Vix Fix Linear Regression Bottom Fishing Strategy

The core idea of this strategy is to combine Vix Fix indicator and its linear regression to accurately capture market bottoms. The strategy is named "Fix Regression Bottom Fishing Strategy".

Pine ScriptMachine learning Trend following Volatility SMA Bollinger Bands ATR OBV

Author: ChaoZhang
Complexity: Intermediate · 77 lines
Parameters: 17
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

The core idea of this strategy is to combine Vix Fix indicator and its linear regression to accurately capture market bottoms. The strategy is named "Fix Regression Bottom Fishing Strategy".

Strategy Logic

Calculate the Vix Fix indicator, which is good at judging market bottoms
Apply linear regression on Vix Fix. When the linear regression histogram color turns green, it means the Vix Fix linear regression starts to rise, a buy signal can be triggered
Combine with the green columns of the Vix Fix indicator to further confirm the timing of entries
When the linear regression histogram color turns red, it means the Vix Fix linear regression starts to decline, a sell signal is triggered

The above process utilizes linear regression to improve the accuracy and timeliness of Vix Fix signals, filtering out some false signals, and thus accurately capturing bottoms.

Advantage Analysis

The strategy uses linear regression to filter out some false signals of the Vix Fix indicator, making buy/sell signals more accurate and reliable
Linear regression improves the sensitivity and timeliness of signals, and can quickly capture market turning points
The strategy logic is simple and clear, easy to understand and implement, suitable for quantitative trading
There are many configurable parameters that can be flexibly adjusted to adapt to market changes

Risks and Solutions

This strategy is mainly used to determine the overall market bottom, not suitable for individual stocks
Linear regression cannot completely filter out false signals. Combining with the Vix Fix indicator can reduce risks
Need to properly adjust parameters to adapt to market changes and avoid failure
It is recommended to combine with other indicators to further confirm signals

Optimization Directions

Consider combining with volatility indicators or on-balance volume indicators to further filter out signals
Study parameter adaptive optimization methods to make the strategy more intelligent
Explore machine learning methods to predict Vix Fix trends with more complex models
Try to apply similar methods to individual stocks to study how to filter false signals

Conclusion

This strategy utilizes the Vix Fix indicator to judge bottoms while introducing linear regression to improve signal quality, thereby effectively capturing market bottoms. The strategy is simple, practical and yields decent results. The main risk lies in the false signals that fail to be completely filtered out. We still need to optimize parameter settings and consider introducing other means to further confirm signals to make the strategy more robust. Overall, this strategy provides a new effective way to determine market bottoms, and is worth further research.

Parameters

Name	Default	What it controls
v_input_1	22	LookBack Period Standard Deviation High
v_input_2	20	Bolinger Band Length
v_input_3	2	Bollinger Band Standard Devaition Up
v_input_4	50	Look Back Period Percentile High
v_input_5	0.85	Highest Percentile - 0.90=90%, 0.95=95%, 0.99=99%
v_input_6	1.01	Lowest Percentile - 1.10=90%, 1.05=95%, 1.01=99%
v_input_7	false	Show High Range - Based on Percentile and LookBack Period?
v_input_8	false	Show Standard Deviation Line?
v_input_9	timestamp(01 Jan 2010 00:00 +0000)	Start Time
v_input_10	timestamp(01 Jan 2099 00:00 +0000)	End Time
v_input_11	false	considerVIXFixClose
v_input_12	20	KC Length
v_input_13	1.5	KC MultFactor
v_input_14	22	atrLen
v_input_15	5	atrMult
v_input_16	5	initialStopBar
v_input_17	true	waitForCloseBeforeStop

Source Pine Script

/*backtest
start: 2023-12-01 00:00:00
end: 2023-12-31 23:59:59
period: 1h
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/
// © HeWhoMustNotBeNamed

//@version=4
strategy("VixFixLinReg-Strategy", shorttitle="VixFixLinReg - Strategy",
                     overlay=false, initial_capital = 100000, 
                     default_qty_type = strategy.percent_of_equity, default_qty_value = 100, commission_type = strategy.commission.percent, pyramiding = 1, 
                     commission_value = 0.01)
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?")
i_startTime = input(defval = timestamp("01 Jan 2010 00:00 +0000"), title = "Start Time", type = input.time)
i_endTime = input(defval = timestamp("01 Jan 2099 00:00 +0000"), title = "End Time", type = input.time)
inDateRange = true
considerVIXFixClose = input(false)
lengthKC=input(20, title="KC Length")
multKC = input(1.5, title="KC MultFactor")

atrLen = input(22)
atrMult = input(5)
initialStopBar = input(5)
waitForCloseBeforeStop = input(true)
f_getStop(atrLen, atrMult)=>
    stop = strategy.position_size > 0 ? close - (atrMult * atr(atrLen)) : lowest(initialStopBar)
    stop := strategy.position_size > 0 ? max(stop,nz(stop[1], stop)) : lowest(initialStopBar)
    stop

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 ? color.lime : color.gray

val = linreg(wvf, pd, 0)
absVal = abs(val)

linRegColor = val>val[1]? (val > 0 ? color.green : color.orange): (val > 0 ? color.lime : color.red)
plot(hp and rangeHigh ? rangeHigh : na, title="Range High Percentile", style=plot.style_line, linewidth=4, color=color.orange)
plot(hp and rangeLow ? rangeLow : na, title="Range High Percentile", style=plot.style_line, linewidth=4, color=color.orange)
plot(wvf, title="Williams Vix Fix", style=plot.style_histogram, linewidth = 4, color=col)
plot(sd and upperBand ? upperBand : na, title="Upper Band", style=plot.style_line, linewidth = 3, color=color.aqua)

plot(-absVal, title="Linear Regression", style=plot.style_histogram, linewidth=4, color=linRegColor)

vixFixState = (col == color.lime) ? 1: 0
vixFixState := strategy.position_size == 0? max(vixFixState, nz(vixFixState[1],0)) : vixFixState

longCondition = (vixFixState == 1 and linRegColor == color.lime) and inDateRange
exitLongCondition = (linRegColor == color.orange or linRegColor == color.red) and considerVIXFixClose

stop = f_getStop(atrLen, atrMult)
label_x = time+(60*60*24*1000*20) 
myLabel = label.new(x=label_x, y=0, text="Stop : "+tostring(stop), xloc=xloc.bar_time, style=label.style_none, textcolor=color.black, size=size.normal)
label.delete(myLabel[1])
strategy.entry("Long", strategy.long, when=longCondition, oca_name="oca_buy")
strategy.close("Long", when=exitLongCondition or (close < stop and waitForCloseBeforeStop and linRegColor == color.green))
strategy.exit("ExitLong", "Long", stop = stop, when=not waitForCloseBeforeStop and linRegColor == color.green)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-01-30. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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