Strategi Mengikuti Tren RSI
ChaoZhang
Ringkasan
Strategi ini menggabungkan indikator RSI dan rata-rata bergerak berbobot untuk melakukan perdagangan yang mengikuti tren. Strategi ini melakukan perdagangan bullish ketika RSI lebih tinggi dari 60, dan bullish ketika RSI lebih rendah dari 40, dan mengharuskan rata-rata bergerak untuk memenuhi kondisi tren. Strategi ini menggunakan RSI 40 siklus sebagai indikator yang mengikuti tren.
Prinsip Strategi
Strategi ini pertama-tama menghitung RSI dan rata-rata bergerak berbobot. RSI memiliki panjang 20 periode, rata-rata bergerak berbobot memiliki panjang 20, dan setelan beratnya lebih besar untuk mengurangi dampak dari fluktuasi jangka pendek. Bila RSI lebih besar dari 60 dan rasio perubahan rata-rata bergerak berbobot kurang dari 1%, melakukan operasi multipel; Bila RSI lebih kecil dari 40 dan rasio perubahan rata-rata bergerak berbobot lebih besar dari 1%, melakukan operasi kosong.
Setelah melakukan shorting lebih banyak, Anda akan mengatur stop loss dan stop stop mobile secara bersamaan. Stop loss jaraknya 3 kali ATR dari harga saat ini. Stop stop mobile pertama kali mengaktifkan harga dari 4 kali ATR dari harga saat ini, kemudian bergerak dengan amplitudo 3%.
Strategi ini juga menambahkan aturan pengelolaan dana untuk menyesuaikan posisi melalui proporsi tetap. Setiap kali keuntungan atau kerugian mencapai jumlah tetap, volume perdagangan meningkat atau menurun dalam jumlah tetap.
Analisis Keunggulan
- Menggunakan indikator RSI untuk menilai tren, dapat secara efektif melacak tren
- Rata-rata bergerak berbobot mengurangi dampak dari fluktuasi jangka pendek dengan berbagai bobot untuk menghindari pegangan
- Menggunakan Stop Stop Mobile untuk Memaksimalkan Keuntungan
- Pengelolaan modal proporsi tetap dan pengendalian risiko yang efektif
Keunggulan keseluruhan dari strategi ini adalah kemampuan untuk melacak tren, sementara mengambil tindakan stop loss dan move stops untuk mengendalikan risiko, sehingga mendapatkan hasil yang lebih baik dalam situasi yang kuat.
Analisis risiko
- Indikator RSI mengirimkan sinyal yang salah yang dapat menyebabkan perdagangan yang tidak perlu
- Penembusan Stop Loss atau Stop Loss yang bergerak akan memaksa stop loss dan tidak dapat terus mengikuti tren
- Aturan pengelolaan dana bisa terlalu radikal dan menyebabkan kerugian yang lebih besar
Risiko utama dari strategi ini adalah keandalan indikator RSI dan apakah pengaturan stop loss yang bergerak masuk akal. Jika parameter tidak diatur dengan benar, mungkin akan menyebabkan kerugian yang tidak perlu atau lebih dari kemampuan menanggung kerugian. Selain itu, mungkin juga terhenti secara paksa ketika harga stop loss atau stop loss pecah, kehilangan kesempatan untuk terus mengikuti tren.
Anda dapat mempertimbangkan untuk mengoptimalkan parameter RSI, atau mengubah penilaian dengan indikator lain. Anda dapat menyesuaikan parameter stop loss mobile stop loss untuk menyesuaikan dengan berbagai varietas dan situasi fluktuasi. Akhirnya, berhati-hatilah dalam mengatur aturan manajemen dana, jangan terlalu radikal untuk menghindari risiko melebihi kemampuan tanggung jawab Anda.
Arah optimasi
- Cobalah indikator lain yang digabungkan dengan RSI untuk konfirmasi sinyal, seperti KD, MACD, dll.
- Optimalkan parameter Stop Loss Mobile Stop sesuai dengan karakteristik varietas dan rentang fluktuasi
- Cobalah metode pengelolaan uang lainnya, seperti perdagangan volume tetap, rumus Kelly, dan sebagainya.
