The resource loading... loading...
  1. Square
  2. PPO Price Sensitivity Momentum Double Bottom Directional Trading Strategy

PPO Price Sensitivity Momentum Double Bottom Directional Trading Strategy

Author: ChaoZhang, Date: 2024-01-29 11:38:42
Tags:

img

Overview

The PPO Price Sensitivity Momentum Double Bottom Directional Trading Strategy is a trend following trading strategy that utilizes the identification of price double bottom formations by the PPO (Percentage Price Oscillator) indicator to generate trade signals. It combines PPO’s double bottom pattern recognition and price momentum characteristics to achieve precise positioning of price double bottom reversal points.

Strategy Principles

The strategy employs PPO indicator to determine price double bottom features, while incorporating price minimum point judgement to monitor PPO indicator’s bottoming formation in real time. When PPO forms an upward reversal double bottom, it signals a current buying opportunity.

On the other hand, the strategy collaborates with price minimum value determination to ascertain if price resides at relatively low levels. If price stays low while PPO exhibits bottoming pattern, a buy signal is triggered.

Through PPO reversal characteristic validation and price level confirmation dual mechanism, potential price reversal chances can be identified effectively, filtering out false signals and improving signal quality.

Advantage Analysis

  1. PPO double bottom pattern enables accurate timing at entry points.

  2. Combining price level confirmation filters out false signals occurring at relatively high levels, improving signal quality.

  3. PPO is sensitive and swiftly captures price trend changes, suitable for trend tracking.

  4. Dual confirmation mechanism effectively mitigates trading risk.

Risks and Solutions

  1. PPO tends to produce false signals, requiring confirmation from other indicators. Moving average or volatility indicators can assist confirmation.

  2. Double bottom reversal may not sustain, facing risks of further decline. Stop loss can be set along with position sizing optimization.

  3. Inappropriate parameter configuration leads to missed profit or wrong entries. Repeated backtests and optimization on parameter combination is necessary.

  4. There is substantial code volume with replications. Further modularization helps reduce duplicated codes.

Optimization Directions

  1. Incorporate stop loss module and optimize position sizing strategies.

  2. Introduce moving average or volatility indicators as confirmation tools.

  3. Modularize codes to avoid redundant logic judgements.

  4. Continue parameter tuning to enhance stability.

  5. Test spread trading applications across more products.

Conclusion

The PPO Price Sensitivity Momentum Double Bottom Directional Trading Strategy captures PPO indicator’s double bottom features coupled with dual confirmation of price level positioning to effectively spot price reversal points. Compared to single indicator judgement, it possesses advantages of improved accuracy and capability to filter out noises. Nonetheless, certain risks of false signals remain, requiring further optimization on indicator combinations and strict position sizing tactics before stable profitability can be achieved in live trading.

/*backtest
start: 2024-01-27 00:00:00
end: 2024-01-28 00:00:00
period: 2h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © luciancapdefier

//@version=4
strategy("PPO Divergence ST", overlay=true, initial_capital=30000, calc_on_order_fills=true, default_qty_type=strategy.percent_of_equity, default_qty_value=100)

// time
FromYear = input(2019, "Backtest Start Year")
FromMonth = input(1, "Backtest Start Month")
FromDay = input(1, "Backtest Start Day")
ToYear = input(2999, "Backtest End Year")
ToMonth = input(1, "Backtest End Month")
ToDay = input(1, "Backtest End Day")
start = timestamp(FromYear, FromMonth, FromDay, 00, 00)  // backtest start window
finish = timestamp(ToYear, ToMonth, ToDay, 23, 59)        // backtest finish window
window() => time >= start and time <= finish ? true : false 

