ChaoZhang
Overview
This strategy utilizes momentum indicators including Average Directional Index (ADX), Directional Movement Index (DMI) and Commodity Channel Index (CCI) to determine trend direction and follow trends. It enters positions when ADX and trend indicators confirm a trend, and CCI is overextended.
Strategy Logic
Calculate ADX, DMI and CCI indicators.
- ADX measures trend strength. A high ADX indicates a strong trend.
- DMI includes DI+ and DI-. DI+ shows uptrend strength while DI- shows downtrend strength. If DI+ is greater than DI-, it’s an uptrend, and vice versa.
- CCI judges overbought/oversold levels. Below -100 is oversold while above 100 is overbought.
Determine trend direction.
- When DI+ crosses above DI-, an uptrend is identified.
- When DI- crosses below DI+, a downtrend is identified.
Enter positions.
- When uptrend forms, ADX is high, and CCI < -100, go long.
- When downtrend forms, ADX is high, and CCI > 100, go short.
Exit positions with stop loss.
- When long, exit when DI- crosses below DI+.
- When short, exit when DI+ crosses above DI-.
Advantage Analysis
ADX filters out trading during weak trends.
DMI reduces mistakes in trend identification.
Entering on CCI overextension improves timing and reduces risk.
Combining momentum indicators improves accuracy.
Stop loss limits loss per trade.
Risks and Hedging
Whipsaws when ADX drops. Raise ADX threshold to ensure strong enough trend.
DMI lags trend early stage. Add other analysis to identify opportunity.
High CCI trading frequency. Widen CCI range to filter noise.
Consider market neutral strategy when long and short, to hedge overall position risk.
Optimization Directions
Optimize ADX parameters to balance noise filtering and catching trend.
Optimize DMI parameters to balance lag and sensitivity.
Optimize CCI parameters to balance trading frequency and catching reversals.
Test adding or modifying indicators for better combos. E.g. MACD, KDJ.
Test on different products to find best fit.
Optimize position sizing to control risk while maintaining trend tracking.
Conclusion
The strategy logically uses ADX for trend, DMI for direction and CCI for reversals. But parameters need optimization and position sizing for risk control. Properly tuned and applied to trending products, it can deliver steady returns. Traders should dynamically adjust for changing markets.
/*backtest
start: 2023-10-02 00:00:00
end: 2023-11-01 00:00:00
period: 4h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=4
strategy("ADX Strategy", currency = "USD", initial_capital = 1000, overlay=true)
adxlen = input(9, title="ADX Smoothing")
dilen = input(14, title="DI Length")
ADX_Entry = input(25, title="ADX Entry")
dirmov(len) =>
up = change(high)
down = -change(low)
truerange = rma(tr, len)
plus = fixnan(100 * rma(up > down and up > 0 ? up : 0, len) / truerange)
minus = fixnan(100 * rma(down > up and down > 0 ? down : 0, len) / truerange)
[plus, minus]
adx(dilen, adxlen) =>
[plus, minus] = dirmov(dilen)
sum = plus + minus
adx = 100 * rma(abs(plus - minus) / (sum == 0 ? 1 : sum), adxlen)
[adx, plus, minus]
[sig, up, down] = adx(dilen, adxlen)
cci_length = input(20, minval=1, title="CCI Length")
cci_ma = sma(close, cci_length)
cci = (close - cci_ma) / (0.015 * dev(close, cci_length))
stop_loss = syminfo.mintick * 100
open_longs = strategy.position_size > 0
open_shorts = strategy.position_size < 0
possible_bull = false
possible_bull := not open_longs ? (possible_bull[1] and not crossunder(up,down) ? true : false) : false
possible_bear = false
possible_bear := not open_shorts ? (possible_bear[1] and not crossunder(down,up) ? true : false) : false
bool bull_entry = crossover(up,down)
if(bull_entry and up < ADX_Entry and cci < 0)
possible_bull := true
bull_entry := false
if(possible_bull and up > ADX_Entry and cci > -100)
bull_entry := true
bool bear_entry = crossover(down,up)
if(bear_entry and down < ADX_Entry and cci > 0)
possible_bear := true
bear_entry := false
if(possible_bear and down >= ADX_Entry and cci < 100)
bear_entry := true
strategy.entry("Short", strategy.short, qty = 1,comment="Short", stop=high[1] - stop_loss, when = bear_entry)
strategy.entry("Long", strategy.long, qty = 1, comment="Long", stop=low[1] - stop_loss, when = bull_entry )
strategy.close_all(when = (open_shorts and (crossover(up,down) or crossover(sig,down))) or (open_longs and ( crossover(down,up) or crossover(sig, up))))