Schaff Trend Cycle + Double MAThis strategy uses two different moving averages to determine a trend. It opens a position on a pullback from a trend.
Conditions for buy signal are:
►Crossover out of Shaff Trend Cycle's extreme levels
►The price is above its short period exponential moving average.
►A short period exponential moving average is above a long period exponential moving average.
*Conditions for sell are the opposite.
All in all, I don't think it needs to be on your chart but it can be optimized and even successful on some timeframes.
Shaff Trend Cycle solution was provided by @everget, I converted his script to Pine v.4, added exponential averages and created an algorithm for backtesting.
In den Scripts nach "backtesting" suchen
expected range STRATEGYThis is the strategy version of "expected range STUDY". The buy and sell signals are generated with the study version, but what is displayed on the chart is different. Here, the PnL of each trade is shown on the chart, as well as the peak profit point of each trade up till the present. Black areas represent take profit and waiting for the next trade to start. Green = long. Red = short. Set to take profit at 53% and stoploss is set to -7%. Having a stoploss trigger does not put a black area on the chart. For the XBTUSD 2 hour chart, but use it however you like on whatever chart for backtesting.
Enjoy. Don't get rekt. A good backtest doesn't mean a good forward test. Use at your own risk.
expected range STUDYThis is an indicator that measures how much price movement (low to high) we've seen in a set of 1 bar back, 2 bars back, 3 bars back, 5 bars back, 8 bars back using the Fibonacci sequence up to 89 bars back, and then measures how low or high within each range we are, sort of like giving a rating of 0 for sitting on the lower Bollinger Band and a rating of 100 for sitting on the higher Bollinger band. It combines all the data and weights the data by the historical strength of signal from each length of bands. It's been tuned to a 2 hour XBTUSD chart, but it could be used on other things and other timeframes too. Some tweaking would be needed, though. The final result works more like a trend following indictor than and indicator that tries to pick an exact trend reversal point. However, you're free to use it how you want. Frequently you get a nice red or green spike up showing you when the bottom or top is in, but sometimes those spikes are just the start of an extended down move or up move.
On the chart, a buy (long) signal is generated when the green line crosses up above the orange line. To make it extra clear the background is green when you should be long. A sell (short) signal is generated with the red line crosses up above the yellow line. The background will be red when you should be short. If the background is black, it's indicating a profit of over 53% was taken and it's waiting for another trade to start. Up to you to take profit or keep riding your trade.
For XBTUSD trades, a full take profit on any trade exceeding 53% gains works nice (on 1x leverage) and a stoploss of -7% works quite nicely too. One could use this on up to 2x leverage but I wouldn't recommend going much higher. Have fun. Trade carefully. Don't get rekt.
I will release the "expected range STRATEGY" to go along with this so you can do your own backtesting.
Disclaimer: I haven't tested the alerts, but they should work. Use at your own risk.
Heiken-Ashi CandlesSimple script to view Heiken-Ashi candles below a normal candles chart.
Could also be useful for using HA calcs in strategy scripts on normal candles chart for proper backtesting.
I adapted this to v4 from original v2 script by @samtsui. If you like please remember to give him a Thumbs Up for his original version! ->
Golden Cross by -Westy-Quick Guide
- Yellow cross and green MA on top = Potential uptrend
- Yellow cross and red MA on top = Potential downtrend
A simple golden cross indicator of the green 50 and red 200 SMA with a yellow cross for ease of visibility and backtesting.
Generally, longer time frames more powerful signals but are less frequent. I typically use it on the 4 hour, daily and weekly.
Complete turtles strategy based on the donchian channelsDear Traders and investor,
I want to demonstrate scrypt of the iconic "trend following strategy" coded by my
The main idea was borrowed from the book "Way of the Turtle: The Secret Methods that Turned Ordinary People into Legendary". The strategy is based on the donchian channels and is one of the oldest and easiest strategy in the using. Also strategy include risk managment and trends filter which prevent false entries and high drawndowns. The results are based on the period from 2006 to present, but you can also change timeframe and period of backtesting.