source = close
topbots = input(true, title="Show PPO high/low triangles?")
long_term_div = input(true, title="Use long term divergences?")
div_lookback_period = input(55, minval=1, title="Lookback Period")
fastLength = input(12, minval=1, title="PPO Fast")
slowLength=input(26, minval=1, title="PPO Slow")
signalLength=input(9,minval=1, title="PPO Signal")
smoother = input(2,minval=1, title="PPO Smooth")
fastMA = ema(source, fastLength)
slowMA = ema(source, slowLength)
macd = fastMA - slowMA
macd2=(macd/slowMA)*100
d = sma(macd2, smoother) // smoothing PPO
 
bullishPrice = low 

priceMins = bullishPrice > bullishPrice[1] and bullishPrice[1] < bullishPrice[2] or low[1] == low[2] and low[1] < low and low[1] < low[3] or low[1] == low[2] and low[1] == low[3] and low[1] < low and low[1] < low[4] or low[1] == low[2] and low[1] == low[3] and low[1] and low[1] == low[4] and low[1] < low and low[1] < low[5] // this line identifies bottoms and plateaus in the price
oscMins= d > d[1] and d[1] < d[2] // this line identifies bottoms in the PPO

BottomPointsInPPO = oscMins

bearishPrice = high
priceMax = bearishPrice < bearishPrice[1] and bearishPrice[1] > bearishPrice[2] or high[1] == high[2] and high[1] > high and high[1] > high[3] or high[1] == high[2] and high[1] == high[3] and high[1] > high and high[1] > high[4] or high[1] == high[2] and high[1] == high[3] and high[1] and high[1] == high[4] and high[1] > high and high[1] > high[5]  // this line identifies tops in the price
oscMax = d < d[1] and d[1] > d[2]   // this line identifies tops in the PPO

TopPointsInPPO = oscMax

currenttrough4=valuewhen (oscMins, d[1], 0) // identifies the value of PPO at the most recent BOTTOM in the PPO
lasttrough4=valuewhen (oscMins, d[1], 1) // NOT USED identifies the value of PPO at the second most recent BOTTOM in the PPO
currenttrough5=valuewhen (oscMax, d[1], 0) // identifies the value of PPO at the most recent TOP in the PPO
lasttrough5=valuewhen (oscMax, d[1], 1) // NOT USED identifies the value of PPO at the second most recent TOP in the PPO

currenttrough6=valuewhen (priceMins, low[1], 0) // this line identifies the low (price) at the most recent bottom in the Price
lasttrough6=valuewhen (priceMins, low[1], 1) // NOT USED this line identifies the low (price) at the second most recent bottom in the Price
currenttrough7=valuewhen (priceMax, high[1], 0) // this line identifies the high (price) at the most recent top in the Price
lasttrough7=valuewhen (priceMax, high[1], 1) // NOT USED this line identifies the high (price) at the second most recent top in the Price

delayedlow = priceMins and barssince(oscMins) < 3 ? low[1] : na
delayedhigh = priceMax and barssince(oscMax) < 3 ? high[1] : na

// only take tops/bottoms in price when tops/bottoms are less than 5 bars away
filter = barssince(priceMins) < 5 ? lowest(currenttrough6, 4) : na
filter2 = barssince(priceMax) < 5 ? highest(currenttrough7, 4) : na

//delayedbottom/top when oscillator bottom/top is earlier than price bottom/top
y11 = valuewhen(oscMins, delayedlow, 0)
y12 = valuewhen(oscMax, delayedhigh, 0)

// only take tops/bottoms in price when tops/bottoms are less than 5 bars away, since 2nd most recent top/bottom in osc
y2=valuewhen(oscMax, filter2, 1) // identifies the highest high in the tops of price with 5 bar lookback period SINCE the SECOND most recent top in PPO
y6=valuewhen(oscMins, filter, 1) // identifies the lowest low in the bottoms of price with 5 bar lookback period SINCE the SECOND most recent bottom in PPO

long_term_bull_filt = valuewhen(priceMins, lowest(div_lookback_period), 1)
long_term_bear_filt = valuewhen(priceMax, highest(div_lookback_period), 1)

y3=valuewhen(oscMax, currenttrough5, 0) // identifies the value of PPO in the most recent top of PPO 
y4=valuewhen(oscMax, currenttrough5, 1) // identifies the value of PPO in the second most recent top of PPO 

