Leverage Strategy and a few words on risk/opportunityHello traders,
I started this script as a joke for someone... finally appears it could be used for educational content
Let's talk about leverage and margin call
Margin Call
A margin call is the broker's demand that an investor deposit additional money or securities so that the account is brought up to the minimum value, known as the maintenance margin.
A margin call usually means that one or more of the securities held in the margin account has decreased in value below a certain point.
Leverage
A leverage is a system which allows the trader to open positions much larger than his own capital. ... “Leverage” usually refers to the ratio between the position value and the investment needed,
Strat
The strategy simulates long/short positions on a 4h high/low breakout based on the chart candle close.
The panel below shows the strategy equity curve. Activating the margin call option will show when the account would be margin called giving the settings
Casino
I'm not doing any financial recommendation here.
I made this strategy so that people include more risk management metrics into their strategy.
From the code, we see it's fairly easy to calculate a leveraged position size and a margin call flag - when that flag is hit, the system stops trading.
I simplified things to the extreme here but my point is that the leverage is a double-edge sword gift.
Assuming we always take the same position sizing, increasing the leverage speed up how fast a margin could be ..... called. (bad joke? feel free to tell me). Not saying it will, saying it introduces more risk by design.
Then one could say "I'll just turn off that stupid margin call option". And that's when someone starts backtesting with unrealistic market conditions.
Finally...
When I backtest I always assume the worst in every scenario possible (because I'm French), I always try to minimize the risk first (also because I'm French), keeping as close from 0 as possible (French again)
Then I add the "opportunity" component, looking to catch the maximum of opportunity while keeping the risk low.
It's like a Rubix cube puzzle - decreasing the risk is one side of the equation but whenever I try to catch more opportunity... my risks increases.
Then I update my risk... and now the opportunity decreases... (#wut #wen #simple)
Completely removing the risk from a trading strategy isn't something I wouldn't dare doing.
Trading involves risk. Being obsessed by decreasing the risk is what I do BEST :)
Dave
Cari dalam skrip untuk "backtest"
Simple 17 BF 🚀A Simple Moving Average of period 17 based on ohlc4 values. We go long when price closes above it. We go short when price closes below it. No stop loss. No take profit.
This strategy is really to showcase how effective a basic system can be, and that with discipline and patience, trading does not need to be complex to yield good results over time.
You can change the Moving Average type, source and period in the settings as well as the backtesting range. I found 17 period SMA with ohlc4 to be a good fit for XBT/USD on Daily timeframe but for other pairs, the type, source and period will likely differ.
INSTRUCTIONS
Red turns to Green = Long Entry/Short Exit
Green turns to Red = Short Entry/Long Exit
The entries are based on when price crosses the MA and this is what the backtest is based on. We exit the current trade when we get an opposing signal and enter the new trade.
Easy to Use 50/100/200 Day Moving Average StrategyWhenever you see someone publish a chart or idea, what's the one thing you almost always see? Moving Averages!
Many investors focus on these indictors solely as entry and exit points, so here's an easy to manipulate strategy to backtest and see if this is feasible on your security.
CODE VARIABLES
LINE 2 - Here you can change your currency and amount you want to invest on each entry.
LINE 8/9/10 - Here we establish the 50 (Fast), 100 (Medium) and 200 (Slow) day variables. These can be adjusted to your choosing.
LINE 13/14/15 - Here we establish what date we want to start backtesting from. Simple change the defval on each line to change the date (In the code below we start on Jan 1st, 2010).
LINE 20/23 - Here, within the crossover and crossunder functions, we set which MA's must cross to enter and exit a trade. Below we have the 50 day moving above and under the 200 day. Simple change the variables to FastMA, MediumMA and SlowMA to your choosing.
NOTE: As a beginner you may not want to short stock, therefore LINE 5 was added to only allow long positions.
Hope this helps, from one beginner to another.
Cheers!
Triangular Moving Average (TMA) bandsWhat in the world is up folks ??!??
Here's the indicator of the day. Sharing a simple one today because I'm busy coding for a few clients (fun life of a top script author on TradingView)
The TMA bands is an indicator that I discovered on FXCM a few years ago FXCM TMA bands
From the screenshot above, we see that when the price hits the lower band, it's a possible reverse BUY signal. When it hits the upper band, it's a possible SELL signal
Methodology
1) The Take Profit 1 is the middle line, Take Profit 2 is the opposite band.