- Tambahkan kondisi untuk membuka posisi, seperti menembus garis Brin, RSI deviasi, dan lain-lain.
- Pertimbangan untuk menambahkan posisi dalam tren yang kuat
Strategi ini dapat dioptimalkan dari berbagai sisi. Pertama, mencari indikator teknis lain yang dapat membantu atau mengkonfirmasi indikator RSI, meningkatkan keandalan sinyal. Kedua, sangat penting untuk mengoptimalkan parameter stop loss mobile stop sesuai dengan karakteristik varietas tertentu.
Meringkaskan
Strategi pelacakan tren RSI ini memiliki konsep yang jelas, dengan fokus pada penggunaan RSI untuk menentukan arah tren, dan membantu meningkatkan akurasi penilaian dengan bobot rata-rata bergerak. Keuntungan dari strategi ini adalah kemampuan untuk melacak tren dan memaksimalkan penguncian keuntungan, sementara juga mengatur stop loss dan manajemen dana untuk mengendalikan risiko. Namun, ada ruang untuk pengoptimalan.
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Overview
This strategy combines the RSI indicator and weighted moving average for trend following trading. It goes long when RSI is above 60 and goes short when RSI is below 40, with the moving average verifying the trend condition. The 40-period RSI acts as a trend following indicator. The weighted moving average uses different weights to reduce the impact of short-term fluctuations. The strategy also employs stop loss and trailing take profit to control risks.
Strategy Logic
The strategy firstly calculates the RSI and weighted moving average. The RSI length is 20 periods and the weighted MA length is 20 with higher weights that reduce the impact of short-term volatility. It goes long when RSI is above 60 and weighted MA rate of change is below -1%. It goes short when RSI is below 40 and weighted MA rate of change is above 1%.
After opening long or short, stop loss and trailing take profit orders are placed simultaneously. The stop loss is set at 3 ATR from the current price. The initial trailing take profit activation is 4 ATR away, and trails in 3% increments. When price hits either stop loss or trailing take profit activation, the position will be closed.
The strategy also incorporates money management rules based on the fixed fractional position sizing approach. Whenever PNL hits a fixed amount, the order size is increased or decreased by a fixed amount.
Advantage Analysis
- RSI indicator can effectively track trends
- Weighted MA reduces the impact of short-term fluctuations, avoiding whipsaws
- Trailing take profit allows profits to be maximized
- Fixed fraction position sizing controls risk effectively
The overall edge is the ability to follow trends, while taking stop loss and trailing take profit measures to control risks, thus capturing significant gains in strong trends.
Risk Analysis
- False signals from RSI may cause unnecessary trades
- Forced to stop out when price breaches stop or trailing take profit levels, unable to keep following trends
- Aggressive money management rules may lead to large losses
The main risks come from the reliability of RSI signals and the stop loss/trailing take profit settings. Incorrect parameters may result in unnecessary closing of trades or losses beyond risk appetite. Breaking stop loss/take profit may also force unwarranted stop outs, losing the chance to continue trend trading.
Solutions include optimizing RSI parameters or adding other indicators for signal confirmation. Adjust stop/trailing take profit levels based on different products and volatility conditions. Also be prudent with money management rules to avoid excessive risks.
Optimization Directions
- Test other indicators together with RSI for signal confirmation, e.g. KD, MACD etc
- Optimize stop loss and trailing take profit parameters based on product characteristics and volatility range
- Try other money management techniques like fixed size trading, Kelly formula etc
- Add entry conditions like Bollinger breakouts, RSI divergences etc
- Consider adding positions on strong trends
There are many aspects to optimize. First is identifying other indicators to supplement RSI signals. Next critical step is optimizing stop loss/trailing take profit parameters based on historical performance. Money management can also switch to other types. Finally, entry, add-on conditions can be enhanced to pyramiding positions in strong trends.
Summary
The RSI trend following strategy has clear logic, using RSI for trend direction and weighted MA for confirmation. Its strength lies in trend trading, maximizing profits with stops/money management controlling risks. But RSI reliability and parameter optimization need improvement. We can look into enhancing signal indicators, stop/trailing parameters, money management methods etc to make the strategy more robust across different products.
