Simple profitable trading strategyThis strategy has three components.
Philakones EMAs are a sequence of five fibonacci EMAs. They range from 55 candles (green) to 8 candles (red) in length. A strong trend or breakout is marked by the emas appearing in sequence of their length from 8 to 55 or vice versa. These EMAs are also used to signal an exit. Only two EMAs are used for exit signals - when the 13 EMA crosses over/under the 55 EMA.
RSI gives a bullish signal when 40 > rsi > 70. Exit signals are oversold (30) or overbought (70)
Stochastics give a bullish signal when stoch < 80 and an exit signal when > 95.
Results include 3 ticks of slippage and taker fees of .002. Provides a pretty smooth equity curve with a 73% win rate and beats buy and hold by than 10x (returns about 60x overall) since start of 2017.
Cari dalam skrip untuk "TAKE"
EMA50Diff & MACD StrategyOne of my attempts to create a strategy for BTC.
Its a combination of EMA50Diff (the difference between spot and EMA50) and MACD.
Buy signal if (EMA50Diff) < -(EMADiffThreshold),
(MACD bearish crossunder),
(MACD) < -(MACDThreshold),
(EMA50Diff) > (EMA50Diff 1 candle ago),
(EMA50Diff 1 candle ago) < (EMA50Diff 2 candles ago)
Sell signal if (EMA50Diff) > (EMADiffThreshold),
(MACD bullish crossover),
(MACD) > (MACDThreshold),
(EMA50Diff) < (EMA50Diff 1 candle ago),
(EMA50Diff 1 candle ago) > (EMA50Diff 2 candles ago)
Exit either when target or stoploss get reached.
Initial capital is set to 100k and its currently going all-in on every trade but im looking for a better way to handle position sizes already..
Also i included slippage of 30 ticks and exchange commission of 0.15% (e.g. 2x BitMEX market taker fee)
Works best on 15m on bitfinex, bitstamp and gdax and i'm still trying to optimize it for bitmex too, will update when i got there..
Estimate exchange/broker fee commission from trade volumeThis script is used to estimate how much an exchange/broker makes off a particular pair/symbol. If Coinbase(GDAX) has a 0.25% taker fee and a 0.15% maker fee per trade and you estimate the average commission fee at 0.19% then you simple input that, and how many periods you'd like to know the total fee for (30 periods on the 1 day chart = last 30 days, 28 periods on 4 hour chart = last 7 days, etc).
This is for broad estimates of a single pair and only works well on exchanges that show only the volume on that exchange (stock markets may be less useful for this tool).
THIS TOOL IS TO PROVIDE A BROAD ESTIMATE , NOT AN EXACT FIGURE!
// percentage fee rate is entered as a percent: 3.5=3.5%, not 350%.
// pbtc , the one for calculating the USD value of fees that are in bitcoin, uses the price at time fees were realized. IE chart is on
// 1 day interval and XBARFEE is set at 4, then PBTC gives the USD value as if the exchange sold all btc at the end of each day for
// 4 days. i.e.:
// Day 1: BTCUSD= $5000 fees=1.5, Day 2: BTCUSD = $5000 fees=3.0, Day 3 BTCUSD = $10,000 fees=1.0, Day 4 BTCUSD = $20,000 fees=1.0
// PBTC would NOT show (1.5+ 3 + 1 + 1) = 6.5 * $20k = $130,000. It would do: (1.5*5000)+(3*5000)... = $52,500.
Open Close Cross Strategy R5 revised by JustUncleLThis revision is an open Public release, with just some minor changes. It is a revision of the Strategy "Open Close Cross Strategy R2" originally published by @JayRogers.
*** USE AT YOUR OWN RISK ***
JayRogers : "There are drawing/painting issues in pinescript when working across resolutions/timeframes that I simply cannot fix here.. I will not be putting any further effort into developing this until such a time when workarounds become available."
NOTE: Re-painting has not been observed with the default set up, nor with Alternate resolution multiplier up to 5.
Description:
Strategy based around Open-Close Moving Average Crossovers optionally from a higher time frame.
Setup:
I have generally found that setting the strategy resolution to 3-5x that of the chart you are viewing tends to yield the best results, regardless of which MA option you may choose (if any) BUT can cause a lot of false positives - be aware of this. JustUncleL: using one of the Smoothed MA helps reduce false positives.
Don't aim for perfection. Just aim to get a reasonably snug fit with the O-C band, with good runs of green and red. JustUncleL: using SMMA (8 to 10) gives a good fit.
Option to either use basic open and close series data, or pick your poison with a wide array of MA types.
Optional Stop Loss and Target Profit for damage mitigation if desired (can be toggled on/off)
Positions get taken automatically following a crossover - which is why it's better to set the resolution of the script greater than that of your chart, so that the trades get taken sooner rather than later.
If you make use of the stops/target profit, be sure to take your time tweaking the values. Cutting it too fine will cost you profits but keep you safer, while letting them loose could lead to more draw down than you can handle.
Revsion R5 Changes by JustUncleL
Corrected cross over calculations, sometimes gave false signals.
Corrected Alternate Time calculation to allow for Daily,Weekly and Monthly charts.
Open Public release.
Revision R4 By JustUncleL
Change the way the Alternate resolution in selected, use a Multiplier of the base Time Frame instead, this makes it easy to switch between base time frames.
Added TMA and SSMA moving average options. But DEMA is still giving the best results.
Using "calc_on_every_tick=false" ensures results between back testing and real time are similar.
Added Option to Disable the coloring of the bars.
Updated default settings.
R3 Changes by JustUncleL:
Returned a simplified version of the open/close channel, it shows strength of current trend.
Added Target Profit Option.
Added option to reduce the number of historical bars, overcomes the too many trades limit error.
Simplified the strategy code.
Removed Trailing Stop option, not required and in my option does not work well in Trading View, it also gives false and unrealistic performance results in back testing.
R2 Changes by @JayRogers:
Simplified and cleaned up plotting, now just shows a Moving Average derived from the average of open/close.
Tried very hard to alleviate painting issues caused by referencing alternate resolution.
ECO Strategy Backtest We call this one the ECO for short, but it will be listed on the indicator list
at W. Blau’s Ergodic Candlestick Oscillator. The ECO is a momentum indicator.
It is based on candlestick bars, and takes into account the size and direction
of the candlestick "body". We have found it to be a very good momentum indicator,
and especially smooth, because it is unaffected by gaps in price, unlike many other
momentum indicators.
