Strategi trailing stop loss berdasarkan stop loss elastis
ChaoZhang
Ringkasan
Strategi ini didasarkan pada indikator stop loss yang elastis, mengatur sinyal beli dan jual, melakukan operasi posisi panjang dan pendek. Ketika indikator muncul sinyal beli, lakukan lebih banyak; Ketika muncul sinyal jual, kosong. Strategi ini juga menggabungkan mekanisme stop loss tracking, yang dapat secara efektif mengendalikan risiko.
Prinsip
Strategi ini terutama menggunakan indikator stop loss elastis untuk mengidentifikasi titik balik tren, melakukan operasi reversal. Di dalam indikator, indikator real-range digunakan untuk mengidentifikasi harga ekstrim, dan ketika harga melebihi nilai ekstrim, dianggap sebagai terobosan yang luar biasa, untuk menilai kemungkinan pembalikan tren. Secara khusus, indikator mempertahankan dua variabel di dalam: harga ekstrim (EP) dan harga pemicu (TP).
Dalam tren naik, ketika harga lebih tinggi dari EP, dinilai sebagai terobosan yang tidak biasa, saat ini EP diperbarui menjadi harga tertinggi, TP adalah harga terendah. Ketika harga lebih rendah dari TP, dinilai tren berbalik, menghasilkan sinyal jual. Dalam tren turun, prinsipnya mirip.
Strategi ini digabungkan dengan mekanisme tracking stop loss yang akan melacak harga stop loss optimal secara real time setelah membuka posisi, sekaligus mengontrol risiko dalam memastikan profitabilitas. Secara khusus, setelah melakukan over, garis stop loss akan melacak titik rendah penutupan; setelah melakukan shorting, garis stop loss akan melacak titik tinggi penutupan.
Keunggulan
Strategi ini memiliki keuntungan sebagai berikut:
Menggunakan indikator untuk mengidentifikasi titik balik tren, tidak mudah untuk dikurung.
Pelacakan mekanisme stop loss, yang dapat mengunci keuntungan dan mencegah kerugian berkembang.
Parameter indikatornya sederhana dan mudah diterapkan.
Anda dapat mengkonfigurasi sinyal pembelian dan penjualan, mudah dioperasikan.
Fleksibilitas dalam mengkonfigurasi siklus pengembalian untuk mengevaluasi efektifitas strategi secara menyeluruh.
Risiko
Strategi ini juga memiliki beberapa risiko:
Indikator tersebut tertinggal, dan mungkin melewatkan titik terbaik untuk membalikkan tren.
Stop loss terlalu radikal, dan bisa saja terganggu oleh pergerakan harga dalam jangka pendek.
Periode yang dipilih tidak tepat, sehingga tidak dapat mengevaluasi efektifitas strategi secara menyeluruh.
Perhatikan dampak dari biaya transaksi pada keuntungan.
Ada beberapa cara untuk mengoptimalkan risiko:
Menyesuaikan parameter indikator untuk mengurangi keterlambatan
Optimalkan algoritma stop loss untuk menghindari penipuan.
Memilih siklus pengujian yang tepat untuk memastikan keandalan.
Mengoptimalkan manajemen posisi dan mengurangi biaya transaksi.
Arah optimasi
Strategi ini dapat dioptimalkan lebih lanjut dengan:
Dalam kombinasi dengan indikator tren, untuk menghindari perdagangan berbalik. Anda dapat menambahkan indikator seperti MA untuk menentukan tren besar.
Mengoptimalkan algoritma manajemen posisi, seperti posisi proporsi tetap, posisi dinamis, dan lain-lain.
Menambahkan filter volume transaksi untuk menghindari kesalahan transaksi yang disebabkan oleh celah.
Optimalkan parameter untuk menemukan kombinasi optimal.
Bergabunglah dengan strategi stop-loss, berhenti tepat waktu saat tren berjalan.
Optimalkan strategi stop loss agar stop loss lebih lancar. Anda dapat mencoba algoritma stop loss seperti Chandelier Exit.
Optimalkan jenis transaksi, jangka waktu, dan lain-lain untuk meningkatkan fleksibilitas strategi.
Menambahkan algoritma pembelajaran mesin untuk membuat strategi lebih adaptif.
Meringkaskan
Strategi ini secara keseluruhan relatif sederhana dan dapat diandalkan, menggunakan indikator stop loss yang elastis untuk mengidentifikasi titik balik, dan dilengkapi dengan mekanisme stop loss untuk melacak risiko kontrol, dapat digunakan sebagai strategi reversal garis pendek. Namun, tetap perlu memperhatikan masalah seperti indikator yang terlambat, stop loss yang terlalu radikal. Dengan pengoptimalan lebih lanjut, diharapkan mendapatkan efek strategi yang lebih baik.
