Triple High Price Volume Breakout Strategy
This strategy judges if price and volume make triple higher highs near market close to predict next day gap opportunities. It aims to capitalize on short-term patterns. Strategy Logic: 1. Check if latest 3 bars make…
This strategy judges if price and volume make triple higher highs near market close to predict next day gap opportunities. It aims to capitalize on short-term patterns.
Strategy Logic:
Check if latest 3 bars make triple higher highs in price.
Check if latest 3 bars show increasing volume.
Check if latest 3 bars all closed higher than open.
If above conditions met near market close, predict possible gap next day.
Take highly leveraged positions to profit from gap open.
Advantages:
Triple high price/volume improves accuracy.
Trading in critical periods maximizes profit potential.
Fixed profit-taking avoids decision difficulties.
Risks:
Prediction relies simply on candle patterns, prone to reversals and traps.
Extremely high leverage entails huge risk, requiring prudent management.
Unable to limit loss size, potentially large drawdowns.
In summary, this strategy attempts to predict next day moves based on end-of-day patterns, providing high probability leveraged profit opportunities balanced with clear loss risks. But extreme caution remains essential.
Source Pine Script
/*backtest
start: 2023-08-13 00:00:00
end: 2023-09-12 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © SharemarketRaja
//@version=4
//Scanner available
strategy("3 Higher High Price & Vol", overlay=true)
volma = sma(volume, 20)
PriceHH = high > high[1] and high[1] > high[2]
VolHH = volume > volume[1] and volume[1] > volume[2]
Volma = volume > volma and volume[1] > volma[1] and volume[2] > volma[2]
Allgreen = close > open and close[1] > open[1] and close[2] > open[2]
PriceLL = low < low[1] and low[1] < low[2]
Allred = close < open and close[1] < open[1] and close[2] < open[2]
Qty = 100
Buy = (PriceHH == true and VolHH == true and Volma == true and Allgreen == true) and time("15", "1515-1530")
Reversal = (PriceLL == true and VolHH == true and Volma == true and Allred == true) and time("15", "1515-1530")
plotshape(Buy, style=shape.arrowup, size=size.large, color=color.green, location=location.belowbar)
plotshape(Reversal, style=shape.arrowup, size=size.large, color=color.red, location=location.belowbar)
strategy.entry(id="L", long=true, when=Buy)
strategy.entry(id="R", long=true, when=Reversal)
// strategy.exit(id="LE", from_entry="L", profit=Profit, loss=Loss)
// strategy.close_all(when=(time("15", "1500-1515")) )Published by ChaoZhang on the FMZ strategy square · last modified 2023-09-13. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.
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A spec is not a trading system. Paste this into your coding agent and AgenKit runs a specialist team — architecture, test-first build, risk gates, review — with paper trading on by default.
/agenkit build a production-grade trading bot with a backtest engine, risk controls and paper trading by default from strategies/Triple-High-Price-Volume-Breakout-Strategy.md- npx agenkit install engineering-kit in your project
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Understand it first
Before you run this, read the lesson behind the idea and how to backtest it honestly. Specs like this one are the survivors of an unknown number of trials; deflate their results accordingly.
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