Best regards,
Vlad
SimpleCrossOver_BotThis is a simple example of how you can compile your own strategy
This script contains the code for alerts and for backtesting.
In order to use the backtester, comment out the sections to be used for signals, and comment in the sections to be used on the back tester, and visa versa for using the script for alerts in order to automate your own bot.
Awesome Oscillator.MMouse_Lager_BCEAwesome Oscillator with added options for turning short trades on and off, as well as a start date for backtesting.
Pivot Reversal Strategy - TimeFramedThis is Pivot Reversal Strategy including the time frames for backtesting.
3 Duck's Trading System from Babypips.comThe 3 Duck's Trading System from Babypips.com
The 3 Duck's Trading System is the most popular and active trading system thread on the the babypips.com forum. It is a system that is mainly for beginners because it teaches you discipline, learning to cope with price moving against your position and learning to stay in a trade and keep profits running. For the thread and more info on the 3 Duck's Trading System click here
How does it work?
The system is a very simple enter/exit based on the 60 SMA of 3 different time frames: 4 hour, 1 hour and 5 minute.
The Rules, er, the Ducks! The Ducks must all be in a row for a trade to take place!
Duck 1 - To go long, price must be above the 60 SMA on the 4 hour chart.
Duck 2 - To go long, price must be above the 60 SMA on the 1 hour chart.
Duck 3 - To go long, price must cross above the 60 SMA on the 5 minute chart and the 60 SMA of the 5 minute chart must be below that of the 4 hour and 1 hour chart. (obviously the reverse for shorting)
YOU MUST USE THIS SYSTEM ONLY ON THE 5 MINUTE CHART.
I say this because I have already charted all of the Ducks into the 5 minute chart so you don't have to flip back and forth.
I have also added some inputs for profit targets, stop targets, trailing stops and times to trade for backtesting.
If you have any questions or comments, please let me know! If you see I messed up on something, please let me know!
Also a VERY special thanks to the babypips.com user Captain_Currency . He wrote this strategy 10 years ago (2007 was 10 years ago?!) and he is still active on the thread and posting results and offering help!
Adam Smith - MovingAvg CrossSimple Moving Average Cross script. Test on stocks and currency. For stocks test shorter time periods, meaning intra-day time periods such as 3min to 30min and so on to fit what is best. For currency, try longer periods with this model such as day to weeks depending on which currency.
NOTE: Take a look at your Max Drawdowns when testing. This will be the main indicator once you figure out your time period for backtesting. This will also let you know how much money to save and/or hold back in savings for down periods.
Trend v4.0 Another updateYet another update, default settings can be customized to your needs. Be aware that while this is similar to the other versions, this can only repaint an active bar, but that slows it down by one period. You are warned. Be that as it may, the basic idea is the same; trying to capture the really strong moves into overbought or oversold territory as defined by Relative Strength index. In RSI mode, you can see the smoothing has slowed it down a bit, but warrants backtesting.
First green bar go long, First red bar go short, first white bar possible trend exhaustion. Or use crossovers and such, play with the inputs OB/OS, RSI length, signal length, tick length, swing length, as I said customize to your tastes. I offer no surety as to its efficacy, but we all learn.
Trade Responsibly,
Shiroki
eBacktesting - Learning: Trend LineseBacktesting - Learning: Trend Lines helps you spot clean trend lines automatically, using real swing points (highs/lows) and confirming a line only after it’s “respected” multiple times.
What you’ll see on the chart
- Uptrend lines (support) when price is making higher lows
- Downtrend lines (resistance) when price is making lower highs
- A simple way to study structure, spot “respect” of a trend line, and understand when a trend may be weakening
- Trend line breaks are based on candle closes, not just quick wicks, so the signals are clearer
You can also keep a few older lines on the chart, making it easy to review past reactions and build pattern recognition.
These indicators are built to pair perfectly with the eBacktesting extension, where traders can practice these concepts step-by-step. Backtesting concepts visually like this is one of the fastest ways to learn, build confidence, and improve trading performance.
