to develop a reliable strategy.
Range MarkerThis indicator is built for chart traders.
When using price and action to trade, you need to keep the chart scale the same.
So this indicator will help you to mark the range you choose.
Let you keep precise when reading the chart.
Enjoy it!
EMA Slope + EMA Cross Strategy (by ChartArt)This strategy uses divergences between three exponential moving averages and their slope directions as well as crosses between the price and these moving averages to switch between a long or short position. The strategy is non-stop in the market and always either long or short.
In addition the moving averages and price bars are colored depending if they are trending up or down.
The strategy was created for the "EURUSD" daily timeframe.
All trading involves high risk; past performance is not necessarily indicative of future results. Hypothetical or simulated performance results have certain inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not actually been executed, the results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown.
Narrow Range + Inside Day, Long Only Strategy (by ChartArt)This long only strategy determines when there is both a NR7 (narrow range 7, a trading day in which the range is narrower than any of the previous six days), plus a inside day (high of the current day is lower than the high of the previous day and the low of the current day is higher than the low of the previous day) both on the same trading day and enters a long trade when the close is larger than the open and the slope of the simple moving average is upwards, too.
The strategy closes the long trade next time the daily close is larger than the open in any of the next trading days. In addition the NR7ID can be colored (the color is green when the close is larger that day than the open, else the color is red) and the SMA can be drawn with a color based on the direction of the SMA slope. To fine-tune the strategy it is highly recommended to change the period length of the SMA, which determines if the measured SMA slope is upwards or not.
Inspiration:
How to trade NR7 and Inside Day Pattern
paststat.com
Code credit:
NR7 indicator script from Tradingview user Lazybear:
pastebin.com
The Always Winning Holy Grail Strategy - Not (by ChartArt)How to win all the time if 1+1 = 2
The most upvoted strategies on Tradingview are those which seemingly work 100%, but they actually don't at all because they are repainting and would not work in live trading reality. They are using the multi-time-frame strategy testing bug and thereby trade during the backtest on close prices before the bar has closed in reality.
Top list of these cheating repainting strategies:
1569 upvotes ANN Strategy
877 upvotes Vdub FX SniperVX3 Strategy
481 upvotes Get Trend Strategy
I guess there are much more strategies among the top upvoted strategies on Tradingview which cheat with a multi-time-frame close price, but three examples are enough. The ANN Strategy uses the daily close price as multi-time-frame and cheats with that. The Vdub FX SniperVX3 Strategy uses the half-day (720 minute) close price to cheat and the Get Trend Strategy uses the 160 minute bar close for repaint cheating (at least here the author of this strategy explains that his strategy is only demo and would not work, which might be the reason why it has 1000 less upvotes than the ANN Strategy. I already wrote months ago a comment underneat these strategies to explain this issue but it hasn't stopped these strategies from getting more and more upvotes and staying in the top list.
I thought this way of cheating is lame, so I invented a new way to cheat my way to seemingly reach 100% profitable trades all the time by going long if 1+1 is equal to 2. Welcome to super wide stop losses. Simply use a extreme unrealistic large stop loss and take profit after a realistic amount of pips and according to Tradingview's current backtest module you win 100% all the time. Yay! :)
My recommendation for the Tradingview team is to add a function to let the user define a stop out and margin call level and maybe set a realistic setting as default, like 100%.
Please don't trade with this strategy!
Buy Tuesday Strategy (by ChartArt)This strategy is as simple as possible: Every Tuesday a new long trade is opened, when Monday (yesterday) closed higher than it opened the week. The strategy closes all orders when the next close is larger than the open.
This strategy does not have any other stop loss or take profit money management logic and is therefore VERY risky, because it always waits to close all orders until the close is larger than the open. I recommend to mainly use it to find stocks or assets which are trending higher and are following this very basic trading idea.