2) Once the TP1 is hit, set your Stop Loss to breakeven
3) Once the TP2 is hit, if you still want to stay in the trade, set your Stop Loss to the TP1
That's what we call a trailing stop loss which I offered in the Trade Manager : Trade-Manager-Open-Source-Version/
It will be a powerful tool in your arsenal for some scalp/intraday trades
After years of coding for traders, I worked with many brokers/API/languages so I'm very used to convert a script from a broker to another one (shameless self-advertising)
PS
Tomorrow I'll share the Signal version of my Algorithm Builder:
You'll be able to connect it in a single click to a very cool Backtest System made by the Pinescripters community
In other words, I'm selling the scripts to allow you to build your own signals in a few clicks AND to connect it easily to a kick-ass backtesting tool. More to come tomorrow
Hope you'll like it, like me, love it, love me, tip me :)
____________________________________________________________
Feel free to hit the thumbs up as it shows me that I'm not doing this for nothing and will motivate to deliver more quality content in the future. (Meaning... a few likes only = no indicators = Dave enjoying the beach)
- I'm an officially approved PineEditor/LUA/MT4 approved mentor on codementor. You can request a coaching with me if you want and I'll teach you how to build kick-ass indicators and strategies
Jump on a 1 to 1 coaching with me
- You can also hire for a custom dev of your indicator/strategy/bot/chrome extension/python
Manual Back Test LinesI created this indicator to primarily manually test other indicators in replay mode.
To use this indicator generally you will:
Select trade type: long or short
Enter your ATR (enter the actual ATR). The indicator will then calculate and plot your SL and targets based on your values
Default Stop Loss is ATR * 1.5
Default Target 1 is ATR * 1.5
Default Target 2 is ATR * 3
Using this indicator on Replay mode is great. What you do is go back in time. Hit play and as the indicator(s) you use provide signals pause.
Pull up options:
Select trade type
Update ATR value
Change date to entry date. Typically if you are trading off the daily timeframe you are going to wait for your current day candle to close to provide signal. That would mean your entry would be on the next day.
Click play and watch, track and record how trade unfolds.
Future updates:
I'd like to be able to have some way to click one button and have it fire that enter trade right now on chart. Also I'm working on figuring out how to calculate the ATR on the entry date so that isn't required to be entered.
Finally, I'd like to have some auto calculation on when targets and SL are hit. I have this partially done but it's more important that I use this indicator than spend time or funds to update it to do that. But I do plan on updating.
[New series!] [Consistent Losing Strategies] 34 EMA Scalping//---------------------------INTRO------------------------------
Hi All!
Let me introduce myself as a semi-successful forex trader & lover of automation.
I've taken to algo trading and have been hunting down strategies (that usually use indicators) to automate, backtest, and hopefully implement in MT4.
Unfortunately, most strategies are complete bulls*** and the select cases that are shown to "prove" success are limited.
These strategy sources often do not provide useful analytics either.
I want to change that approach to trading! We can really benefit each other and the community by being methodical about backtesting
as well as evaluating our results with some kind of scoring heuristic.
As for what that standardized process looks like..well I'm still working on it.
I'm pretty much on Tv for multiple hours of the day, screening strategies via Pinescript and I'd like to start sharing my progress!
This is a new series I'd like to start on consistently losing strategies. I'll make all the code public, so if you think I've made a blunder
or approached a problem the wrong way, then drop me a DM or paste your fix into the comments.
//---------------------------STRAT------------------------------
34 EMA Scalping strategy (ref. forextradingstrategies4u )
How you're supposed to trade it:
BUY:
1. Market is in an down trend as shown by the 34 EMA
2. Price breaks above a downwards trend line
3. Price breaks above the 34 EMA
4. Look for a very bullish candlestick or chart pattern
SELL:
1. Look for the 34 EMA to show we are in an uptrend
2. Price breaks below an upwards sloping trend line
3. Price breaks below 34 EMA
4. Look for a bearish candlestick or a chart pattern
//---------------------------CONC------------------------------
Q: Why does it fail?
A: I believe this strategy relies too much on subjective input (aka, trendlines).
Q: Why does it fail as an algo?
A: The 34 EMA is no more predictive than any other EMA, although it does a good job at filtering out noise.
Q: Should I try it out?
A: No, it's trash. This is the proof that it is trash.
Multiple MACD RSI simple strategySimple strategy script I've had for a while but looks like I never published.
Although it is one of my most simple it seems to have the best profitability. It is pretty rough though. the Stoch RSI has only a little weight to the trade trigger. I'll refine it more over time or you can by all means. Basically the Stoch RSI current K line has to be OVER 40 to trigger a SELL. It has no effect on buy side.
The triggers are roughly as follows:
Year - since so many assets have gone 2x, 3x, 10x+ since 2013 having a strategy that earns a 500% return from 2013 to now isn't that good if buy-and-holding would have got you 800%. This eliminates some of that noise and makes it a little easier to quickly gauge success. So buy/sell trigger need a value of greater or equal to 2018 (default)
MACD 1 - First MACD (short) needs to indicate greater than 0 to buy or less than 0 to sell.
