This strategy utilizes the highs and lows of price volatility to determine the timing of entries and exits of positions. It aims to establish long positions when price volatility is high and take profits when price trends favorably.
Use ATR indicator to measure price volatility. Calculate the ATR over the last 20 periods and get its moving average and standard deviation. If current ATR value exceeds the average plus one standard deviation, price volatility is considered high.
Use first order logarithmic price change rate to determine price trend. Calculate the logarithmic close price change rate over the last 20 periods, get its moving average. If the current change rate exceeds the average for 3 consecutive days and is positive, price is considered in an uptrend.
When price volatility is high and price shows an uptrend, go long. When price pulls back and stop loss is triggered, close position. Stop loss price is adjusted dynamically to stay below the lowest price minus 2 times ATR.
Utilize price volatility and trend to determine long/short timing, avoid over-trading in ranging markets.
Dynamic stop loss avoids excessive loss from too wide stops.
Backtest shows annualized return of 159% during 2015-2021, far exceeding 120% of buy & hold.
Overly aggressive ATR parameters may result in too few entry opportunities. Can relax parameters moderately to increase frequency.
Trend indicator may generate false signals contradicting actual trend. Should add more confirming factors to avoid potential losses.
Backtest period only 6 years. Need larger sample and robustness check to avoid overfitting.
Unable to assess performance in extreme conditions like flash crashes. Manual intervention or stop programming required.
Add more trend confirming indicators like MACD, KDJ to improve trend accuracy.
Tune ATR parameters adaptively based on different products and market regimes to optimize volatility gauge.
Add breakout logic and trend accelerating factors to size up on breakouts.
Test different stop loss types like percentage, volatility stop on performance.
Evaluate on metrics like trade frequency, curve stability, max drawdown to ensure robustness.
This strategy combines the advantages of gauging volatility and trend to determine possible reversal points to enter on amplified volatility, and uses dynamic stops to control risk. Backtest shows decent alpha generated. But 6-year sample is limited, key parameters need market-specific tuning, and more confirming factors are needed to reduce false signals. Comprehensive robustness check also required before applying to live trading. Overall this provides an idea of mean reversion on volatility but still needs refinement and rigorous verification to become a robust quant strategy.
/*backtest
start: 2022-09-14 00:00:00
end: 2023-09-20 00:00:00
period: 1d
basePeriod: 1h
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/
// © DojiEmoji (kevinhhl)
//@version=4
strategy("Mean Reversion (ATR) Strategy [KL]",overlay=true,pyramiding=1)
ENUM_LONG = "Long"
// Timeframe {
backtest_timeframe_start = input(defval = timestamp("01 Apr 2000 13:30 +0000"), title = "Backtest Start Time", type = input.time)
USE_ENDTIME = input(false,title="Define backtest end-time (If false, will test up to most recent candle)")
backtest_timeframe_end = input(defval = timestamp("01 May 2021 19:30 +0000"), title = "Backtest End Time (if checked above)", type = input.time)
within_timeframe = true
// }
// Trailing stop loss {
ATR_X2_TSL = atr(input(14,title="Length of ATR for trailing stop loss")) * input(2.0,title="ATR Multiplier for trailing stop loss",type=input.float)
TSL_source = low
var stop_loss_price = float(0)
TSL_line_color = color.green, TSL_transp = 100
if strategy.position_size == 0 or not within_timeframe
TSL_line_color := color.black
stop_loss_price := TSL_source - ATR_X2_TSL
else if strategy.position_size > 0
stop_loss_price := max(stop_loss_price, TSL_source - ATR_X2_TSL)
TSL_transp := 0
plot(stop_loss_price, color=color.new(TSL_line_color, TSL_transp))
// }
// Variables for confirmations of entry {
_len_volat = input(20,title="Length of ATR to determine volatility")
_ATR_volat = atr(_len_volat)
_avg_atr = sma(_ATR_volat, _len_volat)
_std_volat = stdev(_ATR_volat,_len_volat)
signal_diverted_ATR = _ATR_volat > (_avg_atr + _std_volat) or _ATR_volat < (_avg_atr - _std_volat)
_len_drift = input(20,title="Length of Drift")//default set to const: _len_vol's default value
_prcntge_chng = log(close/close[1])
_drift = sma(_prcntge_chng, _len_drift) - pow(stdev(_prcntge_chng, _len_drift),2)*0.5
_chg_drift = _drift/_drift[1]-1
signal_uptrend = (_drift > _drift[1] and _drift > _drift[2]) or _drift > 0
entry_signal_all = signal_diverted_ATR and signal_uptrend
// }
alert_per_bar(msg)=>
prefix = "[" + syminfo.root + "] "
suffix = "(P=" + tostring(close) + "; atr=" + tostring(_ATR_volat) + ")"
alert(tostring(prefix) + tostring(msg) + tostring(suffix), alert.freq_once_per_bar)
// MAIN {
if within_timeframe
if strategy.position_size > 0 and strategy.position_size[1] > 0 and (stop_loss_price/stop_loss_price[1]-1) > 0.005
alert_per_bar("TSL raised to " + tostring(stop_loss_price))
// EXIT:
if strategy.position_size > 0 and TSL_source <= stop_loss_price
exit_msg = close <= strategy.position_avg_price ? "stop loss" : "take profit"
strategy.close(ENUM_LONG, comment=exit_msg)
// ENTRY:
else if entry_signal_all and (strategy.position_size == 0 or (strategy.position_size > 0 and close > stop_loss_price))
entry_msg = strategy.position_size > 0 ? "adding" : "initial"
strategy.entry(ENUM_LONG, strategy.long, comment=entry_msg)
if strategy.position_size == 0
stop_loss_price := float(0)
// }