Educational use only. Not financial advice.
eBacktesting - Learning: Support & ResistanceeBacktesting - Learning: Support & Resistance helps you spot the price levels where the market repeatedly reacts, bounces, or rejects — the classic “floors” (support) and “ceilings” (resistance) that many day traders use to plan entries, stops, and targets.
This indicator automatically marks historical support and resistance levels right where they formed, so you can scroll back and study how price respected (or broke) those zones over time. It also highlights important moments when a level is broken, showing you how a broken resistance can later act like support (and vice-versa).
These indicators are built to pair perfectly with the eBacktesting extension, where traders can practice these concepts step-by-step. Backtesting concepts visually like this is one of the fastest ways to learn, build confidence, and improve trading performance.
Educational use only. Not financial advice.
eBacktesting - Learning: Change of CharactereBacktesting - Learning: Change of Character helps you spot a “Change of Character” (CHoCH) — the moment price stops behaving one way and starts behaving the other.
It does this by tracking clear swing highs and swing lows, then marking the first **candle close** that breaks structure **against** the current move:
- Bullish CHoCH: price shifts from making lower structure to breaking above a key swing high.
- Bearish CHoCH: price shifts from making higher structure to breaking below a key swing low.
Use CHoCH to practice timing: early trend shifts, reversals, and potential new legs — especially when combined with your usual confluence (liquidity, premium/discount, key levels, sessions, etc.).
These indicators are built to pair perfectly with the eBacktesting extension, where traders can practice these concepts step-by-step. Backtesting concepts visually like this is one of the fastest ways to learn, build confidence, and improve trading performance.
Educational use only. Not financial advice.
eBacktesting - Learning: Order BlockseBacktesting – Learning: Order Blocks helps you spot Order Blocks on your chart in a clean, beginner-friendly way.
When price breaks structure, the indicator highlights the last opposite candle that often becomes a key reaction zone later (the Order Block). You’ll see the OB marked as a zone, and when price comes back and mitigates it (returns into the zone), that OB is removed so your chart stays uncluttered and focused on what matters now.
This indicator is built to pair perfectly with the eBacktesting extension, where traders can practice these concepts step-by-step. Backtesting concepts visually like this is one of the fastest ways to learn, build confidence, and improve trading performance.
Educational use only. Not financial advice.
eBacktesting - Learning: BreakoutseBacktesting - Learning: Breakouts highlights ranges & breakout behaviors in a clean, visual way.
It automatically:
- Detects consolidation ranges (tight price action) and draws a range box
- Marks a breakout only when a candle CLOSES outside the range (no wick-only breakouts)
Adds a label on the breakout candle (↑ bullish breakout / ↓ bearish breakout)
These indicators are built to pair perfectly with the eBacktesting extension, where traders can practice these concepts step-by-step. Backtesting concepts visually like this is one of the fastest ways to learn, build confidence, and improve trading performance.
Educational use only. Not financial advice.
eBacktesting - Learning: FVGeBacktesting - Learning: FVG is an indicator in the eBacktesting Learning series: a collection of tools designed to help new traders understand the most important concepts in trading through clear, visual examples directly on the chart.
This indicator highlights Fair Value Gaps (FVGs): areas where price moved so quickly that it left behind an imbalance. These zones often act like "magnets" for future price action and can become important areas to watch for reactions, continuations, or reversals.
To keep the chart clean and the learning process practical, FVGs are only displayed when they remain relevant, meaning they are not instantly cleared by the very next candle. This helps beginners focus on the imbalances that actually persist and are more likely to matter.
Each FVG is drawn as a zone with a midpoint line and will visually update as price interacts with it:
Touched when price trades into the zone
Filled when price completely clears the zone
These indicators are built to pair perfectly with eBacktesting extension, where traders can practice these concepts step-by-step. Backtesting concepts visually like this is one of the fastest ways to learn, build confidence, and improve trading performance.