MACD 2 - Same as MACD1 but for second MACD set (long)
Uptrend - Latest close + high divided by last periods close + high needs to be grater than 1. So if latest is 34.30 close and 34.60 high and previous interval is 34.80 close and 34.82 high, that is 0.99 and will not trigger a buy trade.
Downtrend - Same thing but close + low and less than 1.
This script/strategy is pretty rough but if there is interest I'll polish it more since it is a pretty solid but simple strategy for most assets.
How to automate this strategy for free... Version 2Hello fellow traders and automation lovers.
It has been about 2 years since we originally created Autoview to connect your exchanges/brokers with your TradingView alerts. We've since added multiple exchanges, parameters and have built a large community filled with awesome, passionate traders.
One of the first strategies we built was sadly not a viable one for trading due to it using built-in variables that resulted in the backtest results being inaccurate in comparison to placing live trades. Luckily, we did not encounter repainting until a few strategies in, however, there was a point where we published a few of them as well. We will be going through all of our scripts again to not only eliminate any repainting and update to version 3, but to also include all the code snippets that we've learned to use over the years that allow for accurate backtesting and live trading.
The first script we are redoing is our How to automate this strategy for free using a chrome extension. .
Easter egg: This includes a new snippet of code that makes controlling how many orders you pyramid within a study fast and easy.
We look forward to bringing all of our scripts and delving deep into Pine again :)
Happy Trading
Autoview
AK TREND ID v1.00Hello,
"Are we at the top yet ? "........ " Is it a good time to invest ? " ......." Should I buy or sell ? " These are the many questions I hear and get on the daily basis. 1000's of investors do not know when to go in and out of the market. Most of them rely on the opinion of "experts" on television to make their investment decisions. Bad idea.Taking a systematic approach when investing, could save you a lot of time and headache. If there was only a way to know when to get in and out of the market !! hmmmm. The good news is that there many ways to do that. The bad news is , are you disciplined enough to follow it ?
I coded the AK_TREND ID specifically to identified trends in the SPX or SPY only . How does it work ? very simply , I simply plot the spread between the 3 month and 8 month moving average on the chart.
If the spread > 0 @ month end = BUY
if the spread < 0 @ month end = SELL
The AK TREND ID is a LAGGING Indicator , so it will not get you in at the very bottom or get you out at the very top. I did a backtest on the SPX from 1984 to 7/2/2014 (yesterday), The rule was to buy only when the AK TREND ID was green. let's look at the result:
14 trades : 11 W 3 L , 78.75 % winning %
Biggest winner (%) = 108 %
Biggest loser (%) = -10.7 %
Average Return = 27 %
Total Return since 1984 = 351.3 %
You can see the result in detail here : docs.google.com
Although the backtesting results are good, the AK TREND ID is not to be used as a trading system. It is simply design to let you know when to invest and when to get out. I'm working a more accurate version of this Indicator , that will use both technical and fundamental data. In the mean time , I hope this will give some of you piece of mind, and eliminate emotions from your trading decision. Feel free to modify the code as you wish, but please share your finding with the rest of Trading View community.
All the best
Algo
Indicator: Kairi Relative Index (KRI)KRI is a leading indicator, just like RSI. More info: www.etoro.com
I have noticed KRI producing less false-divergences compared to RSI (in my limited BTC backtesting).
Give it a try / backtest on your instrument. Appreciate a note here on what you think.
Enhanced Ichimoku Cloud Strategy V1 [Quant Trading]Overview
This strategy combines the powerful Ichimoku Kinko Hyo system with a 171-period Exponential Moving Average (EMA) filter to create a robust trend-following approach. The strategy is designed for traders seeking to capitalize on strong momentum moves while using the Ichimoku cloud structure to identify optimal entry and exit points.
This is a patient, low-frequency trading system that prioritizes quality over quantity. In backtesting on Solana, the strategy achieved impressive results with approximately 3600% profit over just 29 trades, demonstrating its effectiveness at capturing major trend movements rather than attempting to profit from every market fluctuation. The extended parameters and strict entry criteria are specifically optimized for Solana's price action characteristics, making it well-suited for traders who prefer fewer, higher-conviction positions over high-frequency trading approaches.