We like to use this indicator as an additional trend confirmation tool, or as an
alternate trend definition tool, in place of a weekly indicator. The simplest way
of using the indicator is simply to define the trend based on which side of the "0"
line the indicator is located on. If the indicator is above "0", then the trend is up.
If the indicator is below "0" then the trend is down. You can add an additional
qualifier by noting the "slope" of the indicator, and the crossing points of the slow
and fast lines. Some like to use the slope alone to define trend direction. If the
lines are sloping upward, the trend is up. Alternately, if the lines are sloping
downward, the trend is down. In this view, the point where the lines "cross" is the
point where the trend changes.
When the ECO is below the "0" line, the trend is down, and we are qualified only to
sell on new short signals from the Hi-Lo Activator. In other words, when the ECO is
above 0, we are not allowed to take short signals, and when the ECO is below 0, we
are not allowed to take long signals.
You can change long to short in the Input Settings
Please, use it only for learning or paper trading. Do not for real trading.
ECO Strategy We call this one the ECO for short, but it will be listed on the indicator list
at W. Blau’s Ergodic Candlestick Oscillator. The ECO is a momentum indicator.
It is based on candlestick bars, and takes into account the size and direction
of the candlestick "body". We have found it to be a very good momentum indicator,
and especially smooth, because it is unaffected by gaps in price, unlike many other
momentum indicators.
We like to use this indicator as an additional trend confirmation tool, or as an
alternate trend definition tool, in place of a weekly indicator. The simplest way
of using the indicator is simply to define the trend based on which side of the "0"
line the indicator is located on. If the indicator is above "0", then the trend is up.
If the indicator is below "0" then the trend is down. You can add an additional
qualifier by noting the "slope" of the indicator, and the crossing points of the slow
and fast lines. Some like to use the slope alone to define trend direction. If the
lines are sloping upward, the trend is up. Alternately, if the lines are sloping
downward, the trend is down. In this view, the point where the lines "cross" is the
point where the trend changes.
When the ECO is below the "0" line, the trend is down, and we are qualified only to
sell on new short signals from the Hi-Lo Activator. In other words, when the ECO is
above 0, we are not allowed to take short signals, and when the ECO is below 0, we
are not allowed to take long signals.
ECO (Blau`s Ergodic Candlestick Oscillator) We call this one the ECO for short, but it will be listed on the indicator list
at W. Blau’s Ergodic Candlestick Oscillator. The ECO is a momentum indicator.
It is based on candlestick bars, and takes into account the size and direction
of the candlestick "body". We have found it to be a very good momentum indicator,
and especially smooth, because it is unaffected by gaps in price, unlike many other
momentum indicators.
We like to use this indicator as an additional trend confirmation tool, or as an
alternate trend definition tool, in place of a weekly indicator. The simplest way
of using the indicator is simply to define the trend based on which side of the "0"
line the indicator is located on. If the indicator is above "0", then the trend is up.
If the indicator is below "0" then the trend is down. You can add an additional
qualifier by noting the "slope" of the indicator, and the crossing points of the slow
and fast lines. Some like to use the slope alone to define trend direction. If the
lines are sloping upward, the trend is up. Alternately, if the lines are sloping
downward, the trend is down. In this view, the point where the lines "cross" is the
point where the trend changes.
When the ECO is below the "0" line, the trend is down, and we are qualified only to
sell on new short signals from the Hi-Lo Activator. In other words, when the ECO is
above 0, we are not allowed to take short signals, and when the ECO is below 0, we
are not allowed to take long signals.
VKM-RangeTrap-Indicator v1.1VKM-RangeTrap-Indicator v1.1 (AUDCAD M5)
Indicator Name: VKM-RangeTrap-Indicator v1.1
Recommended Timeframe: M5
Example Pair: AUDCAD
Method: VWAP-based range-reversal trading
🧭 Strategy Concept
AUDCAD is known for its narrow daily range and frequent sideways movements, especially during the Asian and early European sessions.
The VKM-RangeTrap strategy takes advantage of this characteristic by using VWAP (Volume Weighted Average Price) and its standard-deviation envelopes (Sigma) to detect temporary overbought and oversold zones.
When the price touches or breaks below the lower VWAP-Sigma band, it indicates a temporary oversold area → BUY signal.
When the price touches or breaks above the upper VWAP-Sigma band, it shows temporary overbought conditions → SELL signal.
A CCI(20) filter can be used to confirm momentum reversal (signals trigger only when CCI crosses the zero line).
⚙️ Basic Configuration
Range Method: VWAP
Sigma (Standard Deviation): 5
Sigma Length: 20
Confirmation Filter: CCI(20)
Signals: Green arrow (BUY) and red arrow (SELL) plotted directly on the chart
💡 Suggested Trading Approach
Timeframe: M5 (M3 if you want denser signals)
Entry Rules:
BUY when a green arrow appears near the VWAP-Lower support zone.
SELL when a red arrow appears near the VWAP-Upper resistance zone.
Take Profit: Use R:R ≈ 1:1.5 or an ATR-based trailing stop.
Stop Loss: Beyond the corresponding VWAP boundary or 10–20 pips away depending on volatility.
Best Conditions: Ranging or balanced markets (Asian session or early London).
📈 Performance on AUDCAD M5
AUDCAD typically moves in a stable 20–40-pip range, making it ideal for VWAP range-based trading.
The indicator performs best in sideways or mild pullback phases within larger trends.
With the CCI filter enabled, false signals are greatly reduced, resulting in steady scalping opportunities.
Suitable for day traders and scalpers aiming to profit from frequent VWAP reversals throughout the day.
⚠️ Notes
This is a range-reversal indicator, not a trend-following system.
Avoid trading during high-volatility news releases when VWAP bands expand sharply.
Can be combined with momentum indicators (ADX, WaveTrend, etc.) for stronger confirmation.
Put Option Profits inspired by Travis Wilkerson; SPX BacktesterPut Option Profits — Travis Wilkerson inspired. This tester evaluates a simple monthly SPX at-the-money credit-spread timing idea: enter on a fixed calendar rule (e.g., 1st Friday or 8th day with business-day shifting) at Open or Close, then exit exactly N calendar days later (first tradable day >= target, at Close). A trade is marked WIN if price at exit is above the entry price (1:1 risk proxy).
