可以帮助你的圣杯策略：Ma8

1# 屁话

偶然发现的一款策略，能神奇的不改参数适应市场
并且2018年到现在不改参数都是盈利的
比所谓的拟合策略强不知道多少倍，哈哈

后来这个策略作为一个因子伴随了我几个月的时间用于实盘

总比一直放在收藏夹吃灰，还不如分享给你们让我赚点流量
仅供分享思路，真要实盘赚钱，你要做的还很多
仅供分享思路，真要实盘赚钱，你要做的还很多

2# 原理

开仓：连续8根收盘价大于均线，最后一根收盘价小于均线
平仓：持仓3根k线，或突破最高点，或ATR，或固定止盈止损

3# 回测

4# 源码

原版：
https://www.tradingview.com/script/gl17fzdf-8-Day-Extended-Runs/

自己修改的：

import talib
import pandas as pd
from main.zhibiao import *

seting =                                                  {
    "备注": "禁用",
    "name": "Ma8",
    "symbol": "BTCUSDT_1h_Buy",
    "kTime": "1h",
    "ma_len": 29,
    "ma_type": "lsma",
    "ma_src": "o+h+l+c",
    "pianli": 14,
    "pingcang": 4,
    "tupo": 34,
    "atr_len": 43,
    "atr_mult": 2.871,
    "atr_type": "rma",
    "buy": 1,
    "buyZhiying": 96.216,
    "buyZhisun": 12.06,
    "sell": 0,
    "sellZhiying": 0,
    "sellZhisun": 0,
    "kai": 100
}

"""
MA连续偏离8次入场，十根K线后出场
"""
def Ma8(r, df, seting):

    c = len(df)
    df['ma_src'] = GetSrc(r, seting['ma_src'])
    df['ma'] = GetMa(df['ma_src'], seting['ma_len'], seting['ma_type'])
    df['atr'] = ATR(r, seting['atr_len'], seting['atr_type'])
    df['zhisun'] = 0.0
    if seting['buy']:
        df['h'] = df['High'].rolling(seting['tupo']).max()
        df['l2'] = df['Low'].rolling(seting['pianli']).min()

    if seting['sell']:
        df['l'] = df['Low'].rolling(seting['tupo']).min()
        df['h2'] = df['High'].rolling(seting['pianli']).max()

    df['da'] = 0
    df['xiao'] = 0
    df['buy'] = 0
    # df['pingtime'] = 0
    for i in range(c):
        if i > seting['ma_len']:
            if df['Close'][i] > df['ma'][i] and (df['Close'][i-1] < df['ma'][i-1] or df['da'][i-1]):
                df['da'].values[i] = df['da'][i-1] + 1

            if df['Close'][i] < df['ma'][i] and (df['Close'][i-1] > df['ma'][i-1] or df['xiao'][i-1]):
                df['xiao'].values[i] = df['xiao'][i-1] + 1

    preSide = 0
    preZhisun = 0
    preZhisunBili = 0
    preZhiYingBili = 0

    buy = 0
    sell = 0
    for i in range(c):
        if i > seting['ma_len'] and i+1 < c:
            if seting['buy']:
                #连续多少根 大于 均线之上
                if df['Close'][i] < df['ma'][i] and df['da'][i-1] > seting['pianli']: #and df['Close'][i] > df['l2'][i]
                    df['side'].values[i] = 'BUY'

                    if preSide != 'BUY':
                        preSide = 'BUY'
                        preZhisun = df['Open'][i+1] - seting['atr_mult'] * df['atr'][i]
                        preZhisunBili = GetRoeJia(-seting['buyZhisun'], {'liang': 1, 'jiage': df['Open'][i+1]})
                        preZhiYingBili = GetRoeJia(seting['buyZhiying'], {'liang': 1, 'jiage': df['Open'][i+1]})

                    # if not buy:
                    #     df['pingtime'].values[i] = df['Time'][i] + (df['Time'][1] - df['Time'][0]) * (seting['pingcang'] + 2)
                        # df['pingtime'].values[i] = GetTime(df['pingtime'].values[i], '%Y-%m-%d %H:%M')

                    buy += 1

                elif buy:
                    buy += 1

                if buy > seting['pingcang']+1 or (seting['tupo'] and df['Close'][i] >= df['h'][i-1]):
                    df['close'].values[i] = 'BUY'
                    buy = 0
                    if preSide == "BUY":
                        preSide = 0

                df['buy'].values[i] = buy

            if seting['sell']:
                if df['Close'][i] > df['ma'][i] and df['xiao'][i-1] > seting['pianli']: # and df['Close'][i] < df['h2'][i]
                    df['side'].values[i] = 'SELL'

                    if preSide != 'SELL':
                        preSide = 'SELL'
                        preZhisun = df['Open'][i+1] + seting['atr_mult'] * df['atr'][i]
                        preZhisunBili = GetRoeJia(-seting['sellZhisun'], {'liang': -1, 'jiage': df['Open'][i+1]})
                        preZhiYingBili = GetRoeJia(seting['sellZhiying'], {'liang': -1, 'jiage': df['Open'][i+1]})

                    # if not sell:
                    #     df['pingtime'].values[i] = df['Time'][i] + (df['Time'][1] - df['Time'][0]) * (seting['pingcang'] + 2)
                        # df['pingtime'].values[i] = GetTime(df['pingtime'].values[i], '%Y-%m-%d %H:%M')
                    sell += 1

                elif sell:
                    sell += 1

                if sell > seting['pingcang']+1 or (seting['tupo'] and df['Close'][i] <= df['l'][i-1]):
                    df['close'].values[i] = 'SELL'
                    sell = 0
                    if preSide == "SELL":
                        preSide = 0

            df['zhisun'].values[i] = preZhisun
            if (preSide == 'BUY' and df['Low'][i] <= preZhisun) or (preSide == 'SELL' and df['High'][i] >= preZhisun) or \
               (preSide == 'BUY' and df['Low'][i] <= preZhisunBili) or (preSide == 'SELL' and df['High'][i] >= preZhisunBili) or \
               (preSide == 'BUY' and df['High'][i] >= preZhiYingBili) or (preSide == 'SELL' and df['Low'][i] <= preZhiYingBili):
                preSide = 0
                buy = 0
                sell = 0

    return df