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基于双均线和波动率的股票投资策略Stan-The-Man-An-Advanced-Stock-Trading-Strategy-Based-on-Dual-Moving-Average-and-Volatility.md

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Name

基于双均线和波动率的股票投资策略Stan-The-Man-An-Advanced-Stock-Trading-Strategy-Based-on-Dual-Moving-Average-and-Volatility

Author

ChaoZhang

Strategy Description

IMG [trans]

概述

本策略基于双均线和相对强度指标,结合股票的历史波动率,实现股票的自动买入和卖出。策略优点是实现了长线和短线结合,能够有效控制风险。但是也存在一定的改进空间,比如可以考虑加入止损机制。

策略原理

策略使用150周 linea均线和50日线快速均线组成的双均线系统,以及20日线最快均线。当价格上穿150周线时认为行情start上行,当价格下穿50日线时认为行情开始下行。这样可以实现在行情上行中追涨杀跌,在下行中随时止损。

此外,策略还使用了年化波动率最高价和相对强度指标来确定具体的买入时机。只有当收盘价超过年化波动率计算的最高价,并且相对强度指标为正时,才会发出买入信号。

策略优势

  1. 使用双均线系统,能够有效判断主要趋势的变化,实现追涨杀跌
  2. 波动率指标和强度指标的加入,可以避免在震荡行情中随波逐流
  3. 20日快速均线的加入,可以更快止损

策略风险

  1. 存在一定的滞后,无法快速止损
  2. 没有设置止损位,容易出现较大亏损
  3. 缺乏参数优化,参数设置比较主观

为了解决风险,可以设置止损位,或者使用ATR指标的倍数作为止损幅度。此外可以通过更严格的回测来优化参数。

策略优化方向

  1. 增加止损机制
  2. 使用参数优化方法找到最优参数 3.考虑加入其它指标过滤信号,例如成交量指标等
  3. 可以考虑将策略打造成多因子模型,结合更多指标

总结

本策略总体来说是比较保守的股票投资策略。使用双均线判断主要趋势,并结合波动率和强度指标进场,可以有效过滤假突破。快速均线的加入也使止损更加快速。但是策略可以进一步优化,例如加入止损机制,使用参数优化等手段。总的来说,本策略适合长线持有股票的投资者使用。

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Overview

This strategy utilizes dual moving average system and relative strength index, combined with historical volatility of the stock, to automate buy and sell signals for stock trading. The advantage is that it combines both long-term and short-term techniques to effectively control risks. However, there are still rooms for improvement, for example a stop loss mechanism could be added.

Strategy Logic

The strategy leverages 150-week moving average and 50-day fast moving average to form a dual MA system. It uses 20-day ultra fast MA as well. When price crosses above 150-week MA, it signals an uptrend start. When price crosses below 50-day MA, it signals a downtrend. This allows us to buy on the way up and sell on the way down.

In addition, the strategy also uses annualized highest price based on volatility and relative strength index to determine specific entry points. It only sends buy signals when close price is above the max price calculated from volatility and RSI is positive.

Advantages

  1. The dual MA system can effectively identify trend changes for chasing upside and stopping downside.

  2. The volatility measure and RSI ensures we don't get whipsawed in sideway markets.

  3. The 20-day fast MA allows quicker stop loss.

Risks

  1. There is some laginess, unable to realize stop loss quickly.

  2. No stop loss is set, could lead to large losses.

  3. Lack of parameter optimization, parameters set rather arbitrary.

To mitigate the risks, stop loss can be added, or use ATR multiples as stop loss percentage. Parameter optimization through more rigorous backtesting can also help.

Enhancement Opportunities

  1. Add stop loss mechanism
  2. Find optimal parameters through optimization
  3. Consider adding other filters like volume
  4. Could build it into a multifactor model with more factors

Summary

In summary, this is a rather conservative stock investing strategy. Using dual MA system to gauge overall trend, combining with volatility and strength measures to time entry, it can effectively filter out false breakouts. The fast MA also allows quick exits. However, the strategy can be further improved by adding stop loss, parameter optimization etc. Overall it suits long-term stock investors.

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Strategy Arguments

Argument Default Description
v_input_1 BTC_USDT:swap Comparative Symbol
v_input_2 50 Period
v_input_3 50 Fast MA
v_input_4 150 Slow MA
v_input_5 20 Fastest MA

Source (PineScript)

/*backtest
start: 2023-12-12 00:00:00
end: 2023-12-20 00:00:00
period: 1m
basePeriod: 1m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
//Relative Strength
strategy("Stan my man", overlay=true)
comparativeTickerId = input("BTC_USDT:swap",  title="Comparative Symbol")
l = input(50, type=input.integer, minval=1, title="Period")
baseSymbol = security(syminfo.tickerid, timeframe.period, close)
comparativeSymbol = security(comparativeTickerId, timeframe.period, close)
hline(0, color=color.black, linestyle=hline.style_dotted)
res = baseSymbol / baseSymbol[l] /(comparativeSymbol / comparativeSymbol[l]) - 1
plot(res, title="RS", color=#1155CC)

//volume ma
vol1 = sma(volume,20)
// 30 week ma
ema1 = ema(close, 150)
//consolidation
h1 = highest(high[1],365)

fastPeriod = input(title="Fast MA", type=input.integer, defval=50)
slowPeriod = input(title="Slow MA", type=input.integer, defval=150)
fastestperiod = input(title="Fastest MA", type=input.integer, defval=20)

fastEMA = ema(close, fastPeriod)
slowEMA = ema(close, slowPeriod)
fastestEMA = ema(close, fastestperiod)

monitorStrategy = close < close[20]


// trade conditions
buytradecondition1 = close >ema1 and res>0 and volume> 1.5*vol1 and close > h1
buytradecondition2 = close > fastEMA  and volume> 1.5* vol1 
selltradecondition1  = close< 0.95 * fastEMA 
selltradecondition2  = close< 0.90 * open

if (buytradecondition1)
    strategy.entry("long",strategy.long,alert_message ="Seems ready to Buy")
    alert("Buy Alert Price (" + tostring(close) + ") crossed over Slow moving average",alert.freq_all)
    
if (buytradecondition2)
    strategy.entry("long",strategy.long,alert_message ="Seems ready to Buy")
    alert("Buy Alert Price (" + tostring(close) + ") crossed over fast moving average",alert.freq_all)
    
if (selltradecondition1)
    strategy.close("long",alert_message ="Seems ready to Sell")
    alert("Sell Alert Price (" + tostring(close) + ") crossed down fast moving average",alert.freq_all)
    
if (selltradecondition2)
    strategy.close("long",alert_message ="Seems ready to Sell")
    alert("Sell Alert Price (" + tostring(close) + ") crossed down 10% below open price  ",alert.freq_all)

//alertcondition(buytradecondition1,title ="BuySignal", message ="Price Crossed Slow Moving EMA ")

plot(fastEMA, color=color.navy)
plot(slowEMA, color=color.fuchsia)
plot(fastestEMA, color=color.green)

Detail

https://www.fmz.com/strategy/435970

Last Modified

2023-12-20 14:54:41