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The Momentum Direction Divergence Strategy is one of the techniques described by William Blau in his book “Momentum, Direction and Divergence”. The strategy focuses on three key aspects: momentum, direction and divergence. Blau, who was an electrical engineer before becoming a trader, thoroughly examines the relationship between price and momentum. 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.

The strategy plots Ergotic CSI and its smoothed line to filter out noise.

The code starts by defining an Adaptive Direction Index (ADX) function fADX, which takes parameter Len as the smoothing period. The function calculates the RMA of True Range (TR) as denominator, and RMA of upside momentum and downside momentum as numerator, then divides them to get ratios indicating the relative strength of upside and downside. Finally, ADX is obtained by combining upside strength and downside strength.

Then strategy parameters are defined. r is the smoothing parameter for ATR, Length is the length of ADX, BigPointValue is big point value, SmthLen is the smoothing length for CSI, SellZone and BuyZone are sell and buy zones that meet the criteria. reverse indicates whether to reverse the trading signals.

The key logic is in CSI calculation. First ATR and ADX are computed. Then the penalty coefficient K is calculated, incorporating considerations of big point value, ATR and ADX. The standardized residual nRes combines information from ATR, ADX and close price. Finally CSI value is obtained, and its SMA is calculated.

Trading direction is determined according to SMA value of CSI. Go long if above BuyZone, go short if below SellZone. Plot CSI curve and its SMA, color code different trading zones.

The strategy combines the advantages of momentum indicator ATR and trend indicator ADX, considering both market volatility and trend strength, avoiding limitations of using ATR or ADX alone. The design of penalty coefficient K cleverly integrates the relationships between these indicators and big point value.

The standardized residual nRes incorporates price information, paying attention not only to momentum trend but also absolute price level, which is different from typical oscillators, enhancing the strategy’s performance.

The smoothing process and zone determination provide clear trading signals for practical trading.

The strategy is quite sensitive to parameter settings like periods of ATR and ADX, big point value etc., which can affect performance. Extensive backtests are needed to determine proper parameter combinations.

As a newly proposed oscillator, the efficacy of CSI needs validation across more diverse markets. Poor CSI performance would hurt strategy profitability.

The strategy itself does not have a stop loss mechanism, just directly long or short per CSI signals. There are risks that need to be mitigated by incorporating stop loss.

Test parameter combinations across different markets to find relatively universal settings.

Introduce a dynamic ADX period mechanism adjusting ADX parameters based on market states.

Incorporate other oscillator indicators to determine entries and exits to make the strategy more robust. Effects like bottom divergence, top divergence can be useful.

Add stop loss mechanisms to complete the strategy.

The Momentum Direction Divergence Strategy integrates advantages of multiple indicators, utilizing price, momentum, trend dimensions to design CSI indicator for trading. With flexible parameter settings and strong capacity, the strategy deserves further testing and optimization, and can become a beneficial quantitative trading tool.

/*backtest start: 2022-12-20 00:00:00 end: 2023-12-26 00:00:00 period: 1d basePeriod: 1h exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}] */ //@version=2 //////////////////////////////////////////////////////////// // Copyright by HPotter v1.0 20/06/2018 // This is one of the techniques described by William Blau in his book // "Momentum, Direction and Divergence" (1995). If you like to learn more, // we advise you to read this book. 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. // This indicator plots Ergotic CSI and smoothed Ergotic CSI to filter out noise. // // You can change long to short in the Input Settings // WARNING: // - For purpose educate only // - This script to change bars colors. //////////////////////////////////////////////////////////// fADX(Len) => up = change(high) down = -change(low) trur = rma(tr, Len) plus = fixnan(100 * rma(up > down and up > 0 ? up : 0, Len) / trur) minus = fixnan(100 * rma(down > up and down > 0 ? down : 0, Len) / trur) sum = plus + minus 100 * rma(abs(plus - minus) / (sum == 0 ? 1 : sum), Len) strategy(title="Ergodic CSI Backtest") r = input(32, minval=1) Length = input(1, minval=1) BigPointValue = input(1.0, minval=0.00001) SmthLen = input(5, minval=1) SellZone = input(0.004, minval=0.00001) BuyZone = input(0.024, minval=0.001) reverse = input(false, title="Trade reverse") hline(BuyZone, color=green, linestyle=line) hline(SellZone, color=red, linestyle=line) source = close K = 100 * (BigPointValue / sqrt(r) / (150 + 5)) xTrueRange = atr(1) xADX = fADX(Length) xADXR = (xADX + xADX[1]) * 0.5 nRes = iff(Length + xTrueRange > 0, K * xADXR * xTrueRange / Length,0) xCSI = iff(close > 0, nRes / close, 0) xSMA_CSI = sma(xCSI, SmthLen) pos = iff(xSMA_CSI > BuyZone, 1, iff(xSMA_CSI <= SellZone, -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(xCSI, color=green, title="Ergodic CSI") plot(xSMA_CSI, color=red, title="SigLin")template: strategy.tpl:40:21: executing "strategy.tpl" at <.api.GetStrategyListByName>: wrong number of args for GetStrategyListByName: want 7 got 6