200 lines
7.1 KiB
Markdown
200 lines
7.1 KiB
Markdown
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> Name
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基于波浪趋势的量化交易策略Wave-Trend-Based-Quantitative-Trading-Strategy
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> Author
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ChaoZhang
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> Strategy Description
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[trans]
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### 概述
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本策略基于波浪趋势指标设计。波浪趋势指标结合价格通道和平均线,可以有效识别市场趋势,发出买入和卖出信号。本策略通过设置波浪趋势的超买超卖线,在指标线突破关键线位时,进行买入或卖出操作。
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### 策略原理
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1. 计算价格的三角移动平均线ap,以及ap的指数移动平均线esa。
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2. 计算ap和esa的绝对差值的指数移动平均线d。
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3. 得到波动指标ci。
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4. 计算ci的n2周期平均线,得到波浪趋势指标wt1。
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5. 设置超买线和超卖线。
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6. 当wt1上穿超卖线时,做多;当wt1下穿超买线时,做空。
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### 优势分析
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1. 波浪趋势指标突破超买超卖线,可以有效捕捉市场趋势的转折点,精确做出买卖决策。
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2. 结合价格通道和均线理论,指标不会产生频繁信号。
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3. 可任意时间周期使用,适用于多种交易品种。
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4. 指标参数可调节,用户体验良好。
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### 风险及解决
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1. 大幅震荡市场中,指标会产生错误信号,风险较大。可适当缩短持仓周期,或结合其他指标过滤信号。
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2. 未考虑仓位管理和止损机制,存在亏损风险。可设置仓位规模和移动止损来控制风险。
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### 优化方向
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1. 可以考虑与其他指标组合使用,如KDJ、MACD等,形成交易组合,提高策略稳定性。
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2. 可以设计自动止损机制,如跟踪止损、转速线止损等,控制单笔亏损。
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3. 可以结合深度学习算法,通过回测数据训练,自动优化参数,提高策略胜率。
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### 总结
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本策略基于波浪趋势指标,判断超买超卖情况识别趋势,是一种有效的趋势跟踪策略。相比短期指标,波浪趋势指标可减少错误信号,提高稳定性。结合仓位管理和止损,该策略可以获得稳定收益。通过参数和模型调优,策略效果还可进一步提升。
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### Overview
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This strategy is designed based on the Wave Trend indicator. The Wave Trend indicator combines price channel and moving average to effectively identify market trends and generate trading signals. This strategy enters long or short positions when the Wave Trend line crosses over key levels representing overbought or oversold status.
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### Strategy Logic
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1. Calculate the triangular moving average ap of price, as well as the exponential moving average esa of ap.
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2. Calculate the exponential moving average d of absolute difference between ap and esa.
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3. Derive the volatility indicator ci.
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4. Compute the n2 period moving average of ci to get the Wave Trend indicator wt1.
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5. Set overbought and oversold threshold lines.
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6. Go long when wt1 crosses above oversold line, go short when wt1 crosses below overbought line.
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### Advantage Analysis
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1. Wave Trend breaks of overbought/oversold levels effectively catch trend reversal points and generate accurate trading signals.
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2. Combining price channel and moving average theories, the indicator avoids frequent false signals.
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3. Applicable to all timeframes and variety of trading instruments.
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4. Customizable parameters provide good user experience.
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### Risks and Solutions
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1. Significant whipsaws can cause bad signals, high risk. Can use shorter holding periods or combine with other indicators for signal filtering.
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2. No position sizing and stop loss mechanisms, risks of losses. Can set fixed position size rules and moving stops.
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### Optimization Directions
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1. Consider combining with other indicators like KDJ and MACD to form strategy combos, enhancing stability.
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2. Design automatic stop loss like trailing stops, volatility stops to limit per trade loss.
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3. Utilize machine learning algorithms on historical data to auto tune parameters and improve strategy performance.