Educational use only. Not financial advice.
Range Breakout Statistics [Honestcowboy]⯁ Overview
The Range Breakout Statistics uses a very simple system to detect ranges/consolidating markets. The principle is simple, it looks for areas where the slope of a moving average is flat compared to past values. If the moving average is flat for X amount of bars that's a range and it will draw a box.
The statistics part of the script is a bit more complicated. The aim of this script is to expand analysis of trading signals in a different way than a regular backtest. It also highlights the polyline tool, one of my favorite drawing tools on the tradingview platform.
⯁ Statistics Methods
The script has 2 different modes of analyzing a trading signals strength/robustness. It will do that for 2 signals native to the script.
Upper breakout: first price breakout at top of box, before max bars (100 bars by default)
Lower breakout: first price breakout at bottom of box, before max bars
The analysis methods themselves are straightforward and it should be possible for tradingview community to expand this type of analysis to other trading signals. This script is a demo for this analysis, yet some might still find the native signals helpful in their trading, that's why the script includes alerts for the 2 native signals. I've also added a setting to disable any data gathering, which makes script run faster if you want to automate it.
For both of the analysis methods it uses the same data, just with different calculations and drawing methods. The data set is all past price action reactions to the signals saved in a matrix. Below a chart for explaining this visually.
⯁ Method 1: Averages Projection
The idea behind this is that just showing all price action that happened after signal does not give actionable insights. It's more a spaghetti jumble mess of price action lines. So instead the script averages the data out using 3 different approaches, all selectable in the settings menu.
Geometric Average: useful as it accurately reflects compound returns over time, smoothing out the impact of large gains or losses. Accounts for volatility drift.
Arithmetic Average: a standard average calculation, can be misleading in trading due to volatility drift. It is the most basic form of averaging so I included it.
Median: useful as any big volatility huge moves after a signal does not really impact the mean as it's just the middle value of all values.
These averages are the 2 lines you will find in the middle of the projection. Having a clear difference between a lower break average and upper break average price reaction can signal significance of the trading signal instead of pure chaos.
Outside of this I also included calculations for the maximum and minimum values in the dataset. This is useful for seeing price reactions range to the signal, showing extreme losses or wins are possible. For this range I also included 2 matrices of highs and lows data. This makes it possible to draw a band between the range based on closing price and the one using high/low data.
Below is a visualisation of how the averages data is shown on chart.
⯁ Method 2: Equity Simulation
This method will feel closer to home for traders as it more closely resembles a backtest. It does not include any commissions however and also is just a visualisation of price reaction to a signal. This method will simulate what would happen if you would buy at the breakout point and hold the trade for X amount of bars. With 0 being sell at same bar close. To test robustness I've given the option to visualise Equity simulation not just for 1 simulation but a bunch of simulations.
On default settings it will draw the simulations for 0 bars holding all the way to 10 bars holding. The idea behind it is to check how stable the effect is, to have further confirmation of the significance of the signal. If price simulation line moves up on average for 0 bars all the way to 10 bars holding time that means the signal is steady.
Below is a visualisation of the Equity Simulation.
⯁ Signal filtering
For the boxes themselves where breakouts come from I've included a simple filter based on the size of the box in ATR or %. This will filter out all the boxes that are larger top to bottom than the ATR or % value you setup.
⯁ Coloring of Script
The script includes 5 color themes. There are no color settings or other visual settings in the script, the script themes are simple and always have colors that work well together. Equity simulation uses a gradient based on lightness to color the different lines so it's easier to differentiate them while still upper breaks having a different color than lower breaks.
This script is not created to be used in conjunction with other scripts, it will force you into a background color that matches the theme. It's purpose is a research tool for systematic trading, to analyse signals in more depth.
Metaverse color theme:
⯁ Conclusion
I hope this script will help traders get a deeper understanding of how different assets react to their assets. It should be possible to convert this script into other signals if you know how to code on the platform. It is my intention to make more publications that include this type of analysis. It is especially useful when dealing with signals that do not happen often enough, so a regular backtest is not enough to test their significance.