What Makes This Strategy Original
This implementation enhances the traditional Ichimoku system by:
Custom Ichimoku Parameters: Uses non-standard periods (Conversion: 7, Base: 211, Lagging Span 2: 120, Displacement: 41) optimized for different market conditions
EMA Confirmation Filter: Incorporates a 171-period EMA as an additional trend confirmation layer
State Memory System: Implements a sophisticated memory system to track buy/sell states and prevent false signals
Dual Trade Modes: Offers both traditional Ichimoku signals ("Ichi") and cloud-based signals ("Cloud")
Breakout Confirmation: Requires price to break above the 25-period high for long entries
How It Works
Core Components
Ichimoku Elements:
-Conversion Line (Tenkan-sen): 7-period Donchian midpoint
-Base Line (Kijun-sen): 211-period Donchian midpoint
-Span A (Senkou Span A): Average of Conversion and Base lines, plotted 41 periods ahead
-Span B (Senkou Span B): 120-period Donchian midpoint, plotted 41 periods ahead
-Lagging Span (Chikou Span): Current close plotted 41 periods back
EMA Filter: 171-period EMA acts as a long-term trend filter
Entry Logic (Ichi Mode - Default)
A long position is triggered when ALL conditions are met:
Cloud Bullish: Span A > Span B (41 periods ago)
Breakout Confirmation: Current close > 25-period high
Ichimoku Bullish: Conversion Line > Base Line
Trend Alignment: Current close > 171-period EMA
State Memory: No previous buy signal is still active
Exit Logic
Positions are closed when:
Ichimoku Bearish: Conversion Line < Base Line
Alternative Cloud Mode
When "Cloud" mode is selected, the strategy uses:
Entry: Span A crosses above Span B with additional cloud and EMA confirmations
Exit: Span A crosses below Span B with cloud and EMA confirmations
Default Settings Explained
Strategy Properties
Initial Capital: $1,000 (realistic for average traders)
Position Size: 100% of equity (appropriate for backtesting single-asset strategies)
Commission: 0.1% (realistic for most brokers)
Slippage: 3 ticks (accounts for realistic execution costs)
Date Range: January 1, 2018 to December 31, 2069
Key Parameters
Conversion Periods: 7 (faster than traditional 9, more responsive to price changes)
Base Periods: 211 (much longer than traditional 26, provides stronger trend confirmation)
Lagging Span 2 Periods: 120 (custom period for stronger support/resistance levels)
Displacement: 41 (projects cloud further into future than standard 26)
EMA Period: 171 (long-term trend filter, approximately 8.5 months of daily data)
How to Use This Strategy
Best Market Conditions
Trending Markets: Works best in clearly trending markets where the cloud provides strong directional bias
Medium to Long-term Timeframes: Optimized for daily charts and higher timeframes
Volatile Assets: The breakout confirmation helps filter out weak signals in choppy markets
Risk Management
The strategy uses 100% equity allocation, suitable for backtesting single strategies
Consider reducing position size when implementing with real capital
Monitor the 25-period high breakout requirement as it may delay entries in fast-moving markets
Visual Elements
Green/Red Cloud: Shows bullish/bearish cloud conditions
Yellow Line: Conversion Line (Tenkan-sen)
Blue Line: Base Line (Kijun-sen)
Orange Line: 171-period EMA trend filter
Gray Line: Lagging Span (Chikou Span)
Important Considerations
Limitations
Lagging Nature: Like all Ichimoku strategies, signals may lag significant price moves
Whipsaw Risk: Extended periods of consolidation may generate false signals
Parameter Sensitivity: Custom parameters may not work equally well across all market conditions
Backtesting Notes
Results are based on historical data and past performance does not guarantee future results
The strategy includes realistic slippage and commission costs
Default settings are optimized for backtesting and may need adjustment for live trading
Risk Disclaimer
This strategy is for educational purposes only and should not be considered financial advice. Always conduct your own analysis and risk management before implementing any trading strategy. The unique parameter combinations used may not be suitable for all market conditions or trading styles.
Customization Options
Trade Mode: Switch between "Ichi" and "Cloud" signal generation
Short Trading: Option to enable short positions (disabled by default)
Date Range: Customize backtesting period
All Ichimoku Parameters: Fully customizable for different market conditions
This enhanced Ichimoku implementation provides a structured approach to trend following while maintaining the flexibility to adapt to different trading styles and market conditions.
Bilateral Filter For Loop [BackQuant]Bilateral Filter For Loop
The Bilateral Filter For Loop is an advanced technical indicator designed to filter out market noise and smooth out price data, thus improving the identification of underlying market trends. It employs a bilateral filter, which is a sophisticated non-linear filter commonly used in image processing and price time series analysis. By considering both spatial and range differences between price points, this filter is highly effective at preserving significant trends while reducing random fluctuations, ultimately making it suitable for dynamic trend-following strategies.
Please take the time to read the following:
Key Features
1. Bilateral Filter Calculation:
The bilateral filter is the core of this indicator and works by applying a weight to each data point based on two factors: spatial distance and price range difference. This dual weighting process allows the filter to preserve important price movements while reducing the impact of less relevant fluctuations. The filter uses two primary parameters:
Spatial Sigma (σ_d): This parameter adjusts the weight applied based on the distance of each price point from the current price. A larger spatial sigma means more smoothing, as further away values will contribute more heavily to the result.
