Volatility Adjusted Moving Average Trading Strategy

Pine ScriptVolatility Machine learning Mean reversion RSI MACD EMA ATR Heikin Ashi

Author: ChaoZhang
Complexity: Intermediate · 138 lines
Parameters: 5
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy utilizes a combination of the T3 moving average, ATR indicator and Heikin Ashi to identify buy and sell signals, and uses the ATR to calculate stop loss and take profit levels for trend following trading. The advantage of this strategy is the quick response while controlling trading risk.

Principle Analysis

Indicator Calculations

T3 Moving Average: Calculates a smoothed T3 moving average (default period 100) to determine trend direction
ATR: Calculates the Average True Range, used to determine stop loss/take profit size
ATR Trailing Stop: Calculates a stop loss based on ATR that adjusts based on price movement and volatility

Trade Logic

Buy Signal: Triggered when close crosses above ATR trailing stop and is below T3 moving average
Sell Signal: Triggered when close crosses below ATR trailing stop and is above T3 moving average
Stop Loss/Take Profit: After entry, stop loss and take profit prices calculated based on ATR and user defined risk/reward ratio

Entry and Exit

Long Entry: Stop loss is entry price minus ATR, take profit is entry price plus ATR * risk/reward ratio
Short Entry: Stop loss is entry price plus ATR, take profit is entry price minus ATR * risk/reward ratio
Exit when price hits stop loss or take profit levels

Advantage Analysis

Quick Response

T3 moving average default period is 100, more sensitive than typical moving averages for faster reaction to price changes

Risk Control

ATR trailing stop moves with market volatility to avoid being stopped out. Stop loss/take profit based on ATR controls risk/reward per trade

Trend Following

ATR trailing stop follows the trend, avoids premature exit even during short term pullbacks

Parameter Optimization

Periods for both T3 and ATR can be optimized for different markets to improve robustness

Risk Analysis

Stop Loss Breakeven

Severe price moves could penetrate stop loss causing loss. Can widen ATR period and stop distance.

Trend Reversal

Losses possible if trend reverses and price crosses trailing stop. Can incorporate other indicators to identify reversals.

Optimization Overfitting

Parameter optimization risks overfitting limited historical data. Need robust optimization across markets/timeframes.

Improvement Opportunities

Test different T3 moving average periods to find optimal balance of sensitivity and stability
Optimize ATR period to find best risk control and trend following balance
Incorporate RSI, MACD to avoid wrong trades at turning points
Machine learning for optimal automated parameters, reducing manual bias
Add position sizing rules to better control risk

Summary

This strategy combines the advantages of the T3 and ATR to enable fast response with risk control. Further enhancements in stability and efficiency possible through parameter optimization and additional filters. But traders should still watch for reversal and breakeven risks, and avoid over-reliance on backtest results.

Parameters

Name	Default	What it controls
v_input_1	100	T3
v_input_2	true	Key Value. "This changes the sensitivity"
v_input_3	50	ATR Period
v_input_4	true	Signals from Heikin Ashi Candles
v_input_5	true	Risk Reward Ratio

Source Pine Script

/*backtest
start: 2022-10-31 00:00:00
end: 2023-11-06 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy(title='UT Bot Alerts (QuantNomad) Strategy w/ NinjaView', overlay=true)
T3 = input(100)//600
// Input for Long Settings
// Input for Long Settings


xPrice3 = close
xe1 = ta.ema(xPrice3, T3)
xe2 = ta.ema(xe1, T3)
xe3 = ta.ema(xe2, T3)
xe4 = ta.ema(xe3, T3)
xe5 = ta.ema(xe4, T3)
xe6 = ta.ema(xe5, T3)

b3 = 0.7
c1 = -b3*b3*b3
c2 = 3*b3*b3+3*b3*b3*b3
c3 = -6*b3*b3-3*b3-3*b3*b3*b3
c4 = 1+3*b3+b3*b3*b3+3*b3*b3
nT3Average = c1 * xe6 + c2 * xe5 + c3 * xe4 + c4 * xe3

//plot(nT3Average, color=color.white, title="T3")

// Buy Signal - Price is below T3 Average
buySignal3 = xPrice3 < nT3Average
sellSignal3 = xPrice3 > nT3Average
// Inputs
a = input(1, title='Key Value. "This changes the sensitivity"')
c = input(50, title='ATR Period')
h = input(true, title='Signals from Heikin Ashi Candles')
riskRewardRatio = input(1, title='Risk Reward Ratio')

xATR = ta.atr(c)
nLoss = a * xATR

src = h ? request.security(ticker.heikinashi(syminfo.tickerid), timeframe.period, close, lookahead=barmerge.lookahead_off) : close

xATRTrailingStop = 0.0
iff_1 = src > nz(xATRTrailingStop[1], 0) ? src - nLoss : src + nLoss
iff_2 = src < nz(xATRTrailingStop[1], 0) and src[1] < nz(xATRTrailingStop[1], 0) ? math.min(nz(xATRTrailingStop[1]), src + nLoss) : iff_1
xATRTrailingStop := src > nz(xATRTrailingStop[1], 0) and src[1] > nz(xATRTrailingStop[1], 0) ? math.max(nz(xATRTrailingStop[1]), src - nLoss) : iff_2