Volatility Trend Score [BackQuant]Volatility Trend Score
Overview
Volatility Trend Score is a trend-strength and regime-evaluation indicator built to measure directional persistence, not just direction. Most trend tools answer “up or down” using slope, crossovers, or a single condition. This indicator answers a more useful question for real trading: “How consistently is trend structure holding up once volatility is accounted for?”
It does this by building a volatility-scaled trailing structure (ATR-based) and then scoring how that structure evolves over a configurable lookback range. The output is a continuous score that rises when trend is persistent and decays when price action becomes noisy, mean-reverting, or unstable.
What it is measuring (the real goal)
This indicator is not trying to predict reversals. It is trying to quantify whether the market is behaving like a trend market or a chop market. It focuses on:
Persistence: does structure keep pushing in one direction bar after bar?
Stability: are pullbacks being absorbed without breaking the trailing structure?
Regime: is the market trending strongly enough to justify directional bias?
If you already have entries from other systems, this becomes a high-quality trend filter and trade management layer.
Core idea
At its foundation, the indicator combines two parts:
A volatility-adjusted trailing level derived from ATR and a user-defined factor.
A rolling persistence score that compares the current trail to prior trail values over a configurable loop window.
The trailing structure adapts to volatility and enforces one-sided movement, while the scoring logic converts that behavior into a numeric measure of trend quality.
Inputs and what they actually control
Average True Range Period (calc_p)
Defines the ATR window used to estimate volatility. A higher value smooths the volatility estimate and makes the trailing structure less reactive.
Factor (atr_factor)
Scales the ATR band size. Higher values widen the trailing band, filtering more noise, reducing flip frequency, and generally producing slower but more stable regimes.
For Loop Start/End (start/end)
Defines the comparison window used to build the score. It effectively sets how many historical trail values the current trail is compared against.
Shorter ranges produce a faster, more responsive score.
Longer ranges produce a slower, more “confidence-based” score that only climbs when trend persistence is sustained.
Long/Short Thresholds (thresL/thresS)
Convert a continuous score into regime thresholds.
Long threshold is a “trend quality requirement” for bullish bias.
Short threshold is used as a deterioration / breakdown trigger via crossunder logic.
Volatility-adjusted trailing structure
The trailing line is built from ATR bands around price:
up = close + ATR * factor
dn = close - ATR * factor
Then a trailing value is maintained with one-sided ratcheting behavior:
If dn rises above the previous trail, the trail steps up (ratchets upward).
If up drops below the previous trail, the trail steps down (ratchets downward).
This “ratchet” behavior is important. It prevents the trail from oscillating with small countertrend moves, forcing the trail to represent meaningful structure rather than micro-noise. On-chart, this trail often behaves like dynamic support/resistance in trends.
Why the trail is a better base than raw price
Price itself is noisy, and volatility changes the meaning of “big move” vs “small move.” By anchoring structure to ATR:
A move is interpreted relative to current volatility, not in absolute points.
High-volatility chop is less likely to be misread as a trend.
Trend structure is normalized across assets and timeframes more reliably.
This is why the score remains usable even when switching from low-vol assets to high-vol crypto pairs.
Trend scoring logic
The score is built by repeatedly comparing the current trailing value to trailing values from prior bars across a loop window:
If current trail > trail , add +1
If current trail < trail , add -1
This is a persistence test, not a momentum calculation. In a strong trend, the trail should generally keep stepping in the trend direction, so current values will be greater than many past values (bullish) or lower than many past values (bearish). In chop, the trail fails to progress meaningfully, so the score compresses, oscillates, or bleeds out.
How to interpret the score
Think of the score as a “trend conviction meter”:
High positive values: bullish persistence, structure is advancing consistently.
Low positive values: bullish bias may exist, but trend quality is weak or unstable.
Near zero: indecision, range behavior, or frequent structure challenges.
Negative values: bearish dominance or sustained deterioration in structure.
