Price Volatility Mean Reversion Strategy

This strategy detects price reversal opportunities by calculating the standard deviation of price volatility. When there is an anomalously large price fluctuation, it is considered as an opportunity for price…

Pine ScriptMean reversion Volatility RSI MACD SMA Bollinger Bands

Author: ChaoZhang
Complexity: Intermediate · 78 lines
Parameters: 18
Backtest bar: 2d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Principle

The strategy uses two main indicators:

VixFix indicator: Calculates the standard deviation of price over a certain period to determine if there is anomalous price volatility. The specific calculation is:

wvf = ((highest(close, pd)-low)/(highest(close, pd)))*100
sDev = mult * stdev(wvf, bbl) 
midLine = sma(wvf, bbl)
lowerBand = midLine - sDev 
upperBand = midLine + sDev

Where wvf is price volatility, sDev is standard deviation, midLine is the average line, lowerBand and upperBand are the lower and upper limit lines. When price exceeds the upper limit line, it is considered anomalous volatility.

RSI indicator: Calculates the Relative Strength Index of price to determine timing of price reversal. The calculation is:

fastup = rma(max(change(close), 0), 7)
fastdown = rma(-min(change(close), 0), 7) 
fastrsi = fastdown == 0 ? 100 : fastup == 0 ? 0 : 100 - (100 / (1 + fastup / fastdown))

When RSI is below a threshold, it indicates oversold status and potential bounce back. When RSI exceeds a threshold, it indicates overbought status and potential pullback.

Entry and Exit

The entry and exit logic is:

Long entry: When price exceeds upper limit or volatility exceeds threshold, and RSI is below a value, go long.

Short entry: When price exceeds upper limit or volatility exceeds threshold, and RSI exceeds a value, go short.

Exit: When candlestick body direction is opposite of position direction, close position.

Advantages

Uses statistical properties of anomalous price volatility to determine price reversal with wide coverage.
Combining with RSI to judge overbought/oversold improves entry precision.
Breaking lower deviation band as entry signal reduces missing opportunities.
Candlestick body reversal as stop loss realizes quick stop loss and reduces losses.

Risks

Lower deviation band may need adjustment for parameter optimization.
Breaking lower band does not guarantee reversal, risks being trapped.
RSI parameters need optimization, improper values lead to inaccurate signals.
Candlestick body stop loss may be too aggressive, needs adjustment.

Optimization Directions

Optimize calculation period of standard deviation to better capture anomalous volatility.
Optimize RSI parameters to find better overbought/oversold criteria.
Try combining other indicators like KDJ, MACD to determine reversal timing.
Optimize stop loss mechanism, set price retracement as stop loss benchmark.

Conclusion

The strategy detects anomalous price volatility through calculating standard deviation of price volatility, to capture reversal opportunities. RSI is combined to judge overbought/oversold status for improving entry precision. Simple candlestick body direction stop loss is used. Overall, the strategy is effective in using statistical data to detect anomalous volatility, but needs further parameter optimization to improve stability. If the stop loss mechanism can be reasonably optimized to reduce losses, the strategy would perform even better.

Parameters

Name	Default	What it controls
v_input_1	true	Long
v_input_2	true	Short
v_input_3	true	leverage
v_input_4	40	RSI Limit
v_input_5	22	LookBack Period Standard Deviation High
v_input_6	20	Bolinger Band Length
v_input_7	2	Bollinger Band Standard Devaition Up
v_input_8	50	Look Back Period Percentile High
v_input_9	0.85	Highest Percentile - 0.90=90%, 0.95=95%, 0.99=99%
v_input_10	1.01	Lowest Percentile - 1.10=90%, 1.05=95%, 1.01=99%
v_input_11	false	Show High Range - Based on Percentile and LookBack Period?
v_input_12	false	Show Standard Deviation Line?
v_input_13	1900	From Year
v_input_14	2100	To Year
v_input_15	true	From Month
v_input_16	12	To Month
v_input_17	true	From day
v_input_18	31	To day