The book suggests forward testing 60-day and 180-day expirations to prove the concept. This tool lets you backtest both (and more) to see what actually works best. In the book, profits are taken when the spread reaches ~80% of max credit; losers are left to expire and cash-settle. This backtester does not model early profit-taking—every trade is held to the configured hold period and evaluated on price vs entry at the exit close. Think of it as a pure “set it and forget it” stress test. In live trading, you can still follow Travis’s 80% take-profit rule; TradingView just doesn’t simulate that here. Happy trading!
Features:
Schedule: Day-of-Month (with Prev/Next business-day shift, optional “stay in month”) or Nth Weekday (e.g., 1st Friday).
Entry timing: Open or Close.
Exit: N calendar days later at Close (holiday/weekend aware).
Filters: Optional EMA-200 “risk-on” filter.
Scope: Date range limiter.
Visuals: Entry/exit bubbles (paired colors) or simple win/loss dots.
Table: Overall Win% and N (within range).
Alerts: Entry alert (static condition + dynamic alert() message).
How to use:
[* ]Choose Start Mode (NthWeekday or DayOfMonth) and parameters (e.g., 1st Friday or DOM=8, PrevBizDay).
Pick Entry Timing (Open or Close).
Set Days In Trade (e.g., 150).
(Optional) Enable EMA filter and set Date Range.
Turn Bubbles on/off and/or Dots on/off.
Create alert:
Simple ping: Condition = this indicator -> Monthly Entry Signal -> “Once per bar” (Open) or “Once per bar close” (Close).
Rich message: Condition = this indicator -> Any alert() function call.
Notes:
Keep DOM shift in same month: when a DOM falls on a weekend/holiday, PrevBizDay/NextBizDay shift will stay inside the month if enabled; otherwise it can spill into the prior/next month. (Ignored for NthWeekday.)
Credits: Concept sparked by “Put Option Profits – How to turn ten minutes of free time into consistent cash flow each month” by Travis Wilkerson; this script is a neutral research tool (not financial advice).
週一普跌策略 Monday shit Strategy Strategy Description / 策略敘述
EN
This strategy takes a short position at the start of each Monday, based on the hypothesis that cryptocurrency markets tend to experience post-weekend risk-off behavior.
The system enters a full-equity short position at the Tokyo open (Taipei 08:00), aiming to capture Monday downside pressure resulting from accumulated weekend information and macro sentiment adjustments when traditional financial markets reopen.
Risk management uses fixed percentage take-profit and stop-loss levels, emphasizing asymmetric reward-to-risk (large occasional gains, small frequent losses).
The model reflects the increasing alignment between crypto price behavior and traditional financial market cycles.
ZH-TW
本策略於每週一開盤時做空，基於假設加密資產在週末後具有風險釋放與補跌傾向。
系統會在台北時間早上 08:00 以全倉做空，目標捕捉因週末累積消息與傳統金融市場重新開盤所造成的下跌壓力。
風控採固定止盈、止損百分比，強調高報酬／低風險的不對稱結構（小虧多次、偶爾大賺）。
此模型反映加密貨幣市場行為與華爾街週期愈趨一致的市場現象。
NEXT GEN INSPIRED BY OLIVER VELEZDYOR NFA
1. Initial Setup & Application
Load the Strategy to your desired chart (e.g., EURUSD M5, as suggested by the script's backtest).
Overlay: Ensure the script is set to overlay=true (which it is) so the signals and Moving Averages plot directly on the price chart.
Equity Management: Review the initial strategy settings for capital and position sizing:
Initial Capital: Defaults to 10,000.
Default Qty Type: Set to strategy.percent_of_equity (22%), meaning 22% of your available equity is used per trade. Adjust this percentage based on your personal risk tolerance.
2. Reviewing Key Indicator Inputs
The script uses default values that are optimized, but you can adjust them in the settings panel:
Fast EMA: Defaults to 9 (e.g., a 9-period Exponential Moving Average).
Slow EMA: Defaults to 21 (e.g., a 21-period Exponential Moving Average). These EMAs define the short-term trend.
ATR: Defaults to 14 (Average True Range). Used to dynamically calculate volatility for SL/TP distances.
Final R:R: Defaults to 4.5 (minimum R:R required for a signal). This is the core of the strategy's high reward goal.
3. Interpreting Entry Signals
A trade signal is generated only when all conditions—EMA trend, "Elephant Logic" momentum, and non-ranging market—are met.
Long Signal: Appears as a green triangle (▲) below the bar, labeled "COMBO".
Short Signal: Appears as a red triangle (▼) above the bar, labeled "COMBO".
Live Plan: Upon signal, a detailed label is immediately plotted on the chart showing the FULL BATTLE PLAN:
SL: Calculated Stop Loss price.
TP: Calculated Take Profit price (based on the Final R:R).
Risk/Reward Pips: The calculated pips for the trade's risk and reward.
R:R = 1:4.5: The exact Risk-to-Reward ratio.
4. Understanding Market Conditions & Visuals
The script provides visuals to help you understand the current market state:
Trend EMAs: The 9 EMA (green) and 21 EMA (purple/magenta) are plotted to show the underlying trend.
Long trades only fire when Price > 9 EMA > 21 EMA.
Short trades only fire when Price < 9 EMA < 21 EMA.
Ranging Market (Rejection): Bars turn a light gray/silver when the proprietary "Reject Ranging" logic is active, indicating a low-volatility period. No new trades will be taken during these bars.
Momentum Bar: Bars turn a gold/yellow color when the "Elephant Logic" (high-momentum, large-body candles over 2-3 periods) is detected, highlighting powerful price movement.
5. Execution and Exit Logic
The strategy handles entry, scaling, and exit automatically:
Entry: A market order is placed (strategy.entry) immediately upon the bar where the longSetup or shortSetup condition is met.
Scaling Out (+1R): If the trade moves favorably by an amount equal to the initial risk (1R), the script closes a portion of the position (strategy.close with comment "+1R"). This partial exit locks in profit equivalent to the initial risk.
Re-entry (Pyramiding): After the +1R exit, the strategy attempts a re-entry (LONG RE/SHORT RE diamond plot) if the price meets certain criteria near the 9 EMA, trying to capitalize on further trend continuation.
Final Exits:
Take Profit: A limit order is set at the calculated TP level (stopDist * minRR).
Stop Loss: A stop order is set at the calculated SL level (stopDist * 1.3), slightly wider than the initial SL distance, likely to account for spread/slippage, ensuring the maximum loss is defined.
Trailing Stop: A trailing stop is applied to the re-entry positions (LONG RE/SHORT RE) to protect profits as the market moves further in the direction of the trade.
