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.
Calculate ADX, DMI and CCI indicators.
Determine trend direction.
Enter positions.
Exit positions with stop loss.
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.
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.
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.
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))))