Renko Yin Yang Quant Trading Strategy
The Renko Yin Yang quant trading strategy is a short-term trading strategy based on intraday price-volume relationship. It utilizes the yin yang direction information within a day and combines volume confirmation…
Overview
The Renko Yin Yang quant trading strategy is a short-term trading strategy based on intraday price-volume relationship. It utilizes the yin yang direction information within a day and combines volume confirmation signals to implement low-risk short-term trading.
Strategy Logic
The strategy calculates the open, close, high and low prices of each trading day, and generates Renko bricks together with ATR indicator. Trading signals are generated when yin yang bricks reverse.
Specifically, the strategy first calculates the open price o2 and close price c2 of the Renko bricks. If o2<c2, it indicates a yang line, if o2>c2, it indicates a yin line. When yang line turns to yin line, a sell signal is generated. When yin line turns to yang line, a buy signal is generated.
To filter false breakouts, the strategy also counts the number of periods of the last yang and yin line. If the yang line has more periods, the signal is more reliable. In addition, stop loss and take profit logic are set after buying and selling.
Advantages
Renko bricks filter market noise and make trading signals clearer.
Combining price-volume relationship avoids the risk of false breakout.
The DAPM model is simple and effective for intraday trading.
Customizable ATR parameters adjust trading frequency.
Customizable stop loss improves risk management.
Risks
There is still risk of unclear false breakout.
Improper Renko parameter settings may miss trends or increase trading frequency.
A too tight stop loss may get stopped out by minor pullback.
Optimization
Consider combining other technical indicators to filter signals.
Consider adding trailing stop loss feature.
Optimize parameters for different assets.
Consider combining different timeframes for multi-timeframe trading.
Conclusion
In conclusion, this is a very practical short-term trading strategy. It uses price-volume relationship to filter efficiently and capture key turning points. Proper parameter tuning, risk management and stop loss strategy can greatly improve its stability and profitability. With continuous optimization and testing, this strategy can become a powerful tool for intraday traders.
Parameters
| Name | Default | What it controls |
|---|---|---|
| v_input_1 | true | ---------------- Trade Range ---------------- |
| v_input_2 | true | From Month |
| v_input_3 | true | From Day |
| v_input_4 | 2017 | From Year |
| v_input_5 | true | To Month |
| v_input_6 | true | To Day |
| v_input_7 | 2099 | To Year |
| v_input_8 | true | ---------------- Settings ---------------- |
| v_input_9 | false | Allow Short |
| v_input_10 | 10 | ATR Length |
Source Pine Script
/*backtest
start: 2022-09-26 00:00:00
end: 2023-09-26 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=4
// This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License https://creativecommons.org/licenses/by-sa/4.0/
// © dman103
strategy(title="Renko Strategy V2", shorttitle="Renko Strategy V2", overlay=true,precision=3, commission_value=0.025, default_qty_type=strategy.cash, default_qty_value=10000, initial_capital=10000)
// Version 2.0 of my previous renko strategy using Renko calculations, this time without Tilson T3 and without using security with Renko to remove repaints!
// Seems to work nicely on cryptocurrencies on higher time frames.
//== Description ==
// Strategy gets Renko values and uses renko close and open to trigger signals.
// Base on these results the strategy triggers a long and short orders, where green is uptrending and red is downtrending.
// This Renko version is based on ATR, you can Set ATR (in settings) to adjust it.
// == Notes ==
// Supports alerts.
// Supports backtesting time ranges.
// Shorts are disabled by default (can be enabled in settings).
// Link to previous Renko strategy V1: https://www.tradingview.com/script/KeWBWLGT-Renko-Strategy-T3-V1/
//
// Stay tuned for version V3 in the future as i have an in progress prototype, Follow to get updated: https://www.tradingview.com/u/dman103/#published-scripts
// === INPUT BACKTEST RANGE ===
useDate = input(true, title='---------------- Trade Range ----------------', type=input.bool)
FromMonth = input(defval = 1, title = "From Month", minval = 1, maxval = 12)
FromDay = input(defval = 1, title = "From Day", minval = 1, maxval = 31)
FromYear = input(defval = 2017, title = "From Year", minval = 2000)
ToMonth = input(defval = 1, title = "To Month", minval = 1, maxval = 12)
ToDay = input(defval = 1, title = "To Day", minval = 1, maxval = 31)
ToYear = input(defval = 2099, title = "To Year", minval = 2010)
start = timestamp(FromYear, FromMonth, FromDay, 00, 00) // backtest start window
finish = timestamp(ToYear, ToMonth, ToDay, 23, 59) // backtest finish window
window() => time >= start and time <= finish ? true : false // create
settings = input(true, title='---------------- Settings ----------------', type=input.bool)
allow_short = input(false,title="Allow Short")
atr_len = input(10,"ATR Length")
atr = atr(atr_len)
// Thanks to renko snippet calculations from @RafaelZioni https://www.tradingview.com/script/2vKhpfVH-Renko-XZ/
Renko1() =>
p1 = 0.0
p1 := close > nz(p1[1]) + atr ? nz(p1[1]) + atr : close < nz(p1[1]) - atr ? nz(p1[1]) - atr : nz(p1[1])
p1
Renko2() =>
p2 = 0.0
Br_1 = Renko1()
p2 := Renko1() != Renko1()[1] ? Br_1[1] : nz(p2[1])
p2
Renko3() =>
p3 = 0.0
p3 := open > nz(p3[1]) + atr ? nz(p3[1]) + atr : open < nz(p3[1]) - atr ? nz(p3[1]) - atr : nz(p3[1])
p3
Renko4() =>
open_v = 0.0
Br_2 = Renko3()
open_v := Renko3() != Renko3()[1] ? Br_2[1] : nz(open_v[1])
open_v
o2 = Renko4()
c2 = Renko1()
l2 =low
h2 = high
//=== Plotting ===
crossPlot= 0.0
if (o2 < c2)
crossPlot :=o2
else
crossPlot := o2
// Used to make sure that even if o2 and c2 are equal, the result (short or long) will be based on previous trend.
bars_since_up=barssince(o2 < c2)
bars_since_down=barssince(o2 > c2)
go_long= (bars_since_up<bars_since_down) and o2<c2
go_short = (bars_since_up>bars_since_down) and o2>c2
plotColor = go_long and o2<c2 ? color.green : go_short and o2>c2? color.red : color.white
plot(crossPlot, color = plotColor, style = plot.style_circles, linewidth = 2,join=true)
changeCond = plotColor != plotColor[1]
//=== Buy/Sell ===
closeStatus = strategy.openprofit > 0 ? "win" : "lose"
long_entry = plotColor == color.green and window() and changeCond
long_exit_entry = plotColor == color.red //or (allow_alternative_sl and close < low_result )
short_entry = plotColor == color.red and window() and changeCond
short_exit_entry = plotColor == color.green // or (allow_alternative_sl and close > high_result )
strategy.entry("long", true, when = long_entry)
strategy.close("long",when=long_exit_entry,comment=closeStatus)
if (allow_short)
strategy.entry("short",false, when = short_entry)
strategy.close("short",when=short_exit_entry,comment=closeStatus)
//=== Alerts ===
alertcondition(go_long and changeCond , title='Renko Buy Signal', message='Renko Revered to Buy Signal')
alertcondition(go_short and changeCond , title='Renko Sell Signal', message='Renko Revered to Sell Signal')Published by ChaoZhang on the FMZ strategy square · last modified 2023-09-27. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.
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