strategies/范围过滤买卖短线交易策略Range-Filter-Breakout-Short-term-Trading-Strategy.md at 87a415edf7b08065fbcbfbfefb7351cd929e4dbd

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Name

范围过滤买卖短线交易策略Range-Filter-Breakout-Short-term-Trading-Strategy

Author

ChaoZhang

Strategy Description

[trans]

概述

本策略基于价格的波动范围来判断买入和卖出时机。它计算一定周期内的价格波动范围,并以该范围作为过滤条件产生交易信号。当价格超出波动范围时产生买入或卖出信号。属于基于价格突破的短线交易策略。

策略原理

该策略的核心指标是价格的波动范围。具体计算过程为:

计算过去N周期内的最高价和最低价之差作为价格振幅
对价格振幅进行均线平滑处理,得到范围过滤器
当价格上涨超过范围过滤器时,产生买入信号
当价格下跌超过范围过滤器时,产生卖出信号

通过这种方式,可以利用价格突破波动范围来判断趋势方向, filtrate123噪音交易,获得比较清晰的交易信号。

策略优势

使用价格实体范围,容易判断突破
波动范围平滑处理,有效过滤噪声
突破型信号,易于捕捉短线趋势
交易频次较高,适合短线操作
可调参数,容易优化至不同品种

策略风险

范围突破容易出现冲高回落
需要较长历史数据计算范围
参数设置不当会过于灵敏或迟钝
无法有效控制止损,存在较大回撤
效果可能受到交易费用影响

可以通过以下措施来降低风险:

适当放宽范围过滤波动系数
优化参数,找到最佳参数组合
设置止损线止损或移动止损
适当减少交易频次,降低交易费用
根据不同品种分别测试参数

优化方向

该策略可以从以下几个方面进行优化:

测试计算范围的不同周期参数
优化范围过滤波动系数
加入MACD等指标进行二次确认
使用移动止损或追踪止损
根据具体品种不同调整参数
考虑优化仓位管理系统

总结

该策略利用价格突破范围来产生短线交易信号。这可以有效识别短期趋势机会。但也容易出现冲高回落的风险。我们可以通过参数优化,设置止损规则,加入指标过滤等方法来改进策略系统,在保留其突破识别能力的同时,控制风险、减少回撤。此外,针对不同品种特点进行参数调整也很关键。只有不断优化测试,才能使策略更稳定可靠。

Overview

This short-term trading strategy generates buy and sell signals based on the price fluctuation range. It calculates the price movement range over a period and uses that as a filter for trade signals. Signals are triggered when price breaks out of the range.

Strategy Logic

The core indicator is the price fluctuation range. The specific steps are:

Calculate the high-low range over past N periods as the price amplitude
Smooth the amplitude using moving averages to derive the range filter
A buy signal is generated when price rises above the range filter
A sell signal is generated when price drops below the range filter

This way, breakouts of the price range are used to determine trend direction and filtrate noise for cleaner signals.

Advantages

Price range easy to judge breakouts
Smoothed range effectively filters noise
Breakout signals catch short-term trends
Higher trade frequency suitable for short-term
Adjustable parameters easy to optimize

Risks

Range breakouts prone to whipsaws
Needs sufficient historical data to calculate range
Bad parameters cause oversensitivity or sluggishness
No effective stops, large drawdowns
Performance impacted by fees due to high frequency

Risks can be mitigated by:

Relaxing range filter volatility coefficient
Parameter optimization for ideal settings
Implementing stop loss or trailing stops
Reducing trade frequency to lower fees
Product-specific parameter testing

Enhancement Directions

The strategy can be improved by:

Testing different range calculation periods
Optimizing range filter volatility coefficient
Adding confirming indicators like MACD
Using moving or trailing stops
Tuning parameters specifically for each product
Optimizing position sizing system

Summary

This strategy uses price breaking out of ranges to generate short-term signals, effectively capturing temporary trends. But risks like whipsaws exist. Improvements can be made through parameter optimization, stop losses, adding filters etc. to control risks while retaining effectiveness. Fine-tuning parameters by product characteristics is also essential. Continual optimizations lead to robustness.

[/trans]

Strategy Arguments

Argument	Default	Description
v_input_1	true	---------------- Use Date ----------------
v_input_2	7	From Month
v_input_3	25	From Day
v_input_4	2019	From Year
v_input_5	true	To Month
v_input_6	true	To Day
v_input_7	9999	To Year
v_input_8_close	0	Source: close
v_input_9	false	Use HA Candles
v_input_10	50	Sampling Period
v_input_11	3	Range Multiplier
v_input_12	false	----- Use Stop Loss / Take profit -----
v_input_13	100	Stop Loss %
v_input_14	1.5	Take Profit %

Source (PineScript)

/*backtest
start: 2023-08-21 00:00:00
end: 2023-09-20 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=3
strategy(title="Range Filter Buy and Sell 5min [Strategy]", overlay=true, commission_type=strategy.commission.percent, commission_value=0.025, default_qty_type=strategy.cash, default_qty_value=10000, initial_capital=10000, slippage=0)