Overview
This strategy is based on the Parabolic SAR indicator to generate buy and sell signals for long and short positions. It also incorporates a trailing stop loss mechanism to effectively control risks.
Principle
The core of this strategy is to identify trend reversal points using the Parabolic SAR indicator for counter-trend trading. The indicator uses the true range to detect extreme prices. When the price exceeds the extreme, it is considered a breakout and a sign of potential trend reversal. Specifically, the indicator maintains two variables: the Extreme Price (EP) and the Trigger Price (TP). The EP represents the highest/lowest price of the current trend, while the TP is derived from the EP.
In an uptrend, when the price is higher than the EP, it is considered a breakout. The EP is then updated to the highest price and the TP to the lowest price. When the price falls below the TP, a trend reversal is identified and a sell signal is generated. The same principle applies for a downtrend.
The strategy also incorporates a trailing stop loss mechanism. After opening a position, it will track the optimal stop loss price in real-time, locking in profits while controlling risks. Specifically, after long entry, the stop loss tracks the closing low; after short entry, it tracks the closing high.
Advantages
The main advantages of this strategy are:
Identify trend reversal points with the indicator, avoiding being trapped in trends.
Trailing stop loss locks in profits and prevents wider losses.
Simple indicator parameters, easy to implement.
Configurable buy/sell signal alerts for convenience.
Flexible backtest period configuration for thorough evaluation.
Risks
There are also some risks to consider:
Indicator lag may miss optimal reversal points.
Aggressive stops may be stopped out by short-term fluctuations.
Improper backtest period selection cannot fully evaluate the strategy.
Transaction costs may impair profits.
Some ways to address the risks are:
Optimize parameters to reduce lag.
Improve stop loss algorithm to avoid being stopped out unnecessarily.
Select appropriate backtest periods for reliability.
Optimize position sizing to lower transaction costs.
Enhancement
Some ways to further optimize the strategy:
Incorporate trend indicators like MA to avoid being trapped in countertrends.
Optimize position sizing algorithms, e.g. fixed fractional, dynamic.
Add volume filter to avoid false signals from gaps.
Parameter optimization to find optimal combinations.
Implement profit taking strategies to lock in profits in trends.
Refine stop loss algorithms for smoother stops. Experiment with Chandelier Exit etc.
Optimize across products, time frames etc. to improve adaptability.
Incorporate machine learning for greater adaptability.
Summary
In summary, this is a simple and robust strategy using the Parabolic SAR to identify reversals and trailing stop loss to control risk. It can work as a short-term mean-reversion strategy. But indicator lag and oversensitive stops need to be addressed. Further optimizations can lead to improved performance.
/*backtest
start: 2023-09-10 00:00:00
end: 2023-10-10 00:00:00
period: 2h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=4
strategy("PB SAR BackTest - Colorbar", overlay=false)
// Full credit to Sawcruhteez, Lucid Investment Strategies LLC, Casey Bowman and Peter Brandt.
// This is a strategy version of the Peterbolic SAR indicator created by the above-mentioned parties.
// Original version of the indicator: https://www.tradingview.com/script/6nYrH3Vm-Peterbolic-SAR/
// SAR #1
// Lucid Sar
// Branded under the name "Lucid SAR"
// as agreed to with Lucid Investment Strategies LLC on July 9, 2019
// https://lucidinvestmentstrategies.com/
// see branch "lucid"
// SAR #2
// Peterbolic Sar
// Using the name "Peterbolic SAR"
// as agreed to by Peter Brandt on October 2, 2019
// - https://twitter.com/PeterLBrandt/status/1179365590668075008
// in response to request from Sawcruhteez
// - https://twitter.com/Sawcruhteez/status/1179213105705836544
// Sawcruhteez gives credit to @CrazyGabey for coming up with the name
// - https://twitter.com/Sawcruhteez/status/1179213196583940097
// see branch "peterbolic"
// SAR #3
// Sawcruhteez Sar
// Branded under the name "Sawcruhteez SAR"
// as agreed to with Sawcruhteez on September 11, 2019
// see branch "sawcruhteez"
// Open Source on github
// https://github.com/casey-bowman/sar/blob/peterbolic/peterbolic.pine
// Created by Casey Bowman on July 4, 2019
// MIT License
// Copyright (c) 2019 Casey Bowman
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
// copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:
// The above copyright notice and this permission notice shall be included in all
// copies or substantial portions of the Software.
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
// SOFTWARE.
