Pivot Point Golden Ratio Buy High Sell Low Strategy
This strategy calculates pivot points across different timeframes as key price levels and uses the golden ratio principle to determine trend direction for implementing a buy high sell low trading strategy.

Overview
This strategy calculates pivot points across different timeframes as key price levels and uses the golden ratio principle to determine trend direction for implementing a buy high sell low trading strategy.
Strategy Logic
Calculate pivot points including classic pivots and Fibonacci pivots using closing price, highest price and lowest price across different timeframes.
Determine which price zone the price is currently at based on the upper and lower bands. There are 5 buying zones and 5 selling zones.
Generate buy signals when price is in buying zones and sell signals when price is in selling zones to implement a buy high sell low strategy.
Advantage Analysis
Using multi-timeframe analysis to determine trend avoids being misled by market noise.
Combining classic pivots and Fibonacci pivots improves reliability of pivot points.
Determining market entry based on price zones maximizes risk avoidance.
Following trend trading rules by buying high and selling low avoids trading against the trend.
Risk Analysis
Pivot points could fail, so breakthroughs need to be monitored.
Avoid worsening losses from badly placed stop loss orders.
Trading fees can also impact final profitability.
Optimization Direction
Test different parameters like timeframes, trade directions etc to optimize the strategy.
Incorporate other indicators to confirm trend to avoid false breakouts.
Add stop loss mechanisms to control single trade loss amount.
Summary
This strategy integrates classical technical analysis and trend trading by using pivot point zones to time entries and buying high and selling low to effectively manage trade risks. Worth live trading and optimization.
Parameters
| Name | Default | What it controls |
|---|---|---|
| v_input_1_close | 0 | Source: close | high | low | open | hl2 | hlc3 | hlcc4 | ohlc4 |
| v_input_2 | 4D | resolution |
| v_input_3 | 4 | Higher Timeframe multiplier (Used when resolution is set to Same as Symbol) |
| v_input_4 | 0 | Trade Direction: strategy.direction.long | strategy.direction.all | strategy.direction.short |
| v_input_5 | 10 | Backtest from |
| v_input_6 | 0 | Timeframe: years | months | days |
| v_input_7 | true | hideBands |
Source Pine Script
/*backtest
start: 2022-12-22 00:00:00
end: 2023-12-28 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/
// © HeWhoMustNotBeNamed
//@version=4
strategy("BuyHighSellLow - Pivot points", overlay=true, 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, calc_on_order_fills = true)
Source = input(close)
resolution = input("4D", type=input.resolution)
HTFMultiplier = input(4, title="Higher Timeframe multiplier (Used when resolution is set to Same as Symbol)", minval=2, step=1)
//ppType = input(title="Pivot points type", defval="classic", options=["classic", "fib"])
ppType = "fib"
tradeDirection = input(title="Trade Direction", defval=strategy.direction.long, options=[strategy.direction.all, strategy.direction.long, strategy.direction.short])
backtestBars = input(title="Backtest from ", defval=10, minval=1, maxval=30)
backtestFrom = input(title="Timeframe", defval="years", options=["days", "months", "years"])