// === INPUT BACKTEST RANGE ===
useDate = input(true,     title='---------------- Use Date ----------------', type=bool)
FromMonth = input(defval = 7, title = "From Month", minval = 1, maxval = 12)
FromDay   = input(defval = 25, title = "From Day", minval = 1, maxval = 31)
FromYear  = input(defval = 2019, title = "From Year", minval = 2017)
ToMonth   = input(defval = 1, title = "To Month", minval = 1, maxval = 12)
ToDay     = input(defval = 1, title = "To Day", minval = 1, maxval = 31)
ToYear    = input(defval = 9999, title = "To Year", minval = 2017)
start     = timestamp(FromYear, FromMonth, FromDay, 00, 00)  // backtest start window
finish    = timestamp(ToYear, ToMonth, ToDay, 23, 59)        // backtest finish window
window()  => true  // create function "within window of time"
// === INPUT BACKTEST RANGE ===


sources = input(defval=close, title="Source")
isHA = input(false, "Use HA Candles", bool)
src = isHA ? security(heikenashi(tickerid), period, sources) : sources
// Sampling Period
// Settings for 5min chart, BTCUSDC. For Other coin, change the paremeters

per = input(defval=50, minval=1, title="Sampling Period")

// Range Multiplier

mult = input(defval=3.0, minval=0.1, title="Range Multiplier")

// Smooth Average Range

smoothrng(x, t, m)=>
    wper      = (t*2) - 1
    avrng     = ema(abs(x - x[1]), t)
    smoothrng = ema(avrng, wper)*m
    smoothrng
smrng = smoothrng(src, per, mult)

// Range Filter

rngfilt(x, r)=>
    rngfilt  = x
    rngfilt := x > nz(rngfilt[1]) ? ((x - r) < nz(rngfilt[1]) ? nz(rngfilt[1]) : (x - r)) : ((x + r) > nz(rngfilt[1]) ? nz(rngfilt[1]) : (x + r))
    rngfilt
filt = rngfilt(src, smrng)

// Filter Direction

upward   = 0.0
upward  := filt > filt[1] ? nz(upward[1]) + 1 : filt < filt[1] ? 0 : nz(upward[1])
downward = 0.0
downward := filt < filt[1] ? nz(downward[1]) + 1 : filt > filt[1] ? 0 : nz(downward[1])

// Target Bands

hband = filt + smrng
lband = filt - smrng

// Colors

filtcolor = upward > 0 ? lime : downward > 0 ? red : orange
barcolor  = (src > filt) and (src > src[1]) and (upward > 0) ? lime : (src > filt) and (src < src[1]) and (upward > 0) ? green : 
   (src < filt) and (src < src[1]) and (downward > 0) ? red : (src < filt) and (src > src[1]) and (downward > 0) ? maroon : orange

filtplot = plot(filt, color=filtcolor, linewidth=3, title="Range Filter")

// Target

hbandplot = plot(hband, color=aqua, transp=100, title="High Target")
lbandplot = plot(lband, color=fuchsia, transp=100, title="Low Target")

// Fills

fill(hbandplot, filtplot, color=aqua, title="High Target Range")
fill(lbandplot, filtplot, color=fuchsia, title="Low Target Range")

// Bar Color

//barcolor(barcolor)

// Break Outs 

longCond = na
shortCond = na
longCond := ((src > filt) and (src > src[1]) and (upward > 0)) or ((src > filt) and (src < src[1]) and (upward > 0)) 
shortCond := ((src < filt) and (src < src[1]) and (downward > 0)) or ((src < filt) and (src > src[1]) and (downward > 0))

CondIni = 0
CondIni := longCond ? 1 : shortCond ? -1 : CondIni[1]
longCondition = longCond and CondIni[1] == -1
shortCondition = shortCond and CondIni[1] == 1

//Alerts

plotshape(longCondition, title = "Buy Signal", text ="BUY", textcolor = white, style=shape.labelup, size = size.normal, location=location.belowbar, color = green, transp = 0)
plotshape(shortCondition, title = "Sell Signal", text ="SELL", textcolor = white, style=shape.labeldown, size = size.normal, location=location.abovebar, color = red, transp = 0)

//strategy.entry("Long", strategy.long, stop = hband, when = window() , comment="Long")
//strategy.entry("Short", strategy.short, stop = lband, when = window() , comment="Short")

strategy.entry("Long", strategy.long, when = longCondition and window() , comment="Long")
strategy.entry("Short", strategy.short, when = shortCondition and window() , comment="Short")



// === Stop LOSS ===
useStopLoss = input(false, title='----- Use Stop Loss / Take profit -----', type=bool)
sl_inp = input(100, title='Stop Loss %', type=float, step=0.25)/100
tp_inp = input(1.5, title='Take Profit %', type=float, step=0.25)/100
stop_level = strategy.position_avg_price * (1 - sl_inp)
take_level = strategy.position_avg_price * (1 + tp_inp)
stop_level_short = strategy.position_avg_price * (1 + sl_inp)
take_level_short = strategy.position_avg_price * (1 - tp_inp)
// === Stop LOSS ===

if useStopLoss
    strategy.exit("Stop Loss/Profit Long","Long", stop=stop_level, limit=take_level)
    strategy.exit("Stop Loss/Profit Short","Short", stop=stop_level_short, limit=take_level_short)

Detail

https://www.fmz.com/strategy/427523

Last Modified

2023-09-21 21:17:40

10 KiB Raw Blame History

概述