[/trans]
/*backtest
start: 2023-01-01 00:00:00
end: 2023-06-24 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/
// © gsanson66
//This code is based on RSI and a backed weighted MA
//@version=5
strategy("RSI + MA BACKTESTING", overlay=true, initial_capital=1000, default_qty_type=strategy.fixed, commission_type=strategy.commission.percent, commission_value=0.18)
//------------------------FUNCTIONS---------------------------//
//@function which calculate a retro weighted moving average to minimize the impact of short term reversal
rwma(source, length) =>
sum = 0.0
denominator = 0.0
weight = 0.0
weight_x = 100/(4+(length-4)*1.30)
weight_y = 1.30*weight_x
for i=0 to length - 1
if i <= 3
weight := weight_x
else
weight := weight_y
sum := sum + source[i] * weight
denominator := denominator + weight
rwma = sum/denominator
//@function which permits the user to choose a moving average type
ma(source, length, type) =>
switch type
"SMA" => ta.sma(source, length)
"RWMA" => rwma(source, length)
//@function Displays text passed to `txt` when called.
debugLabel(txt, color) =>
label.new(bar_index, high, text = txt, color=color, style = label.style_label_lower_right, textcolor = color.black, size = size.small)
//@function which looks if the close date of the current bar falls inside the date range
inBacktestPeriod(start, end) => (time >= start) and (time <= end)
//--------------------------------USER INPUTS-------------------------------//
//Technical parameters
rsiLengthInput = input.int(20, minval=1, title="RSI Length", group="RSI Settings")
maTypeInput = input.string("RWMA", title="MA Type", options=["SMA", "RWMA"], group="MA Settings", inline="1")
maLenghtInput = input.int(20, minval=1, title="MA Length", group="MA Settings", inline="1")
rsiLongSignalValue = input.int(60, minval=1, maxval=99, title="RSI Long Signal", group="Strategy parameters", inline="3")
rsiShortSignalValue = input.int(40, minval=1, maxval=99, title="RSI Short Signal", group="Strategy parameters", inline="3")
rocMovAverLongSignalValue = input.float(-1, maxval=0, title="ROC MA Long Signal", group="Strategy parameters", inline="4")
rocMovAverShortSignalValue = input.float(1, minval=0, title="ROC MA Short Signal", group="Strategy parameters", inline="4")
//TP Activation and Trailing TP
takeProfitActivationInput = input.float(4, minval=1.0, title="TP activation in multiple of ATR", group="Strategy parameters")
trailingStopInput = input.float(3, minval=0, title="Trailing TP in percentage", group="Strategy parameters")
//Money Management
fixedRatio = input.int(defval=400, minval=1, title="Fixed Ratio Value ($)", group="Money Management")
increasingOrderAmount = input.int(defval=200, minval=1, title="Increasing Order Amount ($)", group="Money Management")
//Backtesting period
startDate = input(title="Start Date", defval=timestamp("1 Jan 2018 00:00:00"), group="Backtesting Period")
endDate = input(title="End Date", defval=timestamp("1 July 2024 00:00:00"), group="Backtesting Period")
strategy.initial_capital = 50000
//------------------------------VARIABLES INITIALISATION-----------------------------//
float rsi = ta.rsi(close, rsiLengthInput)
float ma = ma(close, maLenghtInput, maTypeInput)
float roc_ma = ((ma/ma[maLenghtInput]) - 1)*100
float atr = ta.atr(20)
var float trailingStopOffset = na
var float trailingStopActivation = na
var float trailingStop = na
var float stopLoss = na
var bool long = na
var bool short = na
var bool bufferTrailingStopDrawing = na
float theoreticalStopPrice = na
bool inRange = na
equity = strategy.equity - strategy.openprofit
var float capital_ref = strategy.initial_capital
var float cashOrder = strategy.initial_capital * 0.95
//------------------------------CHECKING SOME CONDITIONS ON EACH SCRIPT EXECUTION-------------------------------//
//Checking if the date belong to the range
inRange := true
//Checking performances of the strategy
if equity > capital_ref + fixedRatio
spread = (equity - capital_ref)/fixedRatio
nb_level = int(spread)
increasingOrder = nb_level * increasingOrderAmount