Source Pine Script

/*backtest
start: 2022-10-04 00:00:00
end: 2023-10-10 00:00:00
period: 2d
basePeriod: 1d
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//Noro
//2018

//@version=2
strategy(title = "Noro's VixFix + RSI Strategy v1.0", shorttitle = "VixFix + RSI str 1.0", overlay = true, default_qty_type = strategy.percent_of_equity, default_qty_value = 100, pyramiding = 5)

//Settings
needlong = input(true, defval = true, title = "Long")
needshort = input(true, defval = true, title = "Short")
leverage = input(1, defval = 1, minval = 1, maxval = 100, title = "leverage")
limit = input(40, defval = 40, minval = 2, maxval = 50, title = "RSI Limit")

pd = input(22, title="LookBack Period Standard Deviation High")
bbl = input(20, title="Bolinger Band Length")
mult = input(2.0, minval = 1, maxval = 5, title = "Bollinger Band Standard Devaition Up")
lb = input(50, title="Look Back Period Percentile High")
ph = input(.85, title="Highest Percentile - 0.90=90%, 0.95=95%, 0.99=99%")
pl = input(1.01, title="Lowest Percentile - 1.10=90%, 1.05=95%, 1.01=99%")
hp = input(false, title="Show High Range - Based on Percentile and LookBack Period?")
sd = input(false, title="Show Standard Deviation Line?")

fromyear = input(1900, defval = 1900, minval = 1900, maxval = 2100, title = "From Year")
toyear = input(2100, defval = 2100, minval = 1900, maxval = 2100, title = "To Year")
frommonth = input(01, defval = 01, minval = 01, maxval = 12, title = "From Month")
tomonth = input(12, defval = 12, minval = 01, maxval = 12, title = "To Month")
fromday = input(01, defval = 01, minval = 01, maxval = 31, title = "From day")
today = input(31, defval = 31, minval = 01, maxval = 31, title = "To day")

//Vix Fix
wvf = ((highest(close, pd)-low)/(highest(close, pd)))*100
sDev = mult * stdev(wvf, bbl)
midLine = sma(wvf, bbl)
lowerBand = midLine - sDev
upperBand = midLine + sDev
rangeHigh = (highest(wvf, lb)) * ph
rangeLow = (lowest(wvf, lb)) * pl

col = wvf >= upperBand or wvf >= rangeHigh ? lime : gray

//RSI
fastup = rma(max(change(close), 0), 7)
fastdown = rma(-min(change(close), 0), 7)
fastrsi = fastdown == 0 ? 100 : fastup == 0 ? 0 : 100 - (100 / (1 + fastup / fastdown))

//Body
body = abs(close - open)
abody = sma(body, 10)

//Signals
up = (wvf >= upperBand or wvf >= rangeHigh) and fastrsi < limit and close < open
dn = (wvf >= upperBand or wvf >= rangeHigh) and fastrsi > (100 - limit) and close > open
exit = ((strategy.position_size > 0 and close > open) or (strategy.position_size < 0 and close < open)) and body > abody / 3

//Trading
lot = strategy.position_size == 0 ? strategy.equity / close * leverage : lot[1]

if up
    if strategy.position_size < 0
        strategy.close_all()
        
    strategy.entry("Bottom", strategy.long, needlong == false ? 0 : lot, when=(time > timestamp(fromyear, frommonth, fromday, 00, 00) and time < timestamp(toyear, tomonth, today, 23, 59)))

if dn
    if strategy.position_size > 0
        strategy.close_all()
        
    strategy.entry("Top", strategy.short, needshort == false ? 0 : lot, when=(time > timestamp(fromyear, frommonth, fromday, 00, 00) and time < timestamp(toyear, tomonth, today, 23, 59)))
    
if time > timestamp(toyear, tomonth, today, 23, 59) or exit
    strategy.close_all()

Published by ChaoZhang on the FMZ strategy square · last modified 2023-10-11. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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