hideBands = input(true)
f_multiple_resolution(HTFMultiplier) =>
target_Res_In_Min = timeframe.multiplier * HTFMultiplier * (
timeframe.isseconds ? 1. / 60. :
timeframe.isminutes ? 1. :
timeframe.isdaily ? 1440. :
timeframe.isweekly ? 7. * 24. * 60. :
timeframe.ismonthly ? 30.417 * 24. * 60. : na)
target_Res_In_Min <= 0.0417 ? "1S" :
target_Res_In_Min <= 0.167 ? "5S" :
target_Res_In_Min <= 0.376 ? "15S" :
target_Res_In_Min <= 0.751 ? "30S" :
target_Res_In_Min <= 1440 ? tostring(round(target_Res_In_Min)) :
tostring(round(min(target_Res_In_Min / 1440, 365))) + "D"
f_getBackTestTimeFrom(backtestFrom, backtestBars)=>
byDate = backtestFrom == "days"
byMonth = backtestFrom == "months"
byYear = backtestFrom == "years"
date = dayofmonth(timenow)
mth = month(timenow)
yr = year(timenow)
leapYearDaysInMonth = array.new_int(12,0)
array.set(leapYearDaysInMonth,0,31)
array.set(leapYearDaysInMonth,1,29)
nonleapYearDaysInMonth = array.new_int(12,0)
array.set(leapYearDaysInMonth,0,31)
array.set(leapYearDaysInMonth,1,28)
restMonths = array.new_int(10,0)
array.set(leapYearDaysInMonth,0,31)
array.set(leapYearDaysInMonth,1,30)
array.set(leapYearDaysInMonth,2,31)
array.set(leapYearDaysInMonth,3,30)
array.set(leapYearDaysInMonth,4,31)
array.set(leapYearDaysInMonth,5,31)
array.set(leapYearDaysInMonth,6,30)
array.set(leapYearDaysInMonth,7,31)
array.set(leapYearDaysInMonth,8,30)
array.set(leapYearDaysInMonth,9,31)
array.concat(leapYearDaysInMonth,restMonths)
array.concat(nonleapYearDaysInMonth,restMonths)
isLeapYear = yr % 4 == 0 and (year%100 != 0 or year%400 == 0)
numberOfDaysInCurrentMonth = isLeapYear ? array.get(leapYearDaysInMonth, mth-2) : array.get(nonleapYearDaysInMonth, mth-2)
if(byDate)
mth := (date - backtestBars) < 0 ? mth - 1 : mth
yr := mth < 1 ? yr - 1 : yr
mth := mth < 1 ? 1 : mth
date := (date - backtestBars) < 0 ? numberOfDaysInCurrentMonth - backtestBars + date + 1 : date - backtestBars + 1
if(byMonth)
date := 1
yr := (mth - (backtestBars%12)) < 0 ? yr - int(backtestBars/12) - 1 : yr - int(backtestBars/12)
mth := mth - (backtestBars%12) + 1
if(byYear)
date := 1
mth := 1
yr := yr - backtestBars
[date, mth, yr]
f_secureSecurity(_symbol, _res, _src) => security(_symbol, _res, _src[1], lookahead = barmerge.lookahead_on)
f_getClassicPivots(HIGHprev, LOWprev, CLOSEprev)=>
PP = (HIGHprev + LOWprev + CLOSEprev) / 3
R1 = PP * 2 - LOWprev
S1 = PP * 2 - HIGHprev
R2 = PP + (HIGHprev - LOWprev)
S2 = PP - (HIGHprev - LOWprev)
R3 = PP * 2 + (HIGHprev - 2 * LOWprev)
S3 = PP * 2 - (2 * HIGHprev - LOWprev)
R4 = PP * 3 + (HIGHprev - 3 * LOWprev)
S4 = PP * 3 - (3 * HIGHprev - LOWprev)
R5 = PP * 4 + (HIGHprev - 4 * LOWprev)
S5 = PP * 4 - (4 * HIGHprev - LOWprev)
[R5, R4, R3, R2, R1, PP, S1, S2, S3, S4, S5]
f_getFibPivots(HIGHprev, LOWprev, CLOSEprev)=>
PP = (HIGHprev + LOWprev + CLOSEprev) / 3
R1 = PP + 0.382 * (HIGHprev - LOWprev)
S1 = PP - 0.382 * (HIGHprev - LOWprev)
R2 = PP + 0.618 * (HIGHprev - LOWprev)
S2 = PP - 0.618 * (HIGHprev - LOWprev)
R3 = PP + (HIGHprev - LOWprev)
S3 = PP - (HIGHprev - LOWprev)
R4 = PP + 1.41 * (HIGHprev - LOWprev)
S4 = PP - 1.41 * (HIGHprev - LOWprev)
R5 = PP + 1.65 * (HIGHprev - LOWprev)
S5 = PP - 1.65 * (HIGHprev - LOWprev)
[R5, R4, R3, R2, R1, PP, S1, S2, S3, S4, S5]
f_getPivotPoints(HTFMultiplier, resolution, ppType)=>
derivedResolution = resolution == ""? f_multiple_resolution(HTFMultiplier) : resolution