--
P.S. The code of the strategy does not work on digital assets like Bitcoin, Litecoin or Ethereum, which are traded every day including Saturday and Sunday, because the code checks if Monday was preceded by a Friday (and not by a Sunday and Saturday).
Fractal Breakout Strategy (by ChartArt)This long only strategy determines the price of the last fractal top and enters a trade when the price breaks above the last fractal top. The strategy also calculates the average price of the last fractal tops to get the trend direction. The strategy exits the long trade, when the average of the fractal tops is falling (when the trend is lower highs as measured by fractals). And the user can manually set a time delay of this exit condition. The default setting is a long strategy exit always 3 bars after the long entry condition appeared.
In addition as gimmicks the fractals tops can be highlighted (the default is blue) and a line can be drawn based on the fractal tops.This fractal top line is colored by the fractal top average trend in combination with the fractal breakout condition.
This strategy works better on higher time-frames (weekly and monthly), but it also works on the daily and some other time-frames. This strategy does not repaint, no repainting.
P.S. I thank Tradingview user barracuda who helped me with the time based exit condition code. And user RicardoSantos for coding the definition of the fractal top, which he uses in his " Fractals" scripts.
All trading involves high risk; past performance is not necessarily indicative of future results. Hypothetical or simulated performance results have certain inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not actually been executed, the results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown.
Daily Close Comparison Strategy (by ChartArt via sirolf2009)Comparing daily close prices as a strategy.
This strategy is equal to the very popular "ANN Strategy" coded by sirolf2009(1) which calculates the percentage difference of the daily close price, but this bar-bone version works completely without his Artificial Neural Network (ANN) part.
Main difference besides stripping out the ANN is that my version uses close prices instead of OHLC4 prices, because they perform better in backtesting. And the default threshold is set to 0 to keep it simple instead of 0.0014 with a larger step value of 0.001 instead of 0.0001. Just like the ANN strategy this strategy goes long if the close of the current day is larger than the close price of the last day. If the inverse logic is true, the strategy goes short (last close larger current close). (2)
This basic strategy does not have any stop loss or take profit money management logic. And I repeat, the credit for the fundamental code idea goes to sirolf2009.
(2) Because the multi-time-frame close of the current day is future data, meaning not available in live-trading (also described as repainting), is the reason why this strategy and the original "ANN Strategy" coded by sirolf2009 perform so excellent in backtesting.
All trading involves high risk; past performance is not necessarily indicative of future results. Hypothetical or simulated performance results have certain inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not actually been executed, the results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown.
(1) You can get the original code by sirolf2009 including the ANN as indicator here:
(1) and this is sirolf2009's very popular strategy version of his ANN:
MACD + Stochastic, Double Strategy (by ChartArt)This strategy combines the classic stochastic strategy to buy when the stochastic is oversold with a classic MACD strategy to buy when the MACD histogram value goes above the zero line. Only difference to the classic stochastic is a default setting of 71 for overbought (classic setting 80) and 29 for oversold (classic setting 20).
Therefore this strategy goes long if the MACD histogram goes above zero and the stochastic indicator detects a oversold condition (value below 29). If the inverse logic is true, the strategy goes short (stochastic overbought condition with a value above 71 and the MACD histogram falling below the zero line value).
Please be aware that this pure double strategy using simply two classic indicators does not have any stop loss or take profit money management logic.
All trading involves high risk; past performance is not necessarily indicative of future results. Hypothetical or simulated performance results have certain inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not actually been executed, the results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown.
Bollinger + RSI, Double Strategy (by ChartArt) v1.1This strategy uses the RSI indicator together with the Bollinger Bands to sell when the price is above the upper Bollinger Band (and to buy when this value is below the lower band). This simple strategy only triggers when both the RSI and the Bollinger Band indicators are at the same time in a overbought or oversold condition.
UPDATE
In this updated version 1.1 the strategy was both simplified for the user (less inputs) and made more successful in backtesting by now using a 200 period for the SMA which is the basis for the Bollinger Band. I also reduced the number of color alerts to show fewer, but more relevant trading opportunities.