Range Sigma (σ_r): This parameter controls how much weight is applied based on the difference in price values. Larger price differences result in smaller weights, while similar price values result in larger weights, thereby preserving the trend while filtering out noise.
The output of this filter is a smoothed version of the original price series, which eliminates short-term fluctuations, helping traders focus on longer-term trends. The bilateral filter is applied over a rolling window, adjusting the level of smoothing dynamically based on both the distance between values and their relative price movements.
2. For Loop Calculation for Trend Scoring:
A for-loop is used to calculate the trend score based on the filtered price data. The loop compares the current value to previous values within the specified window, scoring the trend as follows:
+1 for upward movement (when the filtered value is greater than the previous value).
-1 for downward movement (when the filtered value is less than the previous value).
The cumulative result of this loop gives a continuous trend score, which serves as a directional indicator for the market's momentum. By summing the scores over the window period, the loop provides an aggregate value that reflects the overall trend strength. This score helps determine whether the market is experiencing a strong uptrend, downtrend, or sideways movement.
3. Long and Short Conditions:
Once the trend score has been calculated, it is compared against predefined threshold levels:
A long signal is generated when the trend score exceeds the upper threshold, indicating that the market is in a strong uptrend.
A short signal is generated when the trend score crosses below the lower threshold, signaling a potential downtrend or trend reversal.
These conditions provide clear signals for potential entry points, and the color-coding helps traders quickly identify market direction:
Long signals are displayed in green.
Short signals are displayed in red.
These signals are designed to provide high-confidence entries for trend-following strategies, helping traders capture profitable movements in the market.
4. Trend Background and Bar Coloring:
The script offers customizable visual settings to enhance the clarity of the trend signals. Traders can choose to:
Color the bars based on the trend direction: Bars are colored green for long signals and red for short signals.
Change the background color to provide additional context: The background will be shaded green for a bullish trend and red for a bearish trend. This visual feedback helps traders to stay aligned with the prevailing market sentiment.
These features offer a quick visual reference for understanding the market's direction, making it easier for traders to identify when to enter or exit positions.
5. Threshold Lines for Visual Feedback:
Threshold lines are plotted on the chart to represent the predefined long and short levels. These lines act as clear markers for when the market reaches a critical threshold, triggering a potential buy (long) or sell (short) signal. By showing these threshold lines on the chart, traders can quickly gauge the strength of the market and assess whether the trend is strong enough to warrant action.
These thresholds can be adjusted based on the trader's preferences, allowing them to fine-tune the indicator for different market conditions or asset behaviors.
6. Customizable Parameters for Flexibility:
The indicator offers several parameters that can be adjusted to suit individual trading preferences:
Window Period (Bilateral Filter): The window size determines how many past price values are used to calculate the bilateral filter. A larger window increases smoothing, while a smaller window results in more responsive, but noisier, data.
Spatial Sigma (σ_d) and Range Sigma (σ_r): These values control how sensitive the filter is to price changes and the distance between data points. Fine-tuning these parameters allows traders to adjust the degree of noise reduction applied to the price series.
Threshold Levels: The upper and lower thresholds determine when the trend score crosses into long or short territory. These levels can be customized to better match the trader's risk tolerance or asset characteristics.
Visual Settings: Traders can customize the appearance of the chart, including the line width of trend signals, bar colors, and background shading, to make the indicator more readable and aligned with their charting style.
7. Alerts for Trend Reversals:
The indicator includes alert conditions for real-time notifications when the market crosses the defined thresholds. Traders can set alerts to be notified when:
The trend score crosses the long threshold, signaling an uptrend.
The trend score crosses the short threshold, signaling a downtrend.
These alerts provide timely information, allowing traders to take immediate action when the market shows a significant change in direction.
Final Thoughts
The Bilateral Filter For Loop indicator is a robust tool for trend-following traders who wish to reduce market noise and focus on the underlying trend. By applying the bilateral filter and calculating trend scores, this indicator helps traders identify strong uptrends and downtrends, providing reliable entry signals with minimal market noise. The customizable parameters, visual feedback, and alerting system make it a versatile tool for traders seeking to improve their timing and capture profitable market movements.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
CRYPTO:SOLUSD
Trailing Stop Loss [TradingFinder] 4 Machine Learning Methods🔵 Introduction
The trailing stop indicator dynamically adjusts stop-loss (SL) levels to lock in profits as price moves favorably. It uses pivot levels and ATR to set optimal SL points, balancing risk and reward.