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### Conclusion
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This strategy identifies trends and overbought/oversold levels using Wave Trend indicator, forming an effective trend following strategy. Compared to short-term oscillators, Wave Trend avoids false signals and provides better stability. With proper risk control methods, it can achieve steady profits. Further performance boost can be expected from parameters and model tuning.
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[/trans]
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> Strategy Arguments
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|Argument|Default|Description|
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|----|----|----|
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|v_input_1|10|Channel Length|
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|v_input_2|21|Average Length|
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|v_input_3|70|Over Bought|
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|v_input_4|-30|Over Sold |
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|v_input_5|true|From Day|
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|v_input_6|true|From Month|
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|v_input_7|2001|From Year|
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|v_input_8|true|To Day|
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|v_input_9|12|To Month|
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|v_input_10|2020|To Year|
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|v_input_11|true|Long|
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|v_input_12|true|Short|
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> Source (PineScript)
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``` pinescript
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/*backtest
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start: 2023-11-20 00:00:00
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end: 2023-11-27 00:00:00
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period: 1m
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basePeriod: 1m
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exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
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*/
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//@author SoftKill21
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//@version=4
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strategy(title="WaveTrend strat", shorttitle="WaveTrend strategy")
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n1 = input(10, "Channel Length")
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n2 = input(21, "Average Length")
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Overbought = input(70, "Over Bought")
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Oversold = input(-30, "Over Sold ")
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// BACKTESTING RANGE
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// From Date Inputs
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fromDay = input(defval = 1, title = "From Day", minval = 1, maxval = 31)
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fromMonth = input(defval = 1, title = "From Month", minval = 1, maxval = 12)
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fromYear = input(defval = 2001, title = "From Year", minval = 1970)
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// To Date Inputs
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toDay = input(defval = 1, title = "To Day", minval = 1, maxval = 31)
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toMonth = input(defval = 12, title = "To Month", minval = 1, maxval = 12)
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toYear = input(defval = 2020, title = "To Year", minval = 1970)
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// Calculate start/end date and time condition
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DST = 1 //day light saving for usa
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//--- Europe
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London = iff(DST==0,"0000-0900","0100-1000")
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//--- America
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NewYork = iff(DST==0,"0400-1500","0500-1600")
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//--- Pacific
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Sydney = iff(DST==0,"1300-2200","1400-2300")
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//--- Asia
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Tokyo = iff(DST==0,"1500-2400","1600-0100")
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//-- Time In Range
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timeinrange(res, sess) => time(res, sess) != 0
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london = timeinrange(timeframe.period, London)
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newyork = timeinrange(timeframe.period, NewYork)
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startDate = timestamp(fromYear, fromMonth, fromDay, 00, 00)
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finishDate = timestamp(toYear, toMonth, toDay, 00, 00)
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time_cond = true //and (london or newyork)
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ap = hlc3
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esa = ema(ap, n1)
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d = ema(abs(ap - esa), n1)
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ci = (ap - esa) / (0.015 * d)
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tci = ema(ci, n2)
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wt1 = tci
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wt2 = sma(wt1,4)
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plot(0, color=color.gray)
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plot(Overbought, color=color.red)
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plot(Oversold, color=color.green)
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plot(wt1, color=color.green)
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longButton = input(title="Long", type=input.bool, defval=true)
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shortButton = input(title="Short", type=input.bool, defval=true)
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if(longButton==true)
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strategy.entry("long",1,when=crossover(wt1,Oversold) and time_cond)
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strategy.close("long",when=crossunder(wt1, Overbought))
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if(shortButton==true)
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strategy.entry("short",0,when=crossunder(wt1, Overbought) and time_cond)
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strategy.close("short",when=crossover(wt1,Oversold))
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//strategy.close_all(when= not (london or newyork),comment="time")
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if(dayofweek == dayofweek.friday)
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strategy.close_all(when= timeinrange(timeframe.period, "1300-1400"), comment="friday")
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```
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> Detail
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https://www.fmz.com/strategy/433575
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> Last Modified
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2023-11-28 16:17:31
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