And just like the first version this strategy does not use close prices from higher-time frame and should not repaint after the current candle has closed. It might repaint like every Tradingview indicator while the current candle hasn't closed.
All trading involves high risk; past performance is not necessarily indicative of future results. Hypothetical or simulated performance results have certain inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not actually been executed, the results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown.
P.S. For advanced users if you want access to more functions of this strategy script, then please use version 1.0:
Bollinger + RSI, Double Strategy (by ChartArt)Bollinger Bands + RSI, Double Strategy
This strategy uses a slower RSI with period 16 to sell when the RSI increases over the value of 55 (or to buy when the value falls below 45), with the classic Bollinger Bands strategy to sell when the price is above the upper Bollinger Band and falls below it (and to buy when the price is below the lower band and rises above it). This strategy only triggers when both the RSI and the Bollinger Bands indicators are at the same time in the described overbought or oversold condition. In addition there are color alerts which can be deactivated.
This basic strategy is based upon the "RSI Strategy" and "Bollinger Bands Strategy" which were created by Tradingview and uses no money management like a trailing stop loss and no scalping methods. Every win/loss trade is simply counted from the last overbought/oversold condition to the next one.
This strategy does not use close prices from higher-time frame and should not repaint after the current candle has closed. It might repaint like every Tradingview indicator while the current candle hasn't closed.
All trading involves high risk; past performance is not necessarily indicative of future results. Hypothetical or simulated performance results have certain inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not actually been executed, the results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown.
Moving Average Consecutive Up/Down Strategy (by ChartArt)This simple strategy goes long (or short) if there are several consecutive increasing (or decreasing) moving average values in a row in the same direction. The bars can be colored using the raw moving average trend. And the background can be colored using the consecutive moving average trend setting. In addition a experimental line of the moving average change can be drawn.
The strategy is based upon the "Consecutive Up/Down Strategy" which was created by Tradingview.
All trading involves high risk; past performance is not necessarily indicative of future results. Hypothetical or simulated performance results have certain inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not actually been executed, the results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown.
Rounded Weekly Pivot (by ChartArt)Trade with the trend. This is an overlay indicator which shows the weekly pivot (rounded) either as line or circle drawing, select-able by the user. The width of the pivot line (or circle) overlay is also adjustable.
In addition the bars can be colored by the trend, depending if the close price is above or below both the weekly and monthly pivots. If the close price is neither above or below both the weekly and monthly pivot prices the trend color is neutral blue.
The weekly pivot indicator with the optional setting that the pivot price is drawn as circles instead of a line:
And here with the pivot drawing disabled, showing only the pivot bar trend color
Outsidebar vs Insidebar, Illusion Strategy (by ChartArt)WARNING: This strategy does not work! Please don't trade with this strategy
I'm sharing this strategy for the following three educational reasons:
1. You can easily find 100% strategies, but if they only seem to work 100% on one asset, they actually don't work at all. Therefore never backtest your strategy only on one asset, especially forward testing is useless, because it tends to repeat the old patterns. Your strategy has to work on as many different assets as possible.
2. The pyramiding of orders can have an impact on the strategy. In this case if you manually change the strategy settings by increasing it from 1 to 100 pyramiding orders changes the percent profitable on "UKOIL" monthly from 100% to 90% profitable. On other assets you can see very different results. Allowing much more pyramiding orders in this case results in opening orders where the background color highlights appear.
3. The Tradingview backtest beta version currently does not close the last open trade during the backtest. In this case going long on "UKOIL" near the top in 2011 as this strategy did would result in a big loss in 2015. But since the trade is still open and not canceled out by a new short order it still appears as if this strategy works 100% profitable. Which it doesn't.
