Name
基于RSI和加权移动平均线的趋势跟踪策略Trend-Following-Strategy-Based-on-RSI-and-Weighted-Moving-Average
Author
ChaoZhang
Strategy Description
本策略基于两个著名的指标:相对强弱指标(RSI)和加权移动平均线(Weighted Moving Average,WMA),用来识别市场趋势并跟踪其方向。RSI用来判断超买超卖,WMA用来判断价格趋势,二者结合使用可以有效过滤掉不相关的信号,提高获利概率。这是一个中长期策略,同时结合了资金管理方法,可以根据盈亏情况调整仓位。
RSI是最广为人知的超买超卖指标之一。其公式为:
其中AvgGain为一定周期内收盘价高于开盘价的日数的收盘价之和除以天数,AvgLoss 为收盘价低于开盘价的日数的收盘价绝对值之和除以天数。
本策略将RSI周期设定为20,作为判断趋势的指标。当RSI大于60时产生多头信号,小于40时产生空头信号。
WMA相比SMA更加强调近期价格。其计算公式为:
w为权重,随着i的增加w呈指数增长。本策略采用的权重公式为:
$$w = \begin{cases} 100/(4+(n-4)1.3), & i <= 3 \ 1.3w, & i > 3 \end{cases}$$
即最近3天的权重相同,之后每往前1天权重增加1.3倍。这样可以强调近期价格的影响。
本策略中,WMA的长度为20天。
多头信号:RSI > 60 且 WMA 20天 ROC < -1
空头信号:RSI < 40 且 WMA 20天 ROC > 1
其中WMA的20天ROC的计算公式为:
- 利用RSI判断趋势方向,避免被震荡市耗尽资金
- WMA通过近期加权降低噪音,判断主要趋势
- RSI和WMA ROC结合使用,可以有效过滤无关信号
- 采用多个ATR随机止盈,追踪止盈可以灵活锁定利润
- 资金管理方法可以根据损益情况调整仓位规模,控制风险
- 策略参数不当可能导致交易频繁,建议优化参数
- 止损点设定不当可能扩大损失
- 作为趋势跟踪策略,不适合震荡盘整理市
- 需关注宏观环境变化,必要时手动平仓
- 对RSI长度、WMA长度、ROC阈值进行测试,找到最优参数组合
- 测试不同的资金管理方法,找到最佳仓位调整方案
- 增加其他指标判断,进一步过滤信号
- 结合止损策略,降低单笔损失风险
- 优化止盈策略,在趋势中尽可能追加利润
本策略综合运用RSI和WMA两个指标判断趋势方向,以中长线博取主要趋势的利润。同时利用资金管理和止盈策略控制风险,具有一定的实战价值。但参数设置和止损机制都需要不断测试和优化,才能获得更好的效果。建议投资者在实盘中审时度势,必要时手工干预,始终做到风险可控。
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This strategy is based on two well-known indicators: Relative Strength Index (RSI) and Weighted Moving Average (WMA). It identifies market trend and follows its direction. RSI judges overbought/oversold levels, WMA determines price trend. The combination of both can filter out irrelevant signals effectively and improve profitability. This is a medium/long-term strategy, coupled with money management method to adjust position size based on gain/loss.
RSI is one of the best-known overbought/oversold indicators. Its formula is:
Where AvgGain is the average of days that close is above open over past x days, AvgLoss is the average of absolute value of days that close is below open over past x days.
This strategy sets RSI period as 20 to judge the trend. RSI above 60 generates long signal, RSI below 40 generates short signal.
Compared with SMA, WMA weights recent prices more heavily. Its formula is:
Where w is the weight, w grows exponentially with increasing i. This strategy uses following weight formula:
$$w = \begin{cases} 100/(4+(n-4)1.3), & i <= 3 \ 1.3w, & i > 3 \end{cases}$$
Namely the weight is equal in last 3 days, and grows 1.3 times every 1 day backward. This highlights influence of recent prices.
The WMA length in this strategy is 20.
