ChaoZhang
概述
该策略是一个结合了移动平均线和动态范围过滤器的高级量化交易系统。它主要通过分析价格变动和交易量之间的关系来识别市场趋势,同时利用范围过滤器来过滤虚假信号,提高交易的准确性。策略采用了自适应的计算方法来确定市场的流动性边界,并结合了快速和慢速移动平均线来确认趋势方向。
策略原理
策略的核心逻辑基于以下几个关键计算: 1. 流动性分析: 通过计算成交量与价格变动之比来评估市场流动性,并设定动态的流动性边界。 2. 趋势确认: 使用50周期和100周期的指数移动平均线(EMA)来确认趋势方向。 3. 范围过滤: 采用50周期的采样周期和3倍的范围乘数来构建动态交易区间。 4. 信号生成: 当价格突破范围过滤器且EMA指标显示趋势一致时,生成交易信号。
策略优势
- 自适应性强: 策略能够根据市场条件动态调整参数,适应不同的市场环境。
- 信号可靠: 通过结合多个技术指标和过滤器,有效降低虚假信号。
- 风险管理完善: 集成了止损位置的自动计算,能够有效控制风险。
- 回测功能完整: 包含了详细的回测设置,便于策略优化。
策略风险
- 参数敏感性: 策略的多个参数需要精细调整,容易过度优化。
- 滑点影响: 在高波动市场中,可能面临较大的滑点风险。
- 市场适应性: 在横盘市场中可能产生频繁的假信号。
- 资金管理: 固定资金分配方式可能不适合所有市场条件。
策略优化方向
- 参数自适应: 可以引入自适应参数调整机制,使参数能够根据市场状态自动调整。
- 市场状态识别: 添加市场状态判断模块,在不同市场条件下采用不同的交易策略。
- 资金管理优化: 引入动态仓位管理,根据市场波动性调整交易规模。
- 信号过滤增强: 可以添加更多的技术指标来过滤假信号。
总结
该策略通过结合流动性分析、趋势跟踪和范围过滤器,构建了一个完整的量化交易系统。它的优势在于能够自适应市场变化并提供可靠的交易信号,但同时也需要注意参数优化和风险管理。通过持续优化和改进,该策略有望在不同市场环境下都能保持稳定的表现。
策略源码
/*backtest
start: 2019-12-23 08:00:00
end: 2024-12-15 08:00:00
period: 1d
basePeriod: 1d
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=6
strategy("Killer Coin V2 + Range Filter Strategy", shorttitle="KC-RF Strategy", overlay=true
)
// === INPUT BACKTEST RANGE ===
useDate = input(true, title='---------------- Use Date ----------------', group="Backtest Settings")
FromMonth = input.int(7, title="From Month", minval=1, maxval=12, group="Backtest Settings")
FromDay = input.int(25, title="From Day", minval=1, maxval=31, group="Backtest Settings")
FromYear = input.int(2019, title="From Year", minval=2017, group="Backtest Settings")
ToMonth = input.int(1, title="To Month", minval=1, maxval=12, group="Backtest Settings")
ToDay = input.int(1, title="To Day", minval=1, maxval=31, group="Backtest Settings")
ToYear = input.int(9999, title="To Year", minval=2017, group="Backtest Settings")
start = timestamp(FromYear, FromMonth, FromDay, 00, 00)
finish = timestamp(ToYear, ToMonth, ToDay, 23, 59)
window() => time >= start and time <= finish
// === KILLER COIN V2 INPUTS ===
outlierThreshold = input.int(10, "Outlier Threshold Length", group="Killer Coin Settings")
fastMovingAverageLength = input.int(50, "Fast MA length", group="Killer Coin Settings")
slowMovingAverageLength = input.int(100, "Slow MA length", group="Killer Coin Settings")
// === RANGE FILTER INPUTS ===
sources = input(close, "Source", group="Range Filter Settings")
isHA = input(false, "Use HA Candles", group="Range Filter Settings")
per = input.int(50, "Sampling Period", minval=1, group="Range Filter Settings")
mult = input.float(3.0, "Range Multiplier", minval=0.1, group="Range Filter Settings")
// === KILLER COIN V2 CALCULATIONS ===
priceMovementLiquidity = volume / math.abs(close - open)
liquidityBoundary = ta.ema(priceMovementLiquidity, outlierThreshold) + ta.stdev(priceMovementLiquidity, outlierThreshold)
var liquidityValues = array.new_float(5)
if ta.crossover(priceMovementLiquidity, liquidityBoundary)
array.insert(liquidityValues, 0, close)
fastEMA = ta.ema(array.get(liquidityValues, 0), fastMovingAverageLength)
slowEMA = ta.ema(array.get(liquidityValues, 0), slowMovingAverageLength)
// === RANGE FILTER CALCULATIONS ===
src = isHA ? request.security(ticker.heikinashi(syminfo.tickerid), timeframe.period, sources) : sources
// Smooth Average Range
smoothrng(x, t, m) =>
wper = (t*2) - 1
avrng = ta.ema(math.abs(x - x[1]), t)
smoothrng = ta.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
// === PLOTTING ===
// Killer Coin V2 Plots
bullColor = color.new(#00ffbb, 50)
bearColor = color.new(#800080, 50)
fastPlot = plot(fastEMA, "Fast EMA", color = fastEMA > slowEMA ? bullColor : bearColor)
slowPlot = plot(slowEMA, "Slow EMA", color = fastEMA > slowEMA ? bullColor : bearColor)
fill(fastPlot, slowPlot, color = fastEMA > slowEMA ? bullColor : bearColor)
// Range Filter Plots
filtcolor = upward > 0 ? color.new(color.lime, 0) : downward > 0 ? color.new(color.red, 0) : color.new(color.orange, 0)
filtplot = plot(filt, "Range Filter", color=filtcolor, linewidth=3)
hbandplot = plot(hband, "High Target", color=color.new(color.aqua, 90))
lbandplot = plot(lband, "Low Target", color=color.new(color.fuchsia, 90))
fill(hbandplot, filtplot, color=color.new(color.aqua, 90))
fill(lbandplot, filtplot, color=color.new(color.fuchsia, 90))
// === STRATEGY CONDITIONS ===
// Range Filter Conditions
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
// Combined Conditions
finalLongSignal = longCondition and fastEMA > slowEMA and window()
finalShortSignal = shortCondition and fastEMA < slowEMA and window()
// === PLOTTING SIGNALS ===
plotshape(finalLongSignal, "Buy Signal", text="BUY", textcolor=color.white,
style=shape.labelup, size=size.normal, location=location.belowbar,
color=color.new(color.green, 0))
plotshape(finalShortSignal, "Sell Signal", text="SELL", textcolor=color.white,
style=shape.labeldown, size=size.normal, location=location.abovebar,
color=color.new(color.red, 0))
// === STRATEGY ENTRIES ===
if finalLongSignal
strategy.entry("Long", strategy.long, stop=hband)
if finalShortSignal
strategy.entry("Short", strategy.short, stop=lband)
// === ALERTS ===
alertcondition(finalLongSignal, "Strong Buy Signal", "🚨 Buy - Both Indicators Aligned!")
alertcondition(finalShortSignal, "Strong Sell Signal", "🚨 Sell - Both Indicators Aligned!")
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