Confirmed Momentum QQQ (RSI/MACD Filter)Gemini and Myself,
How This Targets a Higher Win Rate
The key to the win rate increase is the RSI 20/80 filter.
Long Signal: A long entry is now only taken if the trend is up (SMA cross), the MACD is bullish, and the RSI is not overbought (below 80). By only entering when momentum is not yet exhausted, you increase the chance that the price can travel far enough to hit your 4.0 point Take Profit.
Wider SL: The wider Stop Loss of 2.5 points reduces the chance of being stopped out prematurely by routine market movements (whipsaws), which is the number one killer of win rates in high-frequency trading.
After applying these changes, you will need to run the Strategy Tester again to see the new win rate and the new total number of trades.
Would you like me to help you interpret the new Strategy Tester results once you apply these settings?
PSAR with ATR Trailing Stop + SMA Filter📈 Strategy Overview: PSAR + 6×ATR Trailing Stop with SMA Filter
This strategy is built around the principle of “Cut the losers, let the winners run” — a disciplined, trend-following approach that combines the Parabolic SAR indicator with dynamic risk management and a Simple Moving Average (SMA) trend filter.
🔍 Strategy Logic
Trend Filter Trades are only taken in the direction of the prevailing trend, defined by a user-selected SMA (default: 100).
✅ Long trades only when price is above the SMA
✅ Short trades only when price is below the SMA
Entry Signal: A trade is triggered when the Parabolic SAR flips to the opposite side of the price bars, signaling a potential trend reversal.
Stop Loss: The stop loss is dynamically set at 6×ATR from the entry price. This adapts to market volatility and is recalculated every bar — effectively acting as a trailing stop.
Exit Logic: There is no fixed take profit. The trade remains open until the trailing stop is hit — allowing winners to run and losers to be cut quickly.
Risk Management: Each trade risks 0.5% of total equity, ensuring consistent position sizing and capital preservation.
📊 Visual Elements
PSAR dots mark trend direction changes
SMA line shows the broader trend filter
Trailing stop crosses (with 50% opacity) indicate the current stop level without cluttering the chart
⚙️ Customizable Inputs
PSAR parameters: Start, Increment, Maximum
ATR length and multiplier
SMA length
Risk percentage per trade
This strategy is ideal for traders who want to stay aligned with the trend, automate disciplined exits, and avoid emotional decision-making. Clean, simple, and powerful.
Wishing you calm and successful trades!
Enhanced MA Crossover Pro📝 Strategy Summary: Enhanced MA Crossover Pro
This strategy is an advanced, highly configurable moving average (MA) crossover system designed for algorithmic trading. It uses the crossover of two customizable MAs (a "Fast" MA 1 and a "Slow" MA 2) as its core entry signal, but aggressively integrates multiple technical filters, time controls, and dynamic position management to create a robust and comprehensive trading system.
💡 Core Logic
Entry Signal: A bullish crossover (MA1 > MA2) generates a Long signal, and a bearish crossover (MA1 < MA2) generates a Short signal. Users can opt to use MA crossovers from a Higher Timeframe (HTF) for the entry signal.
Confirmation/Filters: The basic MA cross signal is filtered by several optional indicators (see Filters section below) to ensure trades align with a broader trend or momentum context.
Position Management: Trades are managed with a sophisticated system of Stop Loss, Take Profit, Trailing Stops, and Breakeven stops that can be fixed, ATR-based, or dynamically adjusted.
Risk Management: Daily limits are enforced for maximum profit/loss and maximum trades per day.
⚙️ Key Features and Customization
1. Moving Averages
Primary MAs (MA1 & MA2): Highly configurable lengths (default 8 & 20) and types: EMA, WMA, SMA, or SMMA/RMA.
Higher Timeframe (HTF) MAs: Optional MAs calculated on a user-defined resolution (e.g., "60" for 1-hour) for use as an entry signal or as a trend confirmation filter.
2. Multi-Filter System
The entry signal can be filtered by the following optional conditions:
SMA Filter: Price must be above a 200-period SMA for long trades, and below it for short trades.
VWAP Filter: Price must be above VWAP for long trades, and below it for short trades.
RSI Filter: Long trades are blocked if RSI is overbought (default 70); short trades are blocked if RSI is oversold (default 30).
MACD Filter: Requires the MACD Line to be above the Signal Line for long trades (and vice versa for short trades).
HTF Confirmation: Requires the HTF MA1 to be above HTF MA2 for long entries (and vice versa).
3. Dynamic Stop and Target Management (S/L & T/P)
The strategy provides extensive control over exits:
Stop Loss Methods:
Fixed: Fixed tick amount.
ATR: Based on a multiple of the Average True Range (ATR).
Capped ATR: ATR stop limited by a maximum fixed tick amount.
Exit on Close Cross MA: Position is closed if the price crosses back over the chosen MA (MA1 or MA2).
Breakeven Stop: A stop can be moved to the entry price once a trigger distance (fixed ticks or Adaptive Breakeven based on ATR%) is reached.
Trailing Stop: Can be fixed or ATR-based, with an optional feature to auto-tighten the trailing multiplier after the breakeven condition is met.
Profit Target: Can be a fixed tick amount or a dynamic target based on an ATR multiplier.
4. Time and Session Control
Trading Session: Trades are only taken between defined Start/End Hours and Minutes (e.g., 9:30 to 16:00).
Forced Close: All open positions are closed near the end of the session (e.g., 15:45).
Trading Days: Allows specific days of the week to be enabled or disabled for trading.
5. Risk and Position Limits
Daily Profit/Loss Limits: The strategy tracks daily realized and unrealized PnL in ticks and will close all positions and block new entries if the user-defined maximum profit or maximum loss is hit.
Max Trades Per Day: Limits the number of executed trades in a single day.
🎨 Outputs and Alerts
Plots: Plots the MA1, MA2, SMA, VWAP, and HTF MAs (if enabled) on the chart.
Shapes: Plots visual markers (BUY/SELL labels) on the bar where the MA crossover occurs.
Trailing Stop: Plots the dynamic trailing stop level when a position is open.
Alerts: Generates JSON-formatted alerts for entry ({"action":"buy", "price":...}) and exit ({"action":"exit", "position":"long", "price":...}).
Buy And Hold Performance Screener - [JTCAPITAL]Buy And Hold Performance Screener – is a script designed to track and display multi-asset “buy and hold” performance curves and performance statistics over defined timeframes for selected symbols. It doesn’t attempt to time entries or exits; rather, it shows what would happen if one simply bought the asset at the defined start date and held it.
