Skip to content

Latest commit

 

History

History
279 lines (198 loc) · 8.13 KB

趋势回调微调策略Mini-Pullback-Supertrend-Strategy.md

File metadata and controls

279 lines (198 loc) · 8.13 KB
Raw

Name

趋势回调微调策略Mini-Pullback-Supertrend-Strategy

Author

ChaoZhang

Strategy Description

[trans]

概述

该策略旨在捕捉趋势中的小回调,在回调结束时开仓做多,以获利。它综合运用EMA均线、MACD指标、RSI指标等技术指标判断趋势和回调结束时机,同时利用ATR指标设置止损止盈价格。

原理

该策略首先计算EMA均线、MACD指标和RSI指标,以判断目前的趋势方向和力度。

它运用3条EMA均线(短期21周期、中期50周期、长期200周期),当短期均线上穿中长两条时,判断为上升趋势。

MACD指标判断趋势力度,MACD线或histo柱上穿0轴时,认为上升趋势转强。

RSI指标判断是否过热和超卖,RSI值上穿50时,判断回调可能结束。

然后利用SuperTrend指标判断具体的回调买点。当SuperTrend从下向上翻转时,产生买入信号。

最后,根据ATR指标设定回撤止损和盈利止盈的价格。

优势

  • 利用多指标组合判断,使交易信号更可靠。
  • 捕捉趋势中的短线机会,具有高胜率。
  • 设置止损止盈机制,有效控制风险。

风险

  • 回调时间过长,可能造成亏损扩大。
  • 多指标组合,参数设置较复杂,需要反复测试优化。
  • 止损设置过于宽松,亏损可能扩大。

风险管理措施:

  • 优化参数,确保指标顺势使用。
  • 适当调整止损点,防止过大亏损。
  • 避免回调时间过长的股票。

优化方向

  • 测试不同参数组合,找到指标最佳状态值。
  • 结合股票的日内波动情况,调整止损止盈设定。
  • 添加量价指标,避免量能不足情况。

总结

该策略综合运用多种技术指标判断趋势和回调,具有较强的可靠性。通过严格的止损机制控制风险,回撤处置及时。在持续调整参数和股票池的基础上,可以获得较好的回报。

||

Overview

This strategy aims to capture small pullbacks in a trend and go long when the pullback finishes to profit. It uses a combination of technical indicators like EMA, MACD, RSI to identify the trend and end of pullbacks. It also uses ATR to set stop loss and take profit prices.

Principles

The strategy first calculates EMA, MACD and RSI to determine current trend direction and strength.

It uses 3 EMAs (21-period short, 50-period medium and 200-period long). When short EMA crosses above medium and long EMAs, it signals an uptrend.

MACD judges trend strength. When MACD line or histogram crosses above 0 line, it shows uptrend strengthening.

RSI indicates whether overbought/oversold. RSI crossing above 50 suggests pullback may end.

Then SuperTrend indicator identifies specific buy point of pullback. Its flip from down to up gives buy signal.

Finally, stop loss and take profit are set based on ATR.

Advantages

  • More reliable signals using multiple indicator combo.
  • Catch short-term opportunities in trends with high win rate.
  • Effective risk control with stop loss/take profit.

Risks

  • Prolonged pullback may lead to extended losses.
  • Multiple indicators make parameter tuning complex.
  • Stop loss too loose may enlarge losses.

Risk management:

  • Optimize parameters for indicator alignment.
  • Adjust stop loss properly against big losses.
  • Avoid stocks with prolonged pullbacks.

Optimization

  • Test different parameter combinations for best indicator values.
  • Adjust stop loss/take profit based on stock's daily fluctuation.
  • Add volume indicator to avoid low volume cases.

Conclusion

The strategy combines multiple indicators reliably for trend and pullback identification. Strict stop loss mechanism controls risk and allows timely liquidation. With persistent parameter and universe tuning, it can achieve good returns.

[/trans]

Strategy Arguments

Argument Default Description
v_input_source_1_close 0 EMA Source: close
v_input_int_1 21 EMA 1 len
v_input_1 50 EMA 2 len
v_input_2 200 EMA 3 len
v_input_source_2_close 0 MACD Source: close
v_input_int_2 12 MACD Fast
v_input_int_3 26 MACD Signal
v_input_int_4 9 MACD Histogram
v_input_source_3_close 0 RSI Source: close
v_input_int_5 14 RSI Len
v_input_int_6 3 K
v_input_int_7 3 D
v_input_int_8 14 RSI Length
v_input_int_9 14 Stochastic Length
v_input_3_close 0 RSI Source Stoch: close
v_input_bool_1 true Use EMA Filter
v_input_bool_2 true Use RSI Filter
v_input_bool_3 true Use MACD Filter
v_input_int_10 14 ATR Period
v_input_source_4_close 0 Supertrend Source: close
v_input_float_1 2 ATR Multiplier
v_input_bool_4 true Change ATR Calculation Method ?
v_input_bool_5 true Show Buy/Sell Signals ?
v_input_bool_6 true Highlighter On/Off ?
v_input_int_11 5 Bars from cross to signal

