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均线先行指标短期做空策略Short-term-Bearish-Strategy-Based-on-EMA-Crossover-and-Bear-Power-Indicators.md

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Name

均线先行指标短期做空策略Short-term-Bearish-Strategy-Based-on-EMA-Crossover-and-Bear-Power-Indicators

Author

ChaoZhang

Strategy Description

IMG

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概述

本策略结合了均线先行指标和熊强力指标,形成短期看跌方向信号的组合策略。均线先行指标判断趋势,熊强力指标确定做空时机。策略适合短线操作,追踪市场调整行情。

策略原理

  1. 均线先行指标:计算2/20周期的指数移动平均线EMA,当价格低于SMA时看跌,高于时看涨。

  2. 熊强力指标:计算当日收盘价与开盘价的差值,作为“强力值”。强力值大于预设的卖出参数时为熊ish信号,-1做空;强力值小于预设买入参数时为多头信号,1做多;否则为0 持平。

  3. 结合两个指标,当均线先行指标<0 且熊强力指标<-1时生成做空信号。

  4. 根据做空信号,策略开仓做空;根据平仓信号,策略平掉头寸。可设置反转参数,将做多做空方向对调。

优势分析

  1. 均线先行指标可提前判断趋势反转点。

  2. 熊强力指标可捕捉当日强力跌势的做空时机。

  3. 组合双指标,可过滤假突破,确定较强势跌势的短线做空点。

  4. 可调参数灵活,适合不同品种及市场环境。

  5. 可反转做多做空方向,应对多空双向行情。

风险分析

  1. 均线指标存在滞后性,可能错过趋势反转最佳点位。

  2. 熊强力指标对盘整震荡市容易造成错误信号。

  3. 无法判断趋势中长线走势,存在被套风险。

  4. 需谨慎选择参数,如EMA周期过短、卖出阈值过大等都会增加假信号。

  5. 需关注重要经济数据发布,避免计划交易时间段。

优化方向

  1. 可考虑加入止损策略,降低单笔损失。

  2. 可配合动量指标等过滤器,减少较弱势跌的假信号。

  3. 可加入更长周期均线判断大趋势方向,避免逆势操作。

  4. 可优化参数设置,如自适应EMA周期,实时调整卖出阈值等。

  5. 可考虑跨时间周期组合,同时关注短中长线指标信号。

总结

本策略首先利用均线先行判断大盘走势和趋势反转点,再通过熊强力指标捕捉当日强势做空时机,形成较强势跌的短线做空策略。策略优点是简单实用,可灵活调参适应不同市场环境,且可反转做多做空方向。但也存在错过最优点位、产生假信号等风险。可通过严格的参数优化、加入过滤器及止损等进一步提高策略稳定性。

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Overview

This strategy combines the EMA crossover indicator and the bear power indicator to generate short-term bearish signals. The EMA crossover judges the trend while the bear power pinpoints the short selling timing. The strategy is suitable for short-term trading to catch market corrections.

Strategy Logic

  1. EMA Crossover: Calculates the 2/20 period exponential moving average (EMA) and generates sell signals when price is below EMA.

  2. Bear Power: Calculates the difference between the closing price and opening price of the day as the "power value". Power value greater than the sell threshold gives bearish signal (-1 for short); power value lower than the buy threshold gives bullish signal (1 for long); otherwise 0 for neutral.

  3. Combining the two indicators, short signal is generated when EMA crossover <0 and bear power <-1.

  4. The strategy opens short based on the sell signal and closes position based on the exit signal. The reverse parameter can switch the long/short directions.

Advantages

  1. EMA crossover can predict trend reversal points in advance.

  2. Bear power captures short-selling opportunities during strong intraday drops.

  3. Combining two indicators helps filter false breakouts and identify stronger bearish momentum.

  4. Flexible parameters suit different products and market environments.

  5. Reversal function adapts to two-way markets.

Risks

  1. EMA crossover may lag behind the optimal turning points.

  2. Bear power may generate false signals during range-bound consolidations.

  3. It fails to determine medium-long term trends, with risk of being trapped.

  4. Parameter tuning required as inappropriate settings like overly short EMA period or too high sell threshold could increase false signals.