The indicator works by calculating in the following steps:
Start Date Definition
The script begins by reading an input for the start date. This defines the bar from which the equity curves begin.
Symbol Definitions & Close Price Retrieval
The script allows the user to specify up to ten tickers. For each ticker it uses request.security() on the “1D” timeframe to retrieve the daily close price of that symbol.
Plot Enable Inputs
For each ticker there is an input boolean controlling whether the equity curve for that ticker should be plotted.
Asset Name Cleaning
The helper function clean_name(string asset) => … takes the asset string (e.g., “CRYPTO:SOLUSD”) and manipulates it (via string splitting and replacements) to derive a cleaned short name (e.g., “SOL”). This name is used for visuals (labels, table headers).
Equity Curve Calculation (“HODL”)
The helper function f_HODL(closez) defines a variable equity that assumes a starting equity of 1 unit at the start date and then multiplies by the ratio of each bar’s close to the prior bar’s close: i.e. daily compounding of returns.
Performance Metrics Calculation
The helper function f_performance(closez) calculates, for each symbol’s close series, the percentage change of the current close relative to its close 30 days ago, 90 days ago, 180 days ago, 1 year ago (365 days), 2 years ago (730 days) and 3 years ago (1095 days).
Equity Curve Plots
For each ticker, if the corresponding plot input is true, the script assigns a plotted variable equal to the equity curve value. Its then drawing each selected equity curve on the chart, each in a distinct color.
Table Construction
If the plottable input is true, the script constructs a table and populates it with rows and column corresponding to the assigned tickers and the set 6 timeframes used for display.
Buy and Sell Conditions:
Since this is strictly a “buy-and-hold” performance screener, there are no explicit buy or sell signals generated or plotted. The script assumes: buy at the defined start_date, hold continuously to present. There are no filters, no exit logic, no take-profit or stop-loss. The benefit of this approach is to provide a clean benchmark of how selected assets would have performed if one simply adopted a passive “buy & hold” approach from a given start date.
Features and Parameters:
start_date (input.time) : Defines the date from which performance and equity curves begin.
ticker1 … ticker10 (input.symbol) : User-selectable asset symbols to include in the screener.
plot1 … plot10 (input.bool) : Boolean flags to enable/disable plotting of each asset’s equity curve.
plottable (input.bool) : Flag to enable/disable drawing the performance table.
Colored plotting + Labels for identifying each asset curve on the chart.
Specifications:
Here is a detailed breakdown of every calculation/variable/function used in the script and what each part means:
start_date
This is defined via input.time(timestamp("1 Jan 2025"), title = "Start Date"). It allows the user to pick a specific calendar date from which the equity curves and performance calculations will start.
ticker1 … ticker10
These inputs allow the user to select up to ten different assets (symbols) to monitor. The script uses each of these to fetch daily close prices.
plot1 … plot10
Boolean inputs controlling which of the ten asset equity curves are plotted. If plotX is true, the equity curve for ticker X will be visible; otherwise it will be not plotted. This gives the user flexibility to include or exclude specific assets on the chart.
Returns the cleaned asset short name.
This provides friendly text labels like “BTC”, “ETH”, “SOL”, etc., instead of full symbol codes.
The choice of distinct colours for each asset helps differentiate curves visually when multiple assets are overlaid.
Colour definitions
Variables color1…color10 are explicitly defined via color.rgb(r,g,b) to give each asset a unique colour (e.g., red, orange, yellow, green, cyan, blue, purple, pink, etc.).
What are the benefits of combining these calculations?
By computing equity curves for multiple assets from the same start date and overlaying them, you can visualise comparative performance of different assets under a uniform “buy & hold” assumption.
The performance table adds multi-horizon returns (30 D, 90 D, 180 D, 1 Y, 2 Y, 3 Y) which helps the user see both short-term and longer-term performance without having to manually compute returns.
The use of daily close data via request.security(..., "1D") removes dependency on the chart’s timeframe, thereby standardising the comparison across assets.
The equity curve and table together provide both visual (curve) and numerical (table) summaries of performance, making it easier to spot trends, divergences, and cross-asset comparisons at a glance.
Because it uses compounding (equity := equity * (closez / closez )), the curves reflect the real growth of a 1-unit investment held over time, rather than only simple returns.
The labelling of curves and the color-coding make the multi-asset overlay easier to interpret.
Using a clean start date ensures that all curves begin at the same point (1 unit at start_date), making relative performance intuitive.
Because of this, the script is useful as a benchmarking tool: rather than trying to pick entries or exit points, you can simply compare “what if I had held these assets since Jan 1 2025” (or your chosen date), and see which assets out-/under-performed in that period. It helps an investor or trader evaluate the long-term benefits of passive vs. active management, or of allocation decisions.
Please note:
The script assumes continuous daily data and does not account for dividends, fees, slippage, or tax implications.
It does not attempt to optimise timing or provide trading signals.
Returns prior to the start date are ignored (equity only begins once time >= start_date).
For newly listed assets with fewer than 365 or 730 or 1095 days of history, the longer-horizon returns may return na or misleading values.
Because it uses request.security() without specifying lookahead, and on “1D” timeframe, it complies with standard usage but you should verify there is no look-ahead bias in your particular setup.
ENJOY!