HIGHprev = f_secureSecurity(syminfo.tickerid, derivedResolution, high)
LOWprev = f_secureSecurity(syminfo.tickerid, derivedResolution, low)
CLOSEprev = f_secureSecurity(syminfo.tickerid, derivedResolution, close)
[R5, R4, R3, R2, R1, PP, S1, S2, S3, S4, S5] = f_getClassicPivots(HIGHprev, LOWprev, CLOSEprev)
[Rf5, Rf4, Rf3, Rf2, Rf1, PPf, Sf1, Sf2, Sf3, Sf4, Sf5] = f_getFibPivots(HIGHprev, LOWprev, CLOSEprev)
[R5, R4, R3, R2, R1, PP, S1, S2, S3, S4, S5]
f_getState(Source, R5, R4, R3, R2, R1, PP, S1, S2, S3, S4, S5)=>
state =
Source > R5 ? 5 :
Source > R4 ? 4 :
Source > R3 ? 3 :
Source > R2 ? 2 :
Source > R1 ? 1 :
Source > PP ? 0 :
Source > S1 ? -1 :
Source > S2 ? -2 :
Source > S3 ? -3 :
Source > S4 ? -4 :
Source > S5 ? -5 : -6
state
[R5, R4, R3, R2, R1, PP, S1, S2, S3, S4, S5] = f_getPivotPoints(HTFMultiplier, resolution, ppType)
[date, mth, yr] = f_getBackTestTimeFrom(backtestFrom, backtestBars)
inDateRange = time >= timestamp(syminfo.timezone, yr, mth, date, 0, 0)
BBU5 = plot(not hideBands ? R5: na, title="R5", color=color.orange, linewidth=1, transp=50, style=plot.style_linebr)
BBU4 = plot(not hideBands ? R4: na, title="R4", color=color.yellow, linewidth=1, transp=50, style=plot.style_linebr)
BBU3 = plot(not hideBands ? R3: na, title="R3", color=color.navy, linewidth=1, transp=50, style=plot.style_linebr)
BBU2 = plot(not hideBands ? R2: na, title="R2", color=color.olive, linewidth=1, transp=50, style=plot.style_linebr)
BBU1 = plot(not hideBands ? R1: na, title="R1", color=color.lime, linewidth=1, transp=50, style=plot.style_linebr)
BBM4 = plot(not hideBands ? PP:na, title="PP", color=color.black, linewidth=2, style=plot.style_linebr)
BBL1 = plot(not hideBands ? S1: na, title="S1", color=color.lime, linewidth=1, transp=50, style=plot.style_linebr)
BBL2 = plot(not hideBands ? S2: na, title="S2", color=color.olive, linewidth=1, transp=50, style=plot.style_linebr)
BBL3 = plot(not hideBands ? S3: na, title="S3", color=color.navy, linewidth=1, transp=50, style=plot.style_linebr)
BBL4 = plot(not hideBands ? S4: na, title="S4", color=color.yellow, linewidth=1, transp=50, style=plot.style_linebr)
BBL5 = plot(not hideBands ? S5: na, title="S5", color=color.orange, linewidth=1, transp=50, style=plot.style_linebr)
fill(BBU5, BBU4, title="RZ5", color=color.green, transp=90)
fill(BBU4, BBU3, title="RZ4", color=color.lime, transp=90)
fill(BBU3, BBU2, title="RZ3", color=color.olive, transp=90)
fill(BBU2, BBU1, title="RZ2", color=color.navy, transp=90)
fill(BBU1, BBM4, title="RZ1", color=color.yellow, transp=90)
fill(BBM4, BBL1, title="SZ1", color=color.orange, transp=90)
fill(BBL1, BBL2, title="SZ2", color=color.red, transp=90)
fill(BBL2, BBL3, title="SZ3", color=color.maroon, transp=90)
fill(BBL3, BBL4, title="SZ4", color=color.maroon, transp=90)
fill(BBL4, BBL5, title="SZ5", color=color.maroon, transp=90)
strategy.risk.allow_entry_in(tradeDirection)
longCondition = crossover(Source[1],R1) and inDateRange
shortCondition = crossunder(Source[1], S2) and inDateRange
strategy.entry("Buy", strategy.long, when=longCondition, oca_name="oca")
strategy.entry("Sell", strategy.short, when=shortCondition, oca_name="oca")
Published by ChaoZhang on the FMZ strategy square · last modified 2023-12-29. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.
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