TSR() =>
// start with uptrend
var uptrend = true
var EP = high // extreme price - high or low depending on trend
var SP = low // setup price
var TP = float(na) // trigger price
var setup = low
var trigger = float(na)
if barstate.isnew
setup := low
trigger = float(na)
extreme_candle = false
first_extreme_candle = false
setup_candle = false
trigger_candle = false
waiting_for_setup = false
waiting_for_trigger = false
var since_extreme = 0
var since_setup = 0
waiting_for_setup := not extreme_candle and not na(SP)
waiting_for_trigger := not na(TP)
if not barstate.isfirst
if barstate.isnew and extreme_candle[1]
trigger := float(na)
if barstate.isnew and setup_candle[1]
setup := float(na)
if barstate.isnew and waiting_for_trigger
since_setup := since_setup + 1
trigger := TP
if barstate.isnew and waiting_for_setup
since_extreme := since_extreme + 1
setup := SP
if uptrend
if extreme_candle
EP := high
SP := low
else
if high > EP
extreme_candle := true
EP := high
SP := low
since_extreme := 0
since_setup := 0
else
if waiting_for_setup
if barstate.isconfirmed
if close < SP
setup_candle := true
SP := float(na)
TP := low
if waiting_for_trigger
if low < TP
trigger_candle := true
extreme_candle := true
EP := low
SP := high
TP := float(na)
uptrend := false
since_extreme := 0
since_setup := 0
else
if barstate.isconfirmed and extreme_candle
TP := float(na)
trigger := float(na)
else
if extreme_candle
EP := low
SP := high
else
if low < EP
extreme_candle := true
EP := low
SP := high
since_extreme := 0
since_setup := 0
else
if waiting_for_setup
if barstate.isconfirmed
if close > SP
setup_candle := true
SP := float(na)
TP := high
if waiting_for_trigger
if high > TP
trigger_candle := true
extreme_candle := true
EP := high
SP := low
TP := float(na)
uptrend := true
since_extreme := 0
since_setup := 0
else
if barstate.isconfirmed and extreme_candle
TP := float(na)
trigger := float(na)
[trigger_candle, trigger, since_setup, setup_candle, setup, since_extreme, extreme_candle, uptrend]
[TC, T, SS, SC, S, SE, EC, up] = TSR()
// Make input options that configure backtest date range
StartMonth = input(title="Start Month", type=input.integer,
defval=1, minval=1, maxval=12)
StartDate = input(title="Start Date", type=input.integer,
defval=1, minval=1, maxval=31)
StartYear = input(title="Start Year", type=input.integer,
defval=(2019), minval=1800, maxval=2100)
EndMonth = input(title="End Month", type=input.integer,
defval=1, minval=1, maxval=12)
EndDate = input(title="End Date", type=input.integer,
defval=1, minval=1, maxval=31)
EndYear = input(title="End Year", type=input.integer,
defval=(2020), minval=1800, maxval=2100)
// Look if the close time of the current bar falls inside the date range
inDateRange = true
buytrigger = (TC and up)
selltrigger = (TC and not up)
buysetup = (SC and not up)
sellsetup = (SC and up)
IntBuy = buytrigger ? 1 : 0
IntSB = buysetup ? 0.5 : 0
IntSell= selltrigger ? -1 : 0
IntSS = sellsetup ? -0.5 : 0
bgcolor = buytrigger ? color.green : selltrigger ? color.red : buysetup ? color.yellow : sellsetup ? color.orange : color.black
trans = buytrigger ? 20 : selltrigger ? 20 : 100
bgcolor(bgcolor, 30)
NUM = IntBuy + IntSB + IntSell + IntSS
linecolor = color.orange
plot(NUM, color=linecolor, linewidth=2)
alertcondition(NUM > 0.5, title="Buy Signal", message="Buy Alert")
alertcondition(NUM < -0.5, title="Sell Signal", message="Sell Alert")
alertcondition(NUM == 0.5, title="Buy Setup", message="Buy Setup")
alertcondition(NUM == -0.5, title="Sell Setup", message="Sell Setup")
//Switch on for strategy moves
if(inDateRange and buytrigger)
strategy.exit("SHORT", "SHORT_SL", comment="Short_Exit")
strategy.entry("LONG", strategy.long, comment="")
if(inDateRange and selltrigger)
strategy.exit("LONG", "LONG_SL", comment="Long_Exit")
strategy.entry("SHORT", strategy.short, comment="")
if (not inDateRange)
strategy.close_all()
// plotshape(SC and not up, color = color.yellow, style = shape.triangleup, location = location.belowbar, size = size.auto, transp = 0, title = "Setup to Buy")
// plotshape(TC and up, color = color.green, style = shape.triangleup, location = location.belowbar, size = size.auto, title = "Trigger to Buy")
// plotshape(SC and up, color = color.yellow, style = shape.triangledown, location = location.abovebar, size = size.auto, transp = 0, title = "Setup to Sell")
// plotshape(TC and not up, color = color.red, style = shape.triangledown, location = location.abovebar, size = size.auto, title = "Trigger to Sell")