Directional Trend Index Trading Strategy

Pine ScriptTrend following Breakout Mean reversion EMA Stochastic ADX / DMI

Author: ChaoZhang
Complexity: Starter · 59 lines
Parameters: 6
Backtest bar: 4h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy uses the Directional Trend Index (DTI) to determine price trend direction for trend following trades. DTI compares the change in highest and lowest prices over a period to judge the trend, with upper and lower thresholds generating signals. Go long when DTI crosses above upper band, and short when crossing below lower band.

Strategy Logic

Calculate price change value from highest and lowest price changes over a period. Apply multiple exponential moving averages to this to derive the DTI curve. Set upper and lower thresholds for DTI. When the indicator crosses above the upper threshold, a long signal is generated. Crossing below the lower threshold gives a short signal. Hold position until next signal occurs.

Advantages

DTI accurately determines trend direction with fewer signals
Thresholds filter insignificant breakouts avoiding noise trades
Continuously following trends, unaffected by short-term fluctuations
Large parameter tuning space to balance responsiveness

Risks

Trend reversal points cannot be accurately determined, risks losses
Poor DTI parameter tuning risks missing opportunities
Prolonged holding may result in larger drawdowns
Low trade frequency unsuitable for high frequency trading

Risks can be mitigated by shortening calculation period, adjusting thresholds, or adding reversal indicators.

Enhancements

Test different parameter combinations for calculating DTI
Optimize long/short threshold levels
Consider adding stop loss strategies to control risk
Test robustness across different products

Conclusion

DTI strategy accurately determines trend direction from clear signals, enabling steady long-term profits. Further refinements like parameter optimization can make it a high-quality trend following system.

Parameters

Name	Default	What it controls
v_input_1	14	r
v_input_2	10	s
v_input_3	5	u
v_input_4	45	OS
v_input_5	-45	OB
v_input_6	false	Trade reverse

Source Pine Script

/*backtest
start: 2023-08-18 00:00:00
end: 2023-09-17 00:00:00
period: 4h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=2
////////////////////////////////////////////////////////////
//  Copyright by HPotter v1.0 29/03/2017
// This technique was described by William Blau in his book "Momentum,
// Direction and Divergence" (1995). His book focuses on three key aspects 
// of trading: momentum, direction and divergence. Blau, who was an electrical 
// engineer before becoming a trader, thoroughly examines the relationship between 
// price and momentum in step-by-step examples. From this grounding, he then looks 
// at the deficiencies in other oscillators and introduces some innovative techniques, 
// including a fresh twist on Stochastics. On directional issues, he analyzes the 
// intricacies of ADX and offers a unique approach to help define trending and 
// non-trending periods.
// Directional Trend Index is an indicator similar to DM+ developed by Welles Wilder. 
// The DM+ (a part of Directional Movement System which includes both DM+ and 
// DM- indicators) indicator helps determine if a security is "trending." William 
// Blau added to it a zeroline, relative to which the indicator is deemed positive or 
// negative. A stable uptrend is a period when the DTI value is positive and rising, a 
// downtrend when it is negative and falling. 
//
// You can change long to short in the Input Settings
// Please, use it only for learning or paper trading. Do not for real trading.
////////////////////////////////////////////////////////////
strategy(title="Directional Trend Index (DTI)", shorttitle="DTI")
r = input(14, minval=1)
s = input(10, minval=1)
u = input(5, minval=1)
OS = input(45, minval=1)
OB = input(-45, maxval=-1)
reverse = input(false, title="Trade reverse")
hline(0, color=green, linestyle=line)
xHMU = iff(high - high[1] > 0, high - high[1], 0)
xLMD = iff(low - low[1] < 0, -(low - low[1]), 0)
xPrice = xHMU - xLMD
xPriceAbs = abs(xPrice)
xuXA = ema(ema(ema(xPrice, r),s),u)
xuXAAbs = ema(ema(ema(xPriceAbs, r),s),u)
Val1 = 100 * xuXA
Val2 = xuXAAbs
DTI = iff(Val2 != 0, Val1 / Val2, 0)
pos = iff(DTI > OS, -1,
	     iff(DTI < OB, 1, nz(pos[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)	   	    
barcolor(possig == -1 ? red: possig == 1 ? green : blue )
plot(DTI, color=maroon, title="DTI")
plot(OB, color=blue, title="OB")
plot(OS, color=red, title="OS")

Published by ChaoZhang on the FMZ strategy square · last modified 2023-09-18. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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