請問這個策略有偷價或者未來函數行為嗎？回測效果很好

作者：開拓者 TB 來源：cxh99.com 發布時間：2016年04月10日

咨詢內容： import pandas as pd
import numpy as np

def init(context):
context.s1 = '000001.XSHG'
context.max_num_stocks = 40
context.days = 0
context.period_days = 1
context.relative_strength_6m = {}

def period_passed(context):
return context.days % context.period_days == 0

def before_trading(context):
context.days += 1
if not period_passed(context):
      return

dofilter(context)
update_universe(context.fundamental_df.columns.values)

def dofilter(context):

fundamental_df = get_fundamentals(
      query(fundamentals.eod_derivative_indicator.market_cap)
      .order_by(fundamentals.eod_derivative_indicator.market_cap.asc())
      .limit(context.max_num_stocks)
)

#Update context
context.stocks = [stock for stock in fundamental_df]
context.fundamental_df = fundamental_df

def rebalance(context, bar_dict):

for stock in context.portfolio.positions:
      if stock not in context.fundamental_df:
         order_target_percent(stock, 0)

context.stocks = [stock for stock in context.stocks
                  if stock in bar_dict and bar_dict[stock].is_trading and context.relative_strength_6m[stock] <-0.5]

if len(context.stocks) == 0:
      return

weight = 1.0/len(context.stocks)

for stock in context.stocks:
      order_target_percent(stock, weight)

def handle_bar(context, bar_dict):

his = history(10, '1d', 'close')['000001.XSHG']

if period_passed(context):
      if his[9]/his[8]< 0.97:
         if len(context.portfolio.positions)>0:
            for stock in context.portfolio.positions.keys():
                  order_target_percent(stock, 0)
         return

if not period_passed(context):
      return

compute_relative_strength(context,bar_dict)
rebalance(context, bar_dict)

def compute_relative_strength(context,bar_dict):

prices = history (150, '1d', 'close')

#過去六個月的價格變化率
pct_change = (prices.ix[149] - prices.ix[19]) / prices.ix[19]
#print(prices.ix[19])
#print(pct_change)
priceofbase = history (150, '1d', 'close')[context.s1]
pct_changeforbase = (priceofbase.ix[149] - priceofbase.ix[19]) / priceofbase.ix[19]
pct_change = pct_change - pct_changeforbase
print(pct_change.index)
print(bar_dict)
if pct_changeforbase != 0:
      pct_change = pct_change / abs(pct_changeforbase)
context.relative_strength_6m = pct_change
TB技術人員： 你這個代碼都不是TB的，怎么回測的？
TB客服： 本帖最后由 bahuang 于 2016-2-26 08:40 編輯

這里也有人用python

請問這個策略有偷價或者未來函數行為嗎？回測效果很好

請問這個策略有偷價或者未來函數行為嗎？回測效果很好