Dual Table Dashboard - Correct V3add RSI Data## 📈 Trading Applications
### 1. Trend Following Strategy
```
1. Check TABLE 1 for trend direction (AnEMA29 + PDMDR)
2. If both green → Look for longs
3. If both red → Look for shorts
4. Use TABLE 2 for entry levels
```
### 2. Support/Resistance Strategy
```
@70 levels = Resistance (sell/take profit zones)
@50 levels = Pivot (breakout levels)
@30 levels = Support (buy/accumulation zones)
```
### 3. Multi-Timeframe Alignment
```
W_RSI → Weekly bias (long-term)
D_RSI → Daily bias (medium-term)
Sto50 → Current position (swing)
Sto12 → Immediate position (day trade)
RSI(7) & RSI(3) → Entry timing (scalp)
```
### 4. Color Scanning Method
**Quick visual analysis:**
- Count greens vs reds in each row
- More greens = Bullish position
- More reds = Bearish position
- Mixed colors = Transitioning/choppy
---
## ✅ Verification & Accuracy
### Tested Against AmiBroker:
- ✅ RSI band values match within ±0.01%
- ✅ Stochastic channels match exactly
- ✅ Color logic matches exactly
- ✅ All formulas verified line-by-line
### Known Minor Differences:
Small variations (<1%) may occur due to:
1. **Platform calculation precision** - Different floating-point engines
2. **Historical data feeds** - Slight variations in past prices
3. **Weekly bar boundaries** - TradingView vs AmiBroker week definitions
4. **Initialization period** - First N bars need to "warm up"
**These minor differences don't affect trading signals!**
---
## ⚙️ Settings & Customization
### Input Parameters:
```pine
emaLen = 29 // EMA Length for angle calculation
rangePeriods = 30 // Angle normalization lookback
rangeConst = 25 // Angle normalization constant
dmiLen = 14 // DMI/ADX Length for PDMDR
```
### Available Positions:
Can be changed in the code:
- `position.top_left`
- `position.top_center`
- `position.top_right`
- `position.middle_left` (Table 2 default)
- `position.middle_center`
- `position.middle_right`
- `position.bottom_left` (Table 1 default)
- `position.bottom_center`
- `position.bottom_right`
### Text Sizes:
- `size.tiny`
- `size.small` (current default)
- `size.normal`
- `size.large`
- `size.huge`
---
## 🎯 Best Practices
### DO:
✅ Use multiple confirmations before entering trades
✅ Combine with price action and chart patterns
✅ Pay attention to color changes across timeframes
✅ Use @50 levels as key pivot points
✅ Watch for alignment between W_RSI and D_RSI
### DON'T:
❌ Trade based on color alone without confirmation
❌ Ignore the overall trend (Table 1)
❌ Enter trades against strong trend signals
❌ Overtrade when colors are mixed/choppy
❌ Ignore risk management rules
---
## 📊 Example Reading
### Bullish Setup:
```
TABLE 1:
AnEMA29: Green (15°) across all 3 bars
PDMDR: Green (1.65) and rising
TABLE 2:
W_RSI@50: Green (price above)
D_RSI@50: Green (price above)
Sto50@50: Green (price above midpoint)
Sto12@50: Green (price above midpoint)
Interpretation: Strong bullish trend confirmed across multiple timeframes
Action: Look for long entries on pullbacks to @50 or @30 levels
```
### Bearish Setup:
```
TABLE 1:
AnEMA29: Red (-12°) across all 3 bars
PDMDR: Red (0.45) and falling
TABLE 2:
W_RSI@50: Red (price below)
D_RSI@50: Red (price below)
Sto50@50: Red (price below midpoint)
Interpretation: Strong bearish trend confirmed
Action: Look for short entries on rallies to @50 or @70 levels
```
### Reversal Signal:
```
TABLE 1:
-2D: Red, -1D: Yellow, 0D: Green (momentum shifting)
TABLE 2:
Price just crossed above multiple @50 levels
Colors changing from red to green
Interpretation: Potential trend reversal in progress
Action: Wait for confirmation, consider early long entry with tight stop
```
---
## 🔍 Troubleshooting
### "Values don't match AmiBroker exactly"
- Check you're on the same timeframe
- Verify the symbol is identical
- Compare historical data (last 20 closes)
- Small differences (<1%) are normal
### "Tables are overlapping"
- Adjust positions in code
- Use different combinations (top/middle/bottom with left/center/right)
### "Colors seem wrong"
- Verify current close price
- Check if you're comparing same bar
- Ensure both platforms use same session times
### "Script takes too long"
- Use on Daily or higher timeframes
- The RSI band calculation is computationally intensive
- Don't run on tick-by-tick data
---
## 📝 Version History
**v3.0 (Final)** - Current version
- RSI band calculation verified correct
- Tables positioned bottom-left and middle-left
- All values match AmiBroker
- Production ready ✅
**v2.0**
- Fixed RSI band algorithm order (calculate before updating P/N)
- Improved variable scope handling
**v1.0**
- Initial implementation
- Had incorrect RSI band calculation
---
## 📄 Files in Package
Nifty 50 Weighted Volume IndicatorThis takes the volume of the cash market as per the composite weighted average of the Nifty 50 Components.
You can use this at your discretion to take calls on Index trades.
Multi Timeframe Market Structure ContinuationOverview
This indicator identifies Break of Structure (BOS) and Change of Character (ChoCh) patterns using multi-timeframe (MTF) analysis to filter high-probability trade setups. By aligning lower timeframe signals with higher timeframe bias, it helps traders enter positions in the direction of the dominant trend while avoiding counter-trend traps.
Multi-Timeframe Analysis
The indicator analyzes market structure on two timeframes simultaneously:
Current Timeframe (CTF): Detects immediate BOS and ChoCh signals for entry timing
Higher Timeframe (HTF): Establishes the overall trend direction (default: 1H, customizable)
Signals only appear when the current timeframe structure aligns with the higher timeframe bias, ensuring you're trading with the momentum, not against it.
Break of Structure (BOS)
BOS signals indicate trend continuation - when price breaks a previous high in an uptrend or a previous low in a downtrend. These are reliable entries that confirm the trend is still active and strong.
Change of Character (ChoCh)
ChoCh signals mark early trend reversals - when market structure shifts from bearish to bullish (or vice versa). When captured in alignment with the higher timeframe trend, ChoCh entries can achieve exceptional risk-to-reward ratios as they allow entry near the beginning of a new impulse move.
Exit Signals
Exit signals are plotted when a ChoCh occurs in the opposite direction of the HTF trend. For example, if the HTF is bullish and a bearish ChoCh forms on the current timeframe, an orange "EXIT" signal appears - warning long traders that the lower timeframe structure is shifting against them. This provides an early warning system to protect profits or minimize losses before the HTF trend itself reverses.
Trading Strategy Recommendations
Trending Markets (Recommended)
In strong trending conditions, both BOS and ChoCh signals can be taken when aligned with the HTF bias. ChoCh entries are particularly powerful as they catch early reversals within the larger trend, offering entries with tight stop losses and extended profit targets.
Ranging Markets
During consolidation or choppy conditions, it's best to be selective and take only BOS entries. BOS signals confirm that the trend is continuing beyond the range, reducing false breakouts and whipsaw trades that are common with counter-trend ChoCh signals in sideways markets.
Customization
Pivot Length: Adjust the sensitivity of structure detection (default: 5). Lower values detect structure more frequently with earlier but potentially noisier signals. Higher values provide cleaner, more significant structural breaks but with some delay.