pos = 0
iff_3 = src[1] > nz(xATRTrailingStop[1], 0) and src < nz(xATRTrailingStop[1], 0) ? -1 : nz(pos[1], 0)
pos := src[1] < nz(xATRTrailingStop[1], 0) and src > nz(xATRTrailingStop[1], 0) ? 1 : iff_3

xcolor = pos == -1 ? color.red : pos == 1 ? color.green : color.blue

ema = ta.ema(src, 1)
above = ta.crossover(ema, xATRTrailingStop)
below = ta.crossunder(ema, xATRTrailingStop)

buy = src > xATRTrailingStop and above
sell = src < xATRTrailingStop and below

barbuy = src > xATRTrailingStop
barsell = src < xATRTrailingStop

plotshape(buy, title='Buy', text='Buy', style=shape.labelup, location=location.belowbar, color=color.new(color.green, 0), textcolor=color.new(color.white, 0), size=size.tiny)
plotshape(sell, title='Sell', text='Sell', style=shape.labeldown, location=location.abovebar, color=color.new(color.red, 0), textcolor=color.new(color.white, 0), size=size.tiny)

barcolor(barbuy ? color.new(color.green, 90) : na)
barcolor(barsell ? color.new(color.red, 90) : na)

var float entryPrice = na
var float takeProfitLong = na
var float stopLossLong = na
var float takeProfitShort = na
var float stopLossShort = na

if buy and buySignal3
    entryPrice := src
    takeProfitLong := entryPrice + nLoss * riskRewardRatio
    stopLossLong := entryPrice - nLoss
    takeProfitShort := na
    stopLossShort := na

if sell and sellSignal3
    entryPrice := src
    takeProfitShort := entryPrice - nLoss * riskRewardRatio
    stopLossShort := entryPrice + nLoss
    takeProfitLong := na
    stopLossLong := na

// Strategy order conditions
acct = "Sim101"
ticker = "ES 12-23"
qty = 1

OCOMarketLong = '{ "alert": "OCO Market Long", "account": "' + str.tostring(acct) + '", "ticker": "' + str.tostring(ticker) + '", "qty": "' + str.tostring(qty) + '", "take_profit_price": "' + str.tostring(takeProfitLong) + '", "stop_price": "' + str.tostring(stopLossLong) + '", "tif": "DAY" }'
OCOMarketShort = '{ "alert": "OCO Market Short", "account": "' + str.tostring(acct) + '", "ticker": "' + str.tostring(ticker) + '", "qty": "' + str.tostring(qty) + '", "take_profit_price": "' + str.tostring(takeProfitShort) + '", "stop_price": "' + str.tostring(stopLossShort) + '", "tif": "DAY" }'
CloseAll = '{ "alert": "Close All", "account": "' + str.tostring(acct) + '", "ticker": "' + str.tostring(ticker) + '" }'

strategy.entry("Long", strategy.long, when=buy ,alert_message=OCOMarketLong)
strategy.entry("Short", strategy.short, when=sell , alert_message=OCOMarketShort)

// Setting the take profit and stop loss for long trades
strategy.exit("Take Profit/Stop Loss", "Long", stop=stopLossLong, limit=takeProfitLong,alert_message=CloseAll)

// Setting the take profit and stop loss for short trades
strategy.exit("Take Profit/Stop Loss", "Short", stop=stopLossShort, limit=takeProfitShort,alert_message=CloseAll)

// Plot trade setup boxes
bgcolor(buy ? color.new(color.green, 90) : na, transp=0, offset=-1)
bgcolor(sell ? color.new(color.red, 90) : na, transp=0, offset=-1)

longCondition = buy and not na(entryPrice)
shortCondition = sell and not na(entryPrice)

var line longTakeProfitLine = na
var line longStopLossLine = na
var line shortTakeProfitLine = na
var line shortStopLossLine = na

if longCondition
    longTakeProfitLine := line.new(bar_index, takeProfitLong, bar_index + 1, takeProfitLong, color=color.green, width=2)
    longStopLossLine := line.new(bar_index, stopLossLong, bar_index + 1, stopLossLong, color=color.red, width=2)
    label.new(bar_index + 1, takeProfitLong, str.tostring(takeProfitLong, "#.#####"), color=color.green, style=label.style_none, textcolor=color.green, size=size.tiny)
    label.new(bar_index + 1, stopLossLong, str.tostring(stopLossLong, "#.#####"), color=color.red, style=label.style_none, textcolor=color.red, size=size.tiny)

if shortCondition
    shortTakeProfitLine := line.new(bar_index, takeProfitShort, bar_index + 1, takeProfitShort, color=color.green, width=2)
    shortStopLossLine := line.new(bar_index, stopLossShort, bar_index + 1, stopLossShort, color=color.red, width=2)
    label.new(bar_index + 1, takeProfitShort, str.tostring(takeProfitShort, "#.#####"), color=color.green, style=label.style_none, textcolor=color.green, size=size.tiny)
    label.new(bar_index + 1, stopLossShort, str.tostring(stopLossShort, "#.#####"), color=color.red, style=label.style_none, textcolor=color.red, size=size.tiny)

alertcondition(buy, 'UT Long', 'UT Long')
alertcondition(sell, 'UT Short', 'UT Short')

Published by ChaoZhang on the FMZ strategy square · last modified 2023-11-07. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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