def main(select_stock, numOfDailySignal):
signalData = SourceDataDao.getSignalData()
#dailyQuote = SourceDataDao.getDailyQuote()
dailyQuote = SourceDataDao.getNewDailyQuote()
#参数
#每天信号数
#numOfDailySignal = 5
#初始资金
initialMV = 1000000 #1000000
#开始结束日期
#startDate = '1/8/2001'
startDate = '1/1/2004'
#endDate = '1/1/2017'
#eendDate = '5/18/2001'
endDate = '12/31/2005'
#endDate = '12/31/2002'
#endDate = '1/9/2001'
#select top 5 group by TradingDay order by Mom desc
groupedSignalData = select_stock(signalData, numOfDailySignal)
#groupedSignalData = signalData.groupby(level=StockConst.TradingDay).apply(SelectUtil.top,numOfDailySignal,StockConst.Mom,False) #False True
#当前持仓 key:innerCode value:
currHoldSet = {}
stockTradeList = []
#
capitalEntity = CapitalEntity.CapitalEntity(initialMV)
lastMV = initialMV
#netValue = 1;
#初始化每日统计表
stockStatDailyDf = pd.DataFrame(index=pd.date_range(startDate, endDate),
columns=[
'netValue', 'changePCT', 'buyCnt',
'sellCnt', 'prevHoldCnt',
'currHoldCnt', 'cannotSellCnt',
'cannotBuyCnt', 'usableCach', 'mv'
])
#初始化每日持仓表
stockHoldDailyList = []
#从信号表中取得唯一性日期
dateList = SourceDataDao.select_date_from_signal(signalData, startDate,
endDate)
for index, item in enumerate(dateList):
#for date in dateList:
#print('index:'+str(index)+' len:'+str(len(dateList)))
#信号日
signalDay = dateList[index]
# 非最后一天
if index < (len(dateList) - 1):
#交易日
tradingDay = dateList[index + 1]
tradingDayStr = DateUtil.datetime2_str(tradingDay)
#print('dateStr:'+dateStr)
# 最后一天
else:
break
#print(dateStr)
currSignalData = groupedSignalData.ix[signalDay]
if StockConst.IS_DEBUG:
print("currSignalData:" + str(len(currSignalData)))
#print(currSignalData)
# 计划买入列表
planBuyList = getPlanBuyList(currSignalData, currHoldSet)
# 计划卖出列表
planSellList = getPlanSellList(currSignalData, currHoldSet)
# 昨日持仓部分（在今日持仓中）
prevHoldList = getPrevHoldList(currSignalData, currHoldSet)
"""
if (dateStr >= '2015-01-05') & (dateStr <= '2015-01-05'):
print('-----'+dateStr+'-----')
#print(currSignalData)
#print(buyList)
print(list(currHoldSet.keys()))
for key in currHoldSet.keys():
print(str(key) + ':' + currHoldSet.get(key).openDate)
print('----------------')
"""
#dailyChangePCT = 0
cannotSellList = []
cannotBuyList = []
# 实际买入列表
actualBuyList = getActualBuyList(planBuyList, dailyQuote, tradingDay,
cannotBuyList)
# "卖出列表"中要保留的股票数
numOfToKeepInSellList = numOfDailySignal - len(actualBuyList) - len(
prevHoldList)
# 实际卖出列表
actualSellList = getActualSellList(planSellList, tradingDay,
signalData, dailyQuote,
numOfToKeepInSellList,
cannotSellList)
#1.处理实际卖出
handleSellList(tradingDay, dailyQuote, stockTradeList, currHoldSet,
capitalEntity, actualSellList)
#2.处理实际买入
handleBuyList(tradingDay, dailyQuote, stockTradeList, currHoldSet,
capitalEntity, actualBuyList)
#3.计算当日市值
currMV = calculateDailyMV(currHoldSet, capitalEntity, dailyQuote,
tradingDay, stockHoldDailyList, initialMV)
#4.个数
buyCnt = len(actualBuyList)
sellCnt = len(actualSellList)
prevHoldCnt = len(prevHoldList)
currHoldCnt = len(currHoldSet)
cannotSellCnt = len(cannotSellList)
cannotBuyCnt = len(cannotBuyList)
#if StockConst.isDebug:
#print("dateStr:" + dateStr + " changePCTBuy:" + str(changePCTBuy) + " changePCTSell:" + str(changePCTSell) +
#" changePCTHold:" + str(changePCTHold))
#当日净值
netValue = currMV / initialMV
#print("netValue:" + str(netValue))
#当日收益