Moving Average Cross Alert, Multi-Timeframe (MTF) (by ChartArt)See when two moving averages cross. With the option to choose between four moving average calculations:
SMA = simple moving average
EMA = exponential moving average (default)
WMA = weighted moving average
Linear = linear regression
The moving averages can be plotted from different time-frames, like e.g. the weekly or 4 hour time-frame using HL2, HLC3 or OHLC4 as price source for the calculation. In addition there is a background color alert and arrows when the moving averages cross each other when the price also rises or falls. And the moving averages are colored depending on their trend direction (if they are trending up or down).
Market Trend Strength (MTS) (by ChartArt)See the current trend strength of the market. An additional filter makes trend consolidation areas visible. The color changes there each bar back and forth between green and red.
This area was interesting. Would have been a better example:
If the filter is deactivated the indicator shows the last measured price trend (green for up and down for red).
JFC 21:52JFC 21:52 — Brief Description
Concept: Pure time/price rule, no indicators.
Reference: Close at 21:20 (chart/exchange timezone).
Entry (21:52):
– LONG if price is below the 21:20 close.
– SHORT if price is above the 21:20 close.
– Equal → no trade.
Exit: Force close at 22:13.
Frequency: Max one trade per day.
Note: Use 1-minute resolution and the correct chart timezone; market must be trading at those times.
EMA + VWMA + ATR Smoothed BuySell (merged) - TOM ZENG 202509Logic and Functionality Analysis
The script is divided into three main logical sections: EMA trend analysis, ATR-based signal generation, and VWMA smoothing.
1. EMA Trend Analysis (EMA Fan) 📈
This section uses a series of Exponential Moving Averages (EMAs) to identify trends. You've wisely chosen a set of EMA lengths (8, 21, 50, 200) that are commonly used in trading. These numbers are often derived from the Fibonacci sequence and are believed to offer a good balance of sensitivity to recent price action while still reflecting the underlying trend.
Purpose: The EMAs serve as dynamic support and resistance levels. When the price is above the EMAs and they are fanned out in ascending order (short-term EMA above long-term EMA), it indicates a strong uptrend. Conversely, a descending order indicates a downtrend.
Customization: The code allows you to easily adjust the EMA lengths in the inputs section, giving you control over the sensitivity of your trend analysis.
2. ATR Trailing Stop (Buy/Sell Signals) 🎯
This is the core of the indicator's signal-generating capability. It uses the Average True Range (ATR) to create a dynamic trailing stop line. The ATR measures volatility, so the stop line adjusts automatically to wider price swings.
Logic: The script uses a var float variable xATRTrailingStop to store the value of the stop line from the previous bar. The code then determines the current bar's stop line by comparing the current price to the previous bar's stop line and using math.max and math.min to smoothly move the line along with the trend.
Signal Generation: The pos variable tracks whether the trend is long (pos = 1) or short (pos = -1). The isLong and isShort variables act as a state machine, ensuring that the "Buy" and "Sell" signals are only triggered once at the exact point of a crossover, rather than on every subsequent bar.
Visuals & Alerts: The plotshape functions create labels directly on the chart, and the barcolor function changes the color of the candlesticks, providing a clear visual representation of the current trend state. The alertcondition functions are crucial for automation, allowing you to set up notifications for when a signal occurs.
3. VWMA and Combined Average 🌊
This section introduces a Volume-Weighted Moving Average (VWMA), which gives more weight to periods of high trading volume. This makes the VWMA more responsive to significant moves that are backed by strong institutional buying or selling.
Combined Logic: The avg1 variable creates a new line by averaging the VWMA and the xATRTrailingStop line. This is an innovative approach to blend two different types of analysis—volume-based trend and volatility-based risk management—into a single, smoothed line. It can act as an additional filter or a unique trading signal on its own.
Summary
Your code is a very effective and clean example of a multi-faceted indicator. It correctly implements a robust ATR trailing stop for signals while also providing valuable trend context through EMAs and volume analysis through VWMA. The combination of these elements makes it a powerful tool for a trader looking for a comprehensive view of the market.