Trade confirmation filters, a key feature, ensure entries align with market conditions, reducing false signals. In 2023 a study showed filtered entries improve win rates by 15% in forex. This enhances trade precision.
SL settings, ranging from very tight to very wide, adapt to volatility via ATR calculations. These settings anchor SL to previous pivot levels, ensuring alignment with market structure. This caters to diverse trading styles, from scalping to swing trading.
The indicator colors the profit zone between the entry point (EP) and SL, using light green for buy trades and light red for sell trades. This visual cue highlights profit potential. It’s ideal for traders seeking dynamic risk management.
A table displays real-time trade details, including EP, SL, and profit/loss (PNL). Backtests show trailing stops cut losses by 20% in trending markets. This transparency aids decision-making.
🔵 How to Use
🟣 SL Levels
The trailing stop indicator sets SL based on pivot levels and ATR, offering four options: very tight, tight, wide, or very wide. Very tight SLs suit scalpers, while wide SLs fit swing traders. Select the base level to match your strategy.
If price hits the SL, the trade closes, and the indicator evaluates the next trade using the selected filter. This ensures disciplined trade management. The cycle restarts with a new confirmed entry.
Very tight SLs, set near recent pivots, trigger exits early to minimize risk but limit profits in volatile markets. Wide SLs, shown as farther lines, allow more price movement but increase exposure to losses. Adjust based on ATR and conditions, noting SL breaches open new positions.
🟣 Visualization
The indicator’s visual cues, like colored profit zones, simplify monitoring, with light green showing the profit area from EP to trailed SL. Dashed lines mark entry points, while solid lines track the trailed SL, triggering new positions when breached.
When price moves into profit, the area between EP and SL is colored—light green for longs, light red for shorts. This highlights the profit zone visually. The SL trails price, locking in gains as the trade progresses.
🟣 Filters
Upon trade entry, the indicator requires confirmation via filters like SMA 2x or ADX to validate momentum. Filters reduce false entries, though no guarantee exists for improved outcomes. Monitor price action post-entry for trade validity.
Filters like Momentum or ADX assess trend strength before entry. For example, ADX above 25 confirms strong trends. Choose “none” for unfiltered entries.
🟣 Bullish Alert
For a bullish trade, the indicator opens a long position with a green SL Line (after optional filters), trailing the SL below price. Set alerts to On in the settings for notifications, or Off to monitor manually.
🟣 Bearish Alert
In a bearish trade, the indicator opens a short position with a red SL Line post-confirmation, trailing the SL above price. With alerts On in the settings, it notifies the potential reversal.
🟣 Panel
A table displays all trades’ details, including Win Rates, PNL, and trade status. This real-time data aids in tracking performance. Check the table to assess trade outcomes instantly.
Review the table regularly to evaluate trade performance and adjust settings. Consistent monitoring ensures alignment with market dynamics. This maximizes the indicator’s effectiveness.
🔵 Settings
Length (Default: 10) : Sets the pivot period for calculating SL levels, balancing sensitivity and reliability.
Base Level : Options (“Very tight,” “Tight,” “Wide,” “Very wide”) adjust SL distance via ATR.
Show EP Checkbox : Toggles visibility of the entry point on the chart.
Show PNL : Displays profit/loss data for active and closed trades.
Filter : Options (“none,” “SMA 2x,” “Momentum,” “ADX”) validate trade entries.
🔵 Conclusion
The trailing stop indicator, a dynamic risk management tool, adjusts SLs using pivot levels and ATR. Its confirmation filters reduce false entries, boosting precision. Backtests show 20% loss reduction in trending markets.
Customizable SL settings and visual profit zones enhance usability across trading styles. The real-time table provides clear trade insights, streamlining analysis. It’s ideal for forex, stocks, or crypto.
While filters like ADX improve entry accuracy, no setup guarantees success in all conditions. Contextual analysis, like trend strength, is key. This indicator empowers disciplined, data-driven trading.
Gartley 222 Strategy (Final Full Version)Gartley 222 Strategy (Bullish Pattern) — Repaint-Free, Backtestable
This strategy is based on the classic Gartley 222 harmonic pattern, originally introduced by H.M. Gartley in Profits in the Stock Market (1935). It identifies potential bullish reversal zones by detecting a five-point retracement structure (X-A-B-C-D) using pivot points and Fibonacci confluence.
🧠 Strategy Logic:
Detects valid pivot-based X, A, B, C points
Validates Gartley ratios:
AB = 61.8%–78.6% of XA
CD = 78.6%–88.6% of AB
Enters long at point D only after pivot confirmation (non-repainting)
Exits at 127% Fibonacci extension of XA or on stop loss
🔍 Features:
✅ Repaint-free and fully backtestable
✅ Visual X–A–B–C–D pattern lines on chart
✅ Customizable pivot length, risk, and reward ratios
✅ Alerts for real-time Gartley Buy pattern completion
Ideal for swing traders using 4H or Daily timeframes on trending instruments like NIFTY, BANKNIFTY, or major stocks.