Long signal: RSI > 60 and 20-day ROC of WMA < -1 Short signal: RSI < 40 and 20-day ROC of WMA > 1
Where 20-day ROC of WMA is calculated as:
- Use RSI to determine trend direction, avoid losing money in whipsaw markets
- WMA weights recent prices to reduce noise and identify major trend
- Combination of RSI and WMA ROC filters out irrelevant signals
- Multiple ATR trailing take-profit, flexible profit-taking
- Money management adjusts position size based on gain/loss, controls risk
- Improper parameter settings may increase trading frequency
- Improper stop loss setting may expand losses
- As trend following strategy, not suitable for range-bound market
- Pay attention to macro environment changes, manual intervention if necessary
- Test RSI length, WMA length, ROC threshold to find optimum parameter set
- Test different money management methods to find best position adjustment plan
- Add other indicators for further signal filtering
- Incorporate stop loss strategy to limit per trade loss risk
- Optimize take profit strategy to maximize profit during trend
This strategy combines RSI and WMA to determine trend direction, aiming to profit from major trend over medium/long term. Money management and profit taking strategies also used to control risks. It has practical value but parameter settings and stop loss mechanism need continuous testing and optimization for better results. Investors should assess situation, intervene manually if necessary, and ensure controllable risks.
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Strategy Arguments
| Argument | Default | Description |
|---|---|---|
| v_input_int_1 | 20 | (?RSI Settings)RSI Length |
| v_input_string_1 | 0 | (?MA Settings)MA Type: RWMA |
| v_input_int_2 | 20 | MA Length |
| v_input_int_3 | 60 | (?Strategy parameters)RSI Long Signal |
| v_input_int_4 | 40 | RSI Short Signal |
| v_input_float_1 | -1 | ROC MA Long Signal |
| v_input_float_2 | true | ROC MA Short Signal |
| v_input_float_3 | 5 | TP activation in multiple of ATR |
| v_input_float_4 | 3 | Trailing TP in percentage |
| v_input_int_5 | 400 | (?Money Management)Fixed Ratio Value ($) |
| v_input_int_6 | 200 | Increasing Order Amount ($) |
| v_input_1 | timestamp(1 Jan 2018 00:00:00) | (?Backtesting Period)Start Date |
| v_input_2 | timestamp(1 July 2024 00:00:00) | End Date |
Source (PineScript)
/*backtest
start: 2022-12-24 00:00:00
end: 2023-12-06 05:20:00
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, slippage=3)
//------------------------TOOL TIPS---------------------------//
t1 = "Choice between a Standard MA (SMA) or a backed-weighted MA (RWMA) which permits to minimize the impact of short term reversal. Default is RWMA."
t2 = "Value of RSI to send a LONG or a SHORT signal. RSI above 60 is a LONG signal and RSI below 40 is a SHORT signal."
t3 = "Rate of Change Value of selected MA to send a LONG or a SHORT signal. By default : ROC MA below -1 is a LONG signal and ROC MA above 1 is a SHORT signal"
t4 = "Threshold value to trigger trailing Take Profit. This threshold is calculated as a multiple of the ATR (Average True Range)."
t5 = "Percentage value of trailing Take Profit. This Trailing TP follows the profit if it increases, remaining selected percentage below it, but stops if the profit decreases."
t6 = "Each gain or losse (relative to the previous reference) in an amount equal to this fixed ratio will change quantity of orders."
t7 = "The amount of money to be added to or subtracted from orders once the fixed ratio has been reached."
//------------------------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", tooltip=t1)
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", tooltip=t2)
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", tooltip=t3)
//TP Activation and Trailing TP
takeProfitActivationInput = input.float(5, minval=1.0, title="TP activation in multiple of ATR", group="Strategy parameters", tooltip=t4)
trailingStopInput = input.float(3, minval=0, title="Trailing TP in percentage", group="Strategy parameters", tooltip=t5)
//Money Management
fixedRatio = input.int(defval=400, minval=1, title="Fixed Ratio Value ($)", group="Money Management", tooltip=t6)
increasingOrderAmount = input.int(defval=200, minval=1, title="Increasing Order Amount ($)", group="Money Management", tooltip=t7)
//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")
//------------------------------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 = math.abs(strategy.equity - strategy.openprofit)
strategy.initial_capital = 50000
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)
Detail
https://www.fmz.com/strategy/436501
Last Modified
2023-12-25 13:28:24