The speed of score change matters too:
Fast expansion suggests a fresh regime gaining traction.
Slow grind suggests mature trend continuation.
Rapid compression often signals consolidation, exhaustion, or a transition phase.
Signals and regime transitions
This script uses two different styles of conditions (important detail):
Long condition: score > long threshold (state-based, persistent while true).
Short condition: crossunder(score, short threshold) (event-based trigger).
That means:
Long bias can remain active as long as score stays above the long threshold.
Short regime flips are triggered at the moment the score breaks down through the short threshold.
On the chart, long/short shapes are only plotted when the regime flips (first bar of the change), not on every bar, using:
Long shape when signal becomes 1 and previous signal was -1
Short shape when signal becomes -1 and previous signal was 1
This keeps signals clean and avoids spam, making it usable for alerts and regime tagging.
Visual presentation
The indicator is designed to work both as a panel oscillator and as an on-chart overlay:
Score plot (oscillator): color reflects active regime state.
Optional trail on price: volatility-scaled structure line on chart.
Optional threshold reference lines: clear regime boundaries.
Optional candle coloring: makes regime obvious without reading the panel.
Optional background shading: useful for quick scanning and backtesting visually.
You can use only the score, only the trail, or both together depending on your workflow.
Practical use cases
1) Trend filter for systems
Use the score as a regime gate:
Allow long entries only when score is above the long threshold.
Avoid longs when score compresses toward zero or loses the threshold.
Treat the short threshold break as “trend is no longer healthy.”
This often improves system expectancy by reducing exposure during low-conviction conditions.
2) Trend quality grading
Instead of treating all uptrends as equal:
Higher score = higher persistence, better continuation odds.
Score plateau = trend losing pressure, continuation becomes less reliable.
Score decay while price rises = trend is getting weaker under the hood.
This is useful for position sizing or deciding whether to add to winners.
3) Trade management and exits
Two complementary tools exist here:
Trail line can act as a dynamic stop reference or structure invalidation level.
Score behavior can be used to scale out when persistence fades (before a full flip).
Many traders use the trail for “hard structure” and the score for “soft deterioration.”
4) Breakout confirmation vs fakeouts
A breakout that immediately fails to build score is often low quality.
Healthy breakouts usually come with score expansion as structure advances.
Fakeouts often revert quickly, score fails to climb, and regime stays unstable.
Tuning guidelines
These are general behaviors you can expect when adjusting settings:
Higher ATR period and factor: slower regimes, fewer flips, cleaner structure.
Lower ATR period and factor: faster reaction, more sensitivity, more noise risk.
Longer loop range: score becomes more “confidence-based,” slower to change.
Shorter loop range: score becomes more “tactical,” faster but more jittery.
A good way to tune is to pick the trail behavior first (ATR period and factor), then tune the score window (loop) to match how quickly you want “trend conviction” to build.
Market behavior focus
Volatility Trend Score is most valuable in markets where volatility shifts frequently and fake trends are common, especially crypto. It is designed to:
Stay out of low-quality chop where most indicators whipsaw.
Quantify when volatility is being expressed directionally (constructive trend).
Provide a clean regime framework for filtering, alignment, and management.
Summary
Volatility Trend Score converts volatility-adjusted structure into a quantified measure of trend persistence. By combining an ATR-based trailing mechanism with a rolling comparison score, it provides a more reliable read on trend quality than single-condition indicators. It is best used as a regime filter, a trend strength gauge, and a trade management layer, helping you stay aligned with strong directional phases while avoiding low-conviction envir
RSI Divergence Pro Price Overlay High-Prob v6RSI Divergence Pro — Comprehensive Usage Guide
1) What This Indicator Does (in plain English)
Goal: Detect high-probability reversal (and optionally continuation) points using RSI divergences, then draw clean visual lines on price (red/bearish, green/bullish) and attach a % Strength label to help you quickly decide if it’s worth trading.
Core logic:
• Finds confirmed peaks and valleys using ta.pivothigh and ta.pivotlow.