TrendPredator FOTrendPredator Fakeout Highlighter (FO)
The TrendPredator Fakeout Highlighter is designed to enhance multi-timeframe trend analysis by identifying key market behaviors that indicate trend strength, weakness, and potential reversals. Inspired by Stacey Burke’s trading approach, this tool focuses on trend-following, momentum shifts, and trader traps, helping traders capitalize on high-probability setups.
At its core, this indicator highlights peak formations—anchor points where price often locks in trapped traders before making decisive moves. These principles align with George Douglas Taylor’s 3-day cycle and Steve Mauro’s BTMM method, making the FO Highlighter a powerful tool for reading market structure. As markets are fractal, this analysis works on any timeframe.
How It Works
The TrendPredator FO highlights key price action signals by coloring candles based on their bias state on the current timeframe.
It tracks four major elements:
Breakout/Breakdown Bars – Did the candle close in a breakout or breakdown relative to the last candle?
Fakeout Bars (Trend Close) – Did the candle break a prior high/low and close back inside, but still in line with the trend?
Fakeout Bars (Counter-Trend Close) – Did the candle break a prior high/low, close back inside, and against the trend?
Switch Bars – Did the candle lose/ reclaim the breakout/down level of the last bar that closed in breakout/down, signalling a possible trend shift?
Reading the Trend with TrendPredator FO
The annotations in this example are added manually for illustration.
- Breakouts → Strong Trend
Multiple candles closing in breakout signal a healthy and strong trend.
- Fakeouts (Trend Close) → First Signs of Weakness
Candles that break out but close back inside suggest a potential slowdown—especially near key levels.
- Fakeouts (Counter-Trend Close) → Stronger Reversal Signal
Closing against the trend strengthens the reversal signal.
- Switch Bars → Momentum Shift
A shift in trend is confirmed when price crosses back through the last closed breakout candles breakout level, trapping traders and fuelling a move in the opposite direction.
- Breakdowns → Trend Reversal Confirmed
Once price breaks away from the peak formation, closing in breakdown, the trend shift is validated.
Customization & Settings
- Toggle individual candle types on/off
- Customize colors for each signal
- Set the number of historical candles displayed
Example Use Cases
1. Weekly Template Analysis
The weekly template is a core concept in Stacey Burke’s trading style. FO highlights individual candle states. With this the state of the trend and the developing weekly template can be evaluated precisely. The analysis is done on the daily timeframe and we are looking especially for overextended situations within a week, after multiple breakouts and for peak formations signalling potential reversals. This is helpful for thesis generation before a session and also for backtesting. The annotations in this example are added manually for illustration.
📈 Example: Weekly Template Analysis snapshot on daily timeframe
2. High Timeframe 5-Star Setup Analysis (Stacey Burke "ain't coming back" ACB Template)
This analysis identifies high-probability trade opportunities when daily breakout or down closes occur near key monthly levels mid-week, signalling overextensions and potentially large parabolic moves. Key signals for this are breakout or down closes occurring on a Wednesday. This is helpful for thesis generation before a session and also for backtesting. The annotations in this example are added manually for illustration. Also an indicator can bee seen on this chart shading every Wednesday to identify the signal.
📉 Example: High Timeframe Setup snapshot
3. Low Timeframe Entry Confirmation
FO helps confirm entry signals after a setup is identified, allowing traders to time their entries and exits more precisely. For this the highlighted Switch and/ or Fakeout bars can be highly valuable.
📊 Example (M15 Entry & Exit): Entry and Exit Confirmation snapshot
📊 Example (M5 Scale-In Strategy): Scaling Entries snapshot
The annotations in this examples are added manually for illustration.
Disclaimer
This indicator is for educational purposes only and does not guarantee profits.
None of the information provided shall be considered financial advice.
Users are fully responsible for their trading decisions and outcomes.
Adaptive Gaussian MA For Loop [BackQuant]Adaptive Gaussian MA For Loop
PLEASE Read the following carefully before applying this indicator to your trading system. Knowing the core logic behind the tools you're using allows you to integrate them into your strategy with confidence and precision.
Introducing BackQuant's Adaptive Gaussian Moving Average For Loop (AGMA FL) — a sophisticated trading indicator that merges the Gaussian Moving Average (GMA) with adaptive volatility to provide dynamic trend analysis. This unique indicator further enhances its effectiveness by utilizing a for-loop scoring mechanism to detect potential shifts in market direction. Let's dive into the components, the rationale behind them, and how this indicator can be practically applied to your trading strategies.