Higher Timeframe: Customize the HTF to suit your trading style. Day traders might use 1H HTF on 5m charts, while swing traders could use 4H or Daily HTF.
Alert System
Six alert conditions available:
Long BOS Entry / Long ChoCh Entry
Short BOS Entry / Short ChoCh Entry
Long Exit / Short Exit
All alerts fire only on confirmed candle closes to eliminate repainting and false signals.
Visual Features
Color-coded background showing HTF bias
Clear BOS/ChoCh labels with horizontal lines at structure levels
Orange "EXIT" signals when structure breaks against your position
Gray lines tracking current swing highs/lows
HTF trend indicator in the top-right corner
Liquidity Sweeps 2nd attemptLiquidity Sweeps 2nd attempt
The Liquidity Sweeps indicator detects the presence of liquidity sweeps on the user's chart, while also providing potential areas of support/resistance or entry when Liquidity levels are taken.
In the event of a Liquidity Sweep a Sweep Area is created which may provide further areas of interest.
Larry Williams Oops StrategyThis strategy is a modern take on Larry Williams’ classic Oops setup. It trades intraday while referencing daily bars to detect opening gaps and align entries with the prior day’s direction. Risk is managed with day-based stops, and—unlike the original—all positions are closed at the end of the session (or at the last bar’s close), not at a fixed profit target or the first profitable open.
Entry Rules
Long setup (bullish reversion): Today opens below yesterday’s low (down gap) and yesterday’s candle was bearish. Place a buy stop at yesterday’s low + Filter (ticks).
Short setup (bearish reversion): Today opens above yesterday’s high (up gap) and yesterday’s candle was bullish. Place a sell stop at yesterday’s high − Filter (ticks).
Longs are only taken on down-gap days; shorts only on up-gap days.
Protective Stop
If long, stop loss trails the current day’s low.
If short, stop loss trails the current day’s high.
Exit Logic
Positions are force-closed at the end of the session (in the last bar), ensuring no overnight exposure. There is no take-profit; only stop loss or end-of-day flat.
Notes
This strategy is designed for intraday charts (minutes/seconds) using daily data for gaps and prior-day direction.
Longs/shorts can be enabled or disabled independently.
Session Gap Fill [LuxAlgo]The Session Gap Fill tool detects and highlights filled and unfilled price gaps between regular sessions. It features a dashboard with key statistics about the detected gaps.
The tool is highly customizable, allowing users to filter by different types of gaps and customize how they are displayed on the chart.
🔶 USAGE
By default, the tool detects all price gaps between sessions. A price gap is defined as a difference between the opening price of one session and the closing price of the previous session. In this case, the tool uses the opening price of the first bar of the session against the closing price of the previous bar.
A bullish gap is detected when the session open price is higher than the last close, and a bearish gap is detected when the session open price is lower than the last close.
Gaps represent a change in market sentiment, a difference in what market participants think between the close of one trading session and the open of the next.
What is useful to traders is not the gap itself, but how the market reacts to it.
Unfilled gaps occur when prices do not return to the previous session's closing price.
Filled gaps occur when prices come back to the previous session's close price.
By analyzing how markets react to gaps, traders can understand market sentiment, whether different prices are accepted or rejected, and take advantage of this information to position themselves in favor of bullish or bearish market sentiment.
Next, we will cover the Gap Type Filter and Statistics Dashboard.
🔹 Gap Type Filter
Traders can choose from three options: display all gaps, display only overlapping gaps, or display only non-overlapping gaps. All gaps are displayed by default.
An overlapping gap is defined when the first bar of the session has any price in common with the previous bar. No overlapping gap is defined when the two bars do not share any price levels.
As we will see in the next section, there are clear differences in market behavior around these types of gaps.
🔹 Statistics Dashboard
The Statistics Dashboard displays key metrics that help traders understand market behavior around each type of gap.
Gaps: The percentage of bullish and bearish gaps.
Filled: The percentage of filled bullish and bearish gaps.
Reversed: The percentage of filled gaps that move in favor of the gap
Bars Avg.: The average number of bars for a gap to be filled.
Now, let's analyze the chart on the left of the image to understand those stats. These are the stats for all gaps, both overlapping and non-overlapping.
Of the total, bullish gaps represent 55%, and bearish ones represent 44%. The gap bias is pretty balanced in this market.
The second statistic, Filled, shows that 63% of gaps are filled, both bullish and bearish. Therefore, there is a higher probability that a gap will be filled than not.
The third statistic is reversed. This is the percentage of filled gaps where prices move in favor of the gap. This applies to filled bullish gaps when the close of the session is above the open, and to filled bearish gaps when the close of the session is below the open. In other words, first there is a gap, then it fills, and finally it reverses. As we can see in the chart, this only happens 35% of the time for bullish gaps and 29% of the time for bearish gaps.
The last statistic is Bars Avg., which is the average number of bars for a gap to be filled. On average, it takes between one and two bars for both bullish and bearish gaps. On average, gaps fill quickly.
As we can see on the chart, selecting different types of gaps yields different statistics and market behavior. For example, overlapping gaps have a greater than 90% chance of being filled, whereas non-overlapping gaps have a less than 40% chance.
🔶 SETTINGS
Gap Type: Select the type of gap to display.
🔹 Dashboard
Dashboard: Enable or disable the dashboard.
Position: Select the location of the dashboard.
Size: Select the dashboard size.
🔹 Style
Filled Bullish Gap: Enable or disable this gap and choose the color.
Filled Bearish Gap: Enable or disable this gap and choose the color.
Unfilled Gap: Enable or disable this gap and choose the color.
Max Deviation Level: Enable or disable this level and choose the color.
Open Price Level: Enable or disable this level and choose the color.
First Passage Time - Distribution AnalysisThe First Passage Time (FPT) Distribution Analysis indicator is a sophisticated probabilistic tool that answers one of the most critical questions in trading: "How long will it take for price to reach my target, and what are the odds of getting there first?"
Unlike traditional technical indicators that focus on what might happen, this indicator tells you when it's likely to happen.
Mathematical Foundation: First Passage Time Theory
What is First Passage Time?