• Bearish: Price makes Higher High while RSI makes Lower High.
• Bullish: Price makes Lower Low while RSI makes Higher Low.
• Filters for high probability: RSI near OB/OS, min RSI diff, ATR scaling, pivot spacing.
• Draws lines on price chart and attaches % Strength label.
• Alerts trigger only when a new divergence line is drawn.
2) Inputs & What Each One Means
• RSI Period: Shorter = more reactive; longer = smoother.
• Pivot Left/Right: Controls peak/valley confirmation.
• RSI Overbought/Oversold: Default 60/40; tighten for lower TFs.
• Min RSI Divergence: Minimum difference between RSI pivots.
• ATR Length & Min Price Move vs ATR: Ensures structural change.
• Bars Between Pivots: Avoid micro noise and stale signals.
• Hidden Divergence toggle: OFF for reversal; ON for continuation.
3) The % Strength Label — What It Represents
Combines RSI divergence magnitude (60%), Price move vs ATR (30%), OB/OS proximity (10%).
Interpretation:
• 80–100%: A-grade signals.
• 60–79%: Good, tradable with confirmation.
• 40–59%: Caution.
• <40%: Usually skip.
4) High-Probability Trading Workflow (H1)
1. Step 1: Scan & identify the signal.
2. Step 2: Confirm with price action (structure break or engulfing).
3. Step 3: Entry (conservative or aggressive).
4. Step 4: Stop placement (pivot ±0.5×ATR).
5. Step 5: Take profit & management (TP1 1×ATR, TP2 2×ATR, trail).
5) Confluence & Filters
• EMA slope confirmation.
• Structure alignment with S/R zones.
• Volatility regime check.
6) Example Scenarios
• A) Bearish Classic Divergence: HH price + LH RSI, Strength 83%.
• B) Bullish Classic Divergence: LL price + HL RSI, Strength 68%.
• C) Hidden Bullish Divergence: HL price + LL RSI, Strength 75%.
7) Common Pitfalls & How to Avoid Them
• Forcing signals in dead volatility.
• Taking divergences in strong trends without confirmation.
• Ignoring pivot spacing.
8) Tuning for Your Style
• H1 defaults: RSI 10, pivots 5/5, thresholds 60/40.
• M15/M5: thresholds 65/35, min RSI diff 10–12.
• H4/D1: thresholds 58/42, ATR multiple 0.4–0.6.
9) Multi-Asset Notes
• FX majors: overlap session ideal.
• Indices: require engulfing confirmation.
• Crypto: use ATR multiple ≥0.7.
10) Alerts — How to Use Them
• Set alerts Once per bar close.
• Alert names: Bearish RSI Divergence, Bullish RSI Divergence.
11) Backtesting & Forward Testing
• Define rules: entry, stop, TP.
• Track Strength % bins.
12) Troubleshooting & Diagnostics
• No lines? Loosen thresholds.
• Too many lines? Tighten thresholds.
13) Quick Operator’s Checklist
• Signal present?
• Location near S/R?
• Confirmation present?
14) Future Upgrade Options
• Session filter (London–NY overlap).
• EMA slope confirmation.
• Structure-break confirmation.
• Alert text enhancements.
BULL Whale Finder + BTC 1hBULL Whale Finder + BTC 1h is a long-only strategy designed to capture strong impulsive moves in Bitcoin.
It trades expansion (Whale) bars that appear in the direction of the trend, confirmed by the 200-period moving average on both 1H and 4H, with price holding above the 20-period moving average.
Entries focus on impulsive moves that originate from structural zones, not late breakouts.
Risk management is fully automated:
ATR-based initial stop
Automatic profit protection (Pay-Self)
Adds and partial exits based on the expansion-bar sequence
A protected runner managed with a trailing stop
The user only sets the risk per trade (MLPT).
All other parameters are hardcoded and locked to prevent over-optimization.
👉 Ready for backtesting, discretionary execution, or full automation.






