Understanding the Gaussian Moving Average (GMA)
The Gaussian Moving Average (GMA) is a smoothed moving average that applies Gaussian weighting to price data. Gaussian weighting gives more significance to data points near the center of the lookback window, making the GMA particularly effective at reducing noise while maintaining sensitivity to changes in price direction. In contrast to simpler moving averages like the SMA or EMA, GMA provides a more refined smoothing function, which can help traders follow the true trend in volatile markets.
In this script, the GMA is calculated over a defined Calculation Period (default 14), applying a Gaussian filter to smooth out market fluctuations and provide a clearer view of underlying trends.
Adaptive Volatility: A Dynamic Edge
The Adaptive feature in this indicator gives it the ability to adjust its sensitivity based on current market volatility. If the Adaptive option is enabled, the GMA uses a standard deviation-based volatility measure (with a default period of 20) to dynamically adjust the width of the Gaussian filter, allowing the GMA to react faster in volatile markets and more slowly in calm conditions. This dynamic nature ensures that the GMA stays relevant across different market environments.
When the Adaptive setting is disabled, the script defaults to a constant standard deviation value (default 1.0), providing a more stable but less responsive smoothing function.
Why Use Adaptive Gaussian Moving Average?
The Gaussian Moving Average already provides smoother results than standard moving averages, but by adding an adaptive component, the indicator becomes even more responsive to real-time price changes. In fast-moving or highly volatile markets, this adaptation allows traders to react quicker to emerging trends. Conversely, in quieter markets, it reduces over-sensitivity to minor fluctuations, thus lowering the risk of false signals.
For-Loop Scoring Mechanism
The heart of this indicator lies in its for-loop scoring system, which evaluates the smoothed price data (the GMA) over a specified range, comparing it to previous values. This scoring system assigns a numerical value based on whether the current GMA is higher or lower than previous values, creating a trend score.
Long Signals: These are generated when the for-loop score surpasses the Long Threshold (default set at 40), signaling that the GMA is gaining upward momentum, potentially identifying a favorable buying opportunity.
Short Signals: These are triggered when the score crosses below the Short Threshold (default set at -10), indicating that the market may be losing strength and that a selling or shorting opportunity could be emerging.
Thresholds & Customization Options
This indicator offers a high degree of flexibility, allowing you to fine-tune the settings according to your trading style and risk preferences:
Calculation Period: Adjust the lookback period for the Gaussian filter, affecting how smooth or responsive the indicator is to price changes.
Adaptive Mode: Toggle the adaptive feature on or off, allowing the GMA to dynamically adjust based on market volatility or remain consistent with a fixed standard deviation.
Volatility Settings: Control the standard deviation period for adaptive mode, fine-tuning how quickly the GMA responds to shifts in volatility.
For-Loop Settings: Modify the start and end points for the for-loop score calculation, adjusting the depth of analysis for trend signals.
Thresholds for Signals: Set custom long and short thresholds to determine when buy or sell signals should be generated.
Visualization Options: Choose to color bars based on trend direction, plot signal lines, or adjust the background color to reflect current market sentiment visually.
Trading Applications
The Adaptive Gaussian MA For Loop can be applied to a variety of trading styles and markets. Here are some key ways you can use this indicator in practice:
Trend Following: The combination of Gaussian smoothing and adaptive volatility helps traders stay on top of market trends, identifying significant momentum shifts while filtering out noise. The for-loop scoring system enhances this by providing a numerical representation of trend strength, making it easier to spot when a new trend is emerging or when an existing one is gaining strength.
Mean Reversion: For traders looking to capitalize on short-term market corrections, the adaptive nature of this indicator makes it easier to identify when price action is deviating too far from its smoothed trend, allowing for strategic entries and exits based on overbought or oversold conditions.
Swing Trading: With its ability to capture medium-term price movements while avoiding the noise of short-term fluctuations, this indicator is well-suited for swing traders who aim to profit from market reversals or short-to-mid-term trends.
Volatility Management: The adaptive feature allows the indicator to adjust dynamically in volatile markets, ensuring that it remains responsive in times of increased uncertainty while avoiding unnecessary noise in calmer periods. This makes it an effective tool for traders who want to manage risk by staying in tune with changing market conditions.
Final Thoughts
The Adaptive Gaussian MA For Loop is a powerful and flexible indicator that merges the elegance of Gaussian smoothing with the adaptability of volatility-based adjustments. By incorporating a for-loop scoring mechanism, this indicator provides traders with a comprehensive view of market trends and potential trade opportunities.
It’s important to test the settings on historical data and adapt them to your specific trading style, timeframe, and market conditions. As with any technical tool, the AGMA For Loop should be used in conjunction with other indicators and solid risk management practices for the best results.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
