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Multi-indicator Collision Reversal Strategy

Author: ChaoZhang, Date: 2024-01-04 18:02:12
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Overview

This strategy is designed as an efficient reversal strategy by combining dual-indicator signals. It integrates a reversal signal based on stochastic indicators and a system that tracks the number of consecutive up days. The strategy will only place orders when both signals trigger buy or sell concurrently. This multi-indicator collision mechanism can effectively filter out some invalid signals and improve the win rate.

Principle

The strategy consists of two parts. The first part is the 123 reversal system, which observes the change in closing prices over the past two days, as well as the value of a 3-period slow stochastic indicator. Specifically, when yesterday’s close is lower than the previous 2 days and today’s close is higher than yesterday’s, and the 9-period slow stochastic is below 50, go long; conversely, when today’s close is below yesterday’s and the fast stochastic is above 50, go short.

The second indicator tracks the number of consecutive up days recently over n days. If the last n days are all rising, it outputs 1, otherwise 0. This indicator is used to identify trend formation.

Finally, the strategy will only execute trades when the 123 reversal signal and the number of consecutive up days both show buy or sell status concurrently. This multi-indicator collision weighted approach can filter out some invalid signals and improve the overall stability of the strategy.

Advantage Analysis

The biggest advantage of this multi-indicator combo strategy is that it can improve the reliability of signals by filtering out some invalid ones. Specifically, there are main advantages:

  1. The 123 reversal itself has some screening capability to avoid noise interference. Combined with the consecutive day counter, it can further identify trends and avoid reversal bounces.

  2. The stochastic parameters of 9-day and 3-day fast and slow lines comparison can smooth parameter changes and avoid short-term fluctuations and enhance stability.

  3. Customizable parameters including stoch, number of rising days parameters allows adaptation to different markets.

  4. Tradable both ways providing more shorting opportunities.

Risk Analysis

There are also some risks to this strategy:

  1. The multi-indicator combo, while enhancing signal accuracy, may also miss some opportunities and limit profits.

  2. Reversal signals have inherent risks of being trapped, requiring stop losses to control risk.

  3. Improper parameter settings can affect performance requiring adjustment between markets.

  4. Holding long-term positions without timely stop loss or chasing stock reversals also carries risks.

Accordingly, the following measures can be taken to mitigate risks:

  1. Relax parameter conditions appropriately to retain more trading opportunities.

  2. Set stop loss points to limit per trade loss.

  3. Optimize parameters and set parameter rules for different markets.

  4. Avoid holding single stocks long-term and maintain liquidity.

Optimization Directions

There is still great potential to optimize this multi-indicator reversal strategy, mainly from the following aspects:

  1. Test more indicator combinations to find better matches.

  2. Use machine learning algorithms to auto optimize parameters.

  3. Add stop loss and take profit conditions for more robustness.

  4. Test different timeframes in the trend indicator part.

  5. Evaluate applicability across stock indices, forex, commodities,cryptocurrencies.

  6. Design compounding strategies that dynamically adjust allocations across multiple markets concurrently.

Summary

This strategy skillfully combines multiple indicators to design an efficient yet stable reversal trading strategy. Compared to single indicators, the multi-indicator collision mechanism effectively filters false signals. Meanwhile, this strategy also updates traditional reversal methods by adding new trend indicators for signal confirmation. With parameter optimization, stop losses, adaptation across markets, and more, this becomes a powerful quantitative trading toolkit.


/*backtest
start: 2022-12-28 00:00:00
end: 2024-01-03 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
////////////////////////////////////////////////////////////
//  Copyright by HPotter v1.0 26/03/2021
// This is combo strategies for get a cumulative signal. 
//
// First strategy
// This System was created from the Book "How I Tripled My Money In The 
// Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
// The strategy buys at market, if close price is higher than the previous close 
// during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50. 
// The strategy sells at market, if close price is lower than the previous close price 
// during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
//
// Second strategy
// Evaluates for n number of consecutive higher closes. Returns a value 
// of 1 when the condition is true or 0 when false.
//
// WARNING:
// - For purpose educate only
// - This script to change bars colors.
////////////////////////////////////////////////////////////
Reversal123(Length, KSmoothing, DLength, Level) =>
    vFast = sma(stoch(close, high, low, Length), KSmoothing) 
    vSlow = sma(vFast, DLength)
    pos = 0.0
    pos := iff(close[2] < close[1] and close > close[1] and vFast < vSlow and vFast > Level, 1,
	         iff(close[2] > close[1] and close < close[1] and vFast > vSlow and vFast < Level, -1, nz(pos[1], 0))) 
	pos


NBU(nLength) =>
    pos = 0.0
    nCounter = 0
    nCounter :=  iff(close[1] >= open[1], nz(nCounter[1],0)+1,
                  iff(close[1] < open[1], 0, nCounter))
    C1 = iff(nCounter >= nLength, 1, 0)
    posprice = 0.0
    posprice := iff(C1== 1, close, nz(posprice[1], 0)) 
    pos := iff(posprice > 0, 1, 0)
    pos

strategy(title="Combo Backtest 123 Reversal & N Bars Up", shorttitle="Combo", overlay = true)
line1 = input(true, "---- 123 Reversal ----")
Length = input(14, minval=1)
KSmoothing = input(1, minval=1)
DLength = input(3, minval=1)
Level = input(50, minval=1)
//-------------------------
line2 = input(true, "---- N Bars Up ----")
nLength = input(4, minval=1)
reverse = input(false, title="Trade reverse")
posReversal123 = Reversal123(Length, KSmoothing, DLength, Level)
posNBU = NBU(nLength)
pos = iff(posReversal123 == 1 and posNBU == 1 , 1,
	   iff(posReversal123 == -1 and posNBU == -1, -1, 0)) 
possig = iff(reverse and pos == 1, -1,
          iff(reverse and pos == -1 , 1, pos))	   
if (possig == 1 ) 
    strategy.entry("Long", strategy.long)
if (possig == -1 )
    strategy.entry("Short", strategy.short)	 
if (possig == 0) 
    strategy.close_all()
barcolor(possig == -1 ? #b50404: possig == 1 ? #079605 : #0536b3 )

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