cashOrder := cashOrder + increasingOrder
capital_ref := capital_ref + nb_level*fixedRatio
if equity < capital_ref - fixedRatio
spread = (capital_ref - equity)/fixedRatio
nb_level = int(spread)
decreasingOrder = nb_level * increasingOrderAmount
cashOrder := cashOrder - decreasingOrder
capital_ref := capital_ref - nb_level*fixedRatio
//Checking if we close all trades in case where we exit the backtesting period
if strategy.position_size!=0 and not inRange
debugLabel("END OF BACKTESTING PERIOD : we close the trade", color=color.rgb(116, 116, 116))
strategy.close_all()
bufferTrailingStopDrawing := false
stopLoss := na
trailingStopActivation := na
trailingStop := na
short := false
long := false
//------------------------------STOP LOSS AND TRAILING STOP ACTIVATION----------------------------//
// We handle the stop loss and trailing stop activation
if (low <= stopLoss or high >= trailingStopActivation) and long
if high >= trailingStopActivation
bufferTrailingStopDrawing := true
else if low <= stopLoss
long := false
stopLoss := na
trailingStopActivation := na
if (low <= trailingStopActivation or high >= stopLoss) and short
if low <= trailingStopActivation
bufferTrailingStopDrawing := true
else if high >= stopLoss
short := false
stopLoss := na
trailingStopActivation := na
//-------------------------------------TRAILING STOP--------------------------------------//
// If the traling stop is activated, we manage its plotting with the bufferTrailingStopDrawing
if bufferTrailingStopDrawing and long
theoreticalStopPrice := high - trailingStopOffset * syminfo.mintick
if na(trailingStop)
trailingStop := theoreticalStopPrice
else if theoreticalStopPrice > trailingStop
trailingStop := theoreticalStopPrice
else if low <= trailingStop
trailingStop := na
bufferTrailingStopDrawing := false
long := false
if bufferTrailingStopDrawing and short
theoreticalStopPrice := low + trailingStopOffset * syminfo.mintick
if na(trailingStop)
trailingStop := theoreticalStopPrice
else if theoreticalStopPrice < trailingStop
trailingStop := theoreticalStopPrice
else if high >= trailingStop
trailingStop := na
bufferTrailingStopDrawing := false
short := false
//---------------------------------LONG CONDITION--------------------------//
if rsi >= 60 and roc_ma <= rocMovAverLongSignalValue and inRange and not long
if short
bufferTrailingStopDrawing := false
stopLoss := na
trailingStopActivation := na
trailingStop := na
short := false
trailingStopActivation := close + takeProfitActivationInput*atr
trailingStopOffset := (trailingStopActivation * trailingStopInput/100) / syminfo.mintick
stopLoss := close - 3*atr
long := true
qty = cashOrder/close
strategy.entry("Long", strategy.long, qty)
strategy.exit("Exit Long", "Long", stop = stopLoss, trail_price = trailingStopActivation,
trail_offset = trailingStopOffset)
//--------------------------------SHORT CONDITION-------------------------------//
if rsi <= 40 and roc_ma >= rocMovAverShortSignalValue and inRange and not short
if long
bufferTrailingStopDrawing := false
stopLoss := na
trailingStopActivation := na
trailingStop := na
long := false
trailingStopActivation := close - takeProfitActivationInput*atr
trailingStopOffset := (trailingStopActivation * trailingStopInput/100) / syminfo.mintick
stopLoss := close + 3*atr
short := true
qty = cashOrder/close
strategy.entry("Short", strategy.short, qty)
strategy.exit("Exit Short", "Short", stop = stopLoss, trail_price = trailingStopActivation,
trail_offset = trailingStopOffset)
//--------------------------------PLOTTING ELEMENT---------------------------------//
// Plotting of element in the graph
plotchar(rsi, "RSI", "", location.top, color.rgb(0, 214, 243))
plot(ma, "MA", color.rgb(219, 219, 18))
plotchar(roc_ma, "ROC MA", "", location.top, color=color.orange)
// Visualizer trailing stop and stop loss movement
plot(stopLoss, "SL", color.red, 3, plot.style_linebr)
plot(trailingStopActivation, "Trigger Trail", color.green, 3, plot.style_linebr)
plot(trailingStop, "Trailing Stop", color.blue, 3, plot.style_linebr)