Source (PineScript)

/*backtest
start: 2022-10-06 00:00:00
end: 2023-10-12 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy(title="pullb", overlay = true, initial_capital = 10000, default_qty_value = 100, default_qty_type = strategy.percent_of_equity)

//variables

///emas var
ema_src = input.source(close, "EMA Source")
ema_1 = input.int(21, 'EMA 1 len')
ema_2 = input(50, 'EMA 2 len')
ema_3 = input(200, 'EMA 3 len')

///macd var
mac_src = input.source(close, "MACD Source")
mac_1 = input.int(12, 'MACD Fast')
mac_2 = input.int(26, 'MACD Signal')
mac_3 = input.int(9, 'MACD Histogram')

///rsi var
rsi_src = input.source(close, "RSI Source")
rsi_len = input.int(14, 'RSI Len')

///stoch var
smoothK = input.int(3, "K", minval=1)
smoothD = input.int(3, "D", minval=1)
lengthRSI = input.int(14, "RSI Length", minval=1)
lengthStoch = input.int(14, "Stochastic Length", minval=1)
stoch_src = input(close, title="RSI Source Stoch")

//usage variables
ema_b = input.bool(true, "Use EMA Filter")
rsi_b = input.bool(true, "Use RSI Filter")
macd_b = input.bool(true, "Use MACD Filter")
//stoch_b = input(title="Use STOCH Filter", type=bool, defval=true)

//emaas
ema1 = ta.ema(ema_src, ema_1)
ema2 = ta.ema(ema_src, ema_2)
ema3 = ta.ema(ema_src, ema_3)

//macd
[macdLine, signalLine, histLine] = ta.macd(mac_src, mac_1, mac_2, mac_3)

//rsi
rsi = ta.rsi(rsi_src, rsi_len)

//stoch
rsi1 = ta.rsi(stoch_src, lengthRSI)
k = ta.sma(ta.stoch(rsi1, rsi1, rsi1, lengthStoch), smoothK)
d = ta.sma(k, smoothD)

//supertrend
Periods = input.int(14, "ATR Period")
src_st = input.source(close, "Supertrend Source")
Multiplier = input.float(2.0 , "ATR Multiplier")
changeATR= input.bool(true, "Change ATR Calculation Method ?")
showsignals = input.bool(true, "Show Buy/Sell Signals ?")
highlighting = input.bool(true, "Highlighter On/Off ?")
atr2 = ta.sma(ta.tr, Periods)
atr3= changeATR ? ta.atr(Periods) : atr2
up=src_st-(Multiplier*atr3)
up1 = nz(up[1],up)
up := close[1] > up1 ? math.max(up,up1) : up
dn=src_st+(Multiplier*atr3)
dn1 = nz(dn[1], dn)
dn := close[1] < dn1 ? math.min(dn, dn1) : dn
trend = 1
trend := nz(trend[1], trend)
trend := trend == -1 and close > dn1 ? 1 : trend == 1 and close < up1 ? -1 : trend
buySignal = trend == 1 and trend[1] == -1
sellSignal = trend == -1 and trend[1] == 1

//conditions
///buy
rsi_cond_b = if rsi_b
    rsi >= 50
else 
    true

macd_cond_b = if macd_b
    (histLine >= 0 or histLine < histLine[1])
else
    true
ema_cond_b = if ema_b
    (ema1 > ema2 and ema2 > ema3)
else 
    true

look_for = input.int(5, "Bars from cross to signal")

stoch_signal_sum = 0
for i = 0 to (look_for)
    if k[i] > d[i] and k[i + 1] < d[i + 1] and (k[i + 1] < 20 and d[i + 1] < 20)
        stoch_signal_sum := stoch_signal_sum + 1
        
stoch_cond_b = if stoch_signal_sum > 0
    if k > 80 and d > 80
        false
    else
        true
else
    false


sup_cond_b = buySignal

buy_sig = (rsi_cond_b and macd_cond_b and ema_cond_b and stoch_cond_b and sup_cond_b)

tp_b = close + (ta.atr(14) * 3)
sl_b = close - (ta.atr(14) * 1.5)

if (buy_sig)
    strategy.entry("long", strategy.long)
    strategy.exit("exit", "long", stop = sl_b, limit = tp_b)
plot(tp_b)
plot(sl_b)

Detail

https://www.fmz.com/strategy/429149

Last Modified

2023-10-13 15:49:29