  5. Pay attention to key economic events to avoid planned trading sessions.

Enhancement

  1. Consider adding stop loss to limit per trade loss.

  2. Add filters like momentum indicators to avoid weak bearish signals.

  3. Add longer period EMAs to determine major trend direction and avoid counter-trend trades.

  4. Optimize parameters like adaptive EMA period and dynamic sell threshold.

  5. Consider combining multiple timeframes to incorporate short, medium and long-term indicators.

Conclusion

This strategy first uses EMA crossover to determine the major trend and reversal points, then captures strong intraday sell-off opportunities using the bear power indicator, forming a robust short-term bearish strategy. The advantages lie in its simplicity, flexibility to adapt to different market environments, and ability to reverse long/short directions. However, risks like missing optimal points and generating false signals remain. Further improvements on parameter optimization, adding filters and stop loss could help enhance the strategy stability.

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Strategy Arguments

Argument Default Description
v_input_int_1 14 (?●═════ 2/20 EMA ═════●)Length
v_input_float_1 10 (?●═════ Bear Power ═════●)SellLevel
v_input_float_2 true BuyLevel
v_input_bool_1 false (?●═════ MISC ═════●)Trade reverse
v_input_int_2 true (?●═════ Time Start ═════●)From Day
v_input_int_3 true From Month
v_input_int_4 2005 From Year

Source (PineScript)

/*backtest
start: 2023-10-09 00:00:00
end: 2023-10-16 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
////////////////////////////////////////////////////////////
//  Copyright by HPotter v1.0 19/04/2022
// This is combo strategies for get a cumulative signal. 
//
// First strategy
// This indicator plots 2/20 exponential moving average. For the Mov 
// Avg X 2/20 Indicator, the EMA bar will be painted when the Alert criteria is met.
//
// Second strategy
//  Bear Power Indicator
//  To get more information please see "Bull And Bear Balance Indicator" 
//  by Vadim Gimelfarb. 
//
//
// WARNING:
// - For purpose educate only
// - This script to change bars colors.
////////////////////////////////////////////////////////////
EMA20(Length) =>
    pos = 0.0
    xPrice = close
    xXA = ta.ema(xPrice, Length)
    nHH = math.max(high, high[1])
    nLL = math.min(low, low[1])
    nXS = nLL > xXA or nHH < xXA ? nLL : nHH
    iff_1 = nXS < close[1] ? 1 : nz(pos[1], 0)
    pos := nXS > close[1] ? -1 : iff_1
    pos


BP(SellLevel,BuyLevel) =>
    pos = 0.0
    value =  close < open  ?  
                 close[1] > open ?  math.max(close - open, high - low): high - low: 
                     close > open ? 
                         close[1] > open ? math.max(close[1] - low, high - close): math.max(open - low, high - close): 
                             high - close > close - low ? 
                                 close[1] > open ? math.max(close[1] - open, high - low) : high - low : 
                                  high - close < close - low ? 
                                   close > open ? math.max(close - low, high - close) : open - low : 
                                      close > open ? math.max(close[1] - open, high - close) :
                                       close[1] < open ? math.max(open - low, high - close) : high - low
    pos := value > SellLevel ? -1 :
    	     value <= BuyLevel ? 1 :nz(pos[1], 0) 

    pos

strategy(title='Combo 2/20 EMA & Bear Power', shorttitle='Combo', overlay=true)
var I1 = '●═════ 2/20 EMA ═════●'
Length = input.int(14, minval=1, group=I1)
var I2 = '●═════ Bear Power ═════●'
SellLevel = input.float(10, step=0.01, group=I2)
BuyLevel = input.float(1, step=0.01, group=I2)
var misc = '●═════ MISC ═════●'
reverse = input.bool(false, title='Trade reverse', group=misc)
var timePeriodHeader = '●═════ Time Start ═════●'
d = input.int(1, title='From Day', minval=1, maxval=31, group=timePeriodHeader)
m = input.int(1, title='From Month', minval=1, maxval=12, group=timePeriodHeader)
y = input.int(2005, title='From Year', minval=0, group=timePeriodHeader)
StartTrade = time > timestamp(y, m, d, 00, 00) ? true : false
posEMA20 = EMA20(Length)
prePosBP = BP(SellLevel,BuyLevel)
iff_1 = posEMA20 == -1 and prePosBP == -1 and StartTrade ? -1 : 0
pos = posEMA20 == 1 and prePosBP == 1 and StartTrade ? 1 : iff_1
iff_2 = reverse and pos == -1 ? 1 : pos
possig = reverse and pos == 1 ? -1 : iff_2
if possig == 1
    strategy.entry('Long', strategy.long)
if possig == -1
    strategy.entry('Short', strategy.short)
if possig == 0
    strategy.close_all()
barcolor(possig == -1 ? #b50404 : possig == 1 ? #079605 : #0536b3)

Detail

https://www.fmz.com/strategy/429466

Last Modified

2023-10-17 14:00:41