y7=valuewhen(oscMins, currenttrough4, 0) // identifies the value of PPO in the most recent bottom of PPO
y8=valuewhen(oscMins, currenttrough4, 1) // identifies the value of PPO in the SECOND most recent bottom of PPO

y9=valuewhen(oscMins, currenttrough6, 0)
y10=valuewhen(oscMax, currenttrough7, 0)

bulldiv= BottomPointsInPPO ? d[1] : na // plots dots at bottoms in the PPO
beardiv= TopPointsInPPO ? d[1]: na // plots dots at tops in the PPO

i = currenttrough5 < highest(d, div_lookback_period) // long term bearish oscilator divergence
i2 = y10 > long_term_bear_filt // long term bearish top divergence
i3 = delayedhigh > long_term_bear_filt // long term bearish delayedhigh divergence

i4 = currenttrough4 > lowest(d, div_lookback_period) // long term bullish osc divergence
i5 = y9 < long_term_bull_filt // long term bullish bottom div
i6 = delayedlow < long_term_bull_filt // long term bullish delayedbottom div

//plot(0, color=gray)
//plot(d, color=black)
//plot(bulldiv, title = "Bottoms", color=maroon, style=circles, linewidth=3, offset= -1)
//plot(beardiv, title = "Tops", color=green, style=circles, linewidth=3, offset= -1)

bearishdiv1 = (y10 > y2 and oscMax and y3 < y4) ? true : false
bearishdiv2 = (delayedhigh > y2 and y3 < y4) ? true : false
bearishdiv3 = (long_term_div and oscMax and i and i2) ? true : false
bearishdiv4 = (long_term_div and i and i3) ? true : false

bullishdiv1 = (y9 < y6 and oscMins and y7 > y8) ? true : false
bullishdiv2 = (delayedlow < y6 and y7 > y8) ? true : false
bullishdiv3 = (long_term_div and oscMins and i4 and i5) ? true : false
bullishdiv4 = (long_term_div and i4 and i6) ? true : false

bearish = bearishdiv1 or bearishdiv2 or bearishdiv3 or bearishdiv4
bullish = bullishdiv1 or bullishdiv2 or bullishdiv3 or bullishdiv4
 
greendot = beardiv != 0 ? true : false
reddot = bulldiv != 0 ? true : false

if (reddot and window())
    strategy.entry("Buy Id", strategy.long, comment="BUY")

if (greendot and window())
    strategy.entry("Sell Id", strategy.short, comment="SELL")

alertcondition( bearish, title="Bearish Signal (Orange)", message="Orange & Bearish: Short " ) 
alertcondition( bullish, title="Bullish Signal (Purple)", message="Purple & Bullish: Long " )
alertcondition( greendot, title="PPO High (Green)", message="Green High Point: Short " ) 
alertcondition( reddot, title="PPO Low (Red)", message="Red Low Point: Long " )

// plotshape(bearish ? d : na, text='▼\nP', style=shape.labeldown, location=location.abovebar, color=color(orange,0), textcolor=color(white,0), offset=0)
// plotshape(bullish ? d : na, text='P\n▲', style=shape.labelup, location=location.belowbar, color=color(#C752FF,0), textcolor=color(white,0), offset=0)
plotshape(topbots and greendot ? d : na, text='', style=shape.triangledown, location=location.abovebar, color=color.red, offset=0, size=size.tiny)
plotshape(topbots and reddot ? d : na, text='', style=shape.triangleup, location=location.belowbar, color=color.lime, offset=0, size=size.tiny)

//barcolor(bearishdiv1 or bearishdiv2 or bearishdiv3 or bearishdiv4 ? orange : na)
//barcolor(bullishdiv1 or bullishdiv2 or bullishdiv3 or bullishdiv4 ? fuchsia : na)
//barcolor(#dedcdc)
More

2019 FMZ - All rights reserved