First Passage Time (FPT) is a concept in stochastic processes that measures the time it takes for a random process to reach a specific threshold for the first time. Originally developed in physics and mathematics, FPT has applications in:
Quantitative Finance: Option pricing, risk management, and algorithmic trading
Neuroscience: Modeling neural firing patterns
Biology: Population dynamics and disease spread
Engineering: Reliability analysis and failure prediction
The Mathematics Behind It
This indicator uses Geometric Brownian Motion (GBM), the same stochastic model used in the Black-Scholes option pricing formula:
dS = μS dt + σS dW
Where:
S = Asset price
μ = Drift (trend component)
σ = Volatility (uncertainty component)
dW = Wiener process (random walk)
Through Monte Carlo simulation, the indicator runs 1,000+ price path simulations to statistically determine:
When each threshold (+X% or -X%) is likely to be hit
Which threshold is hit first (directional bias)
How often each scenario occurs (probability distribution)
🎯 How This Indicator Works
Core Algorithm Workflow:
Calculate Historical Statistics
Measures recent price volatility (standard deviation of log returns)
Calculates drift (average directional movement)
Annualizes these metrics for meaningful comparison
Run Monte Carlo Simulations
Generates 1,000+ random price paths based on historical behavior
Tracks when each path hits the upside (+X%) or downside (-X%) threshold
Records which threshold was hit first in each simulation
Aggregate Statistical Results
Calculates percentile distributions (10th, 25th, 50th, 75th, 90th)
Computes "first hit" probabilities (upside vs downside)
Determines average and median time-to-target
Visual Representation
Displays thresholds as horizontal lines
Shows gradient risk zones (purple-to-blue)
Provides comprehensive statistics table
📈 Use Cases
1. Options Trading
Selling Options: Determine if your strike price is likely to be hit before expiration
Buying Options: Estimate probability of reaching profit targets within your time window
Time Decay Management: Compare expected time-to-target vs theta decay
Example: You're considering selling a 30-day call option 5% out of the money. The indicator shows there's a 72% chance price hits +5% within 12 days. This tells you the trade has high assignment risk.
2. Swing Trading
Entry Timing: Wait for higher probability setups when directional bias is strong
Target Setting: Use median time-to-target to set realistic profit expectations
Stop Loss Placement: Understand probability of hitting your stop before target
Example: The indicator shows 85% upside probability with median time of 3.2 days. You can confidently enter long positions with appropriate position sizing.
3. Risk Management
Position Sizing: Larger positions when probability heavily favors one direction
Portfolio Allocation: Reduce exposure when probabilities are near 50/50 (high uncertainty)
Hedge Timing: Know when to add protective positions based on downside probability
Example: Indicator shows 55% upside vs 45% downside—nearly neutral. This signals high uncertainty, suggesting reduced position size or wait for better setup.
4. Market Regime Detection
Trending Markets: High directional bias (70%+ one direction)
Range-bound Markets: Balanced probabilities (45-55% both directions)
Volatility Regimes: Compare actual vs theoretical minimum time
Example: Consistent 90%+ bullish bias across multiple timeframes confirms strong uptrend—stay long and avoid counter-trend trades.
First Hit Rate (Most Important!)
Shows which threshold is likely to be hit FIRST:
Upside %: Probability of hitting upside target before downside
Downside %: Probability of hitting downside target before upside
These always sum to 100%
⚠️ Warning: If you see "Low Hit Rate" warning, increase this parameter!
Advanced Parameters
Drift Mode
Allows you to explore different scenarios:
Historical: Uses actual recent trend (default—most realistic)
Zero (Neutral): Assumes no trend, only volatility (symmetric probabilities)
50% Reduced: Dampens trend effect (conservative scenario)
Use Case: Switch to "Zero (Neutral)" to see what happens in a pure volatility environment, useful for range-bound markets.
Distribution Type
Percentile: Shows 10%, 25%, 50%, 75%, 90% levels (recommended for most users)
Sigma: Shows standard deviation levels (1σ, 2σ)—useful for statistical analysis
⚠️ Important Limitations & Best Practices
Limitations
Assumes GBM: Real markets have fat tails, jumps, and regime changes not captured by GBM
Historical Parameters: Uses recent volatility/drift—may not predict regime shifts
No Fundamental Events: Cannot predict earnings, news, or macro shocks
Computational: Runs only on last bar—doesn't give historical signals
Remember: Probabilities are not certainties. Use this indicator as part of a comprehensive trading plan with proper risk management.
Created by: Henrique Centieiro. feedback is more than welcome!
Micro SuiteWhat it is: One Pine v5 indicator that stacks several tools: EMA ribbon + a color-flipping 11/34 EMA trend line, multi-timeframe RSI pressure arrows, and a Bollinger Band re-entry system that marks Top/Bottom triggers (T/B) and later “r” confirmations. It also sprinkles in 3-Line Strike, Leledc exhaustion dots, and a small “Micro Dots” engine (ATR regime + VMA filter). Alerts for all of it.
TradingView
The core signals you’ll actually use:
RSI arrows: Up arrow when current RSI(6) < 30 and selected higher-TF RSIs are also < 30; down arrow when > 70 cluster cools. Idea = stacked OB/OS “pressure.”
TradingView
Bollinger re-entry (T/B + r):
T = first close back inside upper band; B = first close back inside lower band.
r = confirmation within N bars (price takes out the trigger bar’s high/low). These bars tint so they’re easy to see.
TradingView
Trend filter: EMA-11 vs EMA-34 color flip + optional VMA trend line; helps you ignore counter-trend stabs.
TradingView
Quick playbook (how to read it):
Reversal short: See a T near the top band → get the r within your window → bonus if a down RSI arrow or a Leledc high dot shows up.
Reversal long: Mirror that with B → r, plus an up RSI arrow/Leledc low dot.
Continuation: If Micro Dot stays green (or red) and 11>34 EMA holds, ignore isolated T/B traps.
TradingView
Inputs that matter:
confirmBars for the T/B “r” window.
Which higher-TF RSIs must agree for arrows.
Show/hide and lengths for EMAs and BB.
Micro block: show dots, VMA line, and speed (Fast/Med/Slow).
TradingView
Why people like it: You get trend, momentum, and mean-revert cues on one pane with ready-made alerts, so it’s easier to build a ruleset (e.g., “only take B→r longs when 11>34 and there’s an RSI up arrow”).
TradingView
Caveats: It’s still just TA—OB/OS clusters can persist in trends; confirmations can miss V-shaped turns; and stacking signals can be late in fast markets. Pair it with risk rules (fixed R, ATR stops) and a higher-TF bias.
One-liner cheat sheet:
Longs: B → r + RSI up arrow + 11>34 (optional Micro Dot green).
Shorts: T → r + RSI down arrow + 11<34 (optional Micro Dot red).
TradingView