dailyChangePCT = NumUtil.get_change_pct(lastMV, currMV, 2)
#当日可用现金
usableCach = capitalEntity.get_usable_cash()
#
stockStatDailyDf.ix[
tradingDayStr] = netValue, dailyChangePCT, buyCnt, sellCnt, prevHoldCnt, currHoldCnt, cannotSellCnt, cannotBuyCnt, usableCach, currMV
#
lastMV = currMV
# 信号数据
#groupedSignalData.to_csv(StockConst.root + '\export\groupedSignalData.csv')
# 每日交易
# print('每日交易:')
stockTradeDailyDf = pd.DataFrame(stockTradeList)
stockTradeDailyDf.sort_values(by=['tradingDate'], ascending=True)
stockTradeDailyDf.to_csv(StockConst.ROOT + '\export\stockTradeDaily.csv')
# 每日持仓
#print('每日持仓:')
stockHoldDailyDf = pd.DataFrame(stockHoldDailyList)
stockHoldDailyDf.sort_values(by=['tradingDate'], ascending=True)
stockHoldDailyDf.to_csv(StockConst.ROOT + '\export\stockHoldDaily.csv')
#每日统计(收益，净值，买入数，卖出数，持有数)
stockStatDailyDf = stockStatDailyDf.dropna(how='all')
print('每日统计:')
print(stockStatDailyDf)
stockStatDailyDf.to_csv(StockConst.ROOT + '\export\stockStatDaily.csv')
# 每年统计
yearDf = StockYearService.main(stockStatDailyDf)
print('每年统计:')
print(yearDf)
# 最大回撤
maxdrop = StockMaxDropNewService.get_max_drop(stockStatDailyDf)
print('最大回撤:')
print(maxdrop)
#每年的最大回撤
maxdropDf = StockMaxDropNewService.get_max_drop_for_each_year(
stockStatDailyDf)
maxdropDf.sort_values(by=["year"])
print('每年的最大回撤:')
print(maxdropDf)
#夏普比率
sharpRatio = SharpRatioNewService.get_sharp_ratio(stockStatDailyDf)
print('夏普比率:')
print(sharpRatio)
#每年的夏普比率
sharpRatioDf = SharpRatioNewService.get_sharp_ratio_for_each_year(
stockStatDailyDf)
sharpRatioDf.sort_values(by=["year"])
print('每年的夏普比率:')
print(sharpRatioDf)
def main():
signalData = SourceDataDao.getSignalData()
#dailyQuote = SourceDataDao.getDailyQuote()
dailyQuote = SourceDataDao.getNewDailyQuote()
#columns filter
#df3 = sourceData.loc[(df['Mom'] <= 4) & (df['Mom'] <= 4), ['Mom']]
#index filter
#startDate=DateUtils.str2Datetime('20010105');
#endDate=DateUtils.str2Datetime('20010111');
#df4 = df3.ix[startDate:endDate]
numOfDailyHolding = 5
#select top 5 group by TradingDay order by Mom desc
groupedSignalData = signalData.groupby(level='TradingDay').apply(
SelectUtil.top, numOfDailyHolding, 'Mom', False)
#param
#period = 5
#startDate = '1/8/2001'
startDate = '1/8/2001'
#endDate = '1/1/2017'
#eendDate = '5/18/2001'
endDate = '12/31/2016'
#endDate = '12/31/2002'
#endDate = '1/9/2001'
#time series
#dateList = DateUtil.getDateList2(startDate,endDate)
#当前持仓 key:innerCode value:
currHoldSet = {}
stockHoldDF = {}
stockTradeList = []
#资金情况
#capitalDict = {'usableCach':1000000}
#初始资金
initialMV = 1000000
capitalEntity = CapitalEntity.CapitalEntity(initialMV)
lastMV = initialMV
#lastSignalData = pd.DataFrame()
usableVol = 100
netValue = 1
#初始化每日统计表
stockStatDailyDf = pd.DataFrame(index=pd.date_range(startDate, endDate),
columns=[
'netValue', 'changePCT', 'buyCnt',
'sellCnt', 'prevHoldCnt',
'currHoldCnt', 'cannotSellCnt',
'cannotBuyCnt', 'usableCach', 'mv'
])
#初始化每日持仓表
stockHoldDailyList = []
#从信号表中取得唯一性日期
dateList = SourceDataDao.select_date_from_signal(signalData, startDate,
endDate)
for date in dateList:
dateStr = DateUtil.datetime2_str(date)
#print(dateStr)
#isinstance(date, datetime)
# select by single date
#try:
#print(1)
currSignalData = groupedSignalData.ix[date]
if StockConst.IS_DEBUG:
print("currSignalData:" + str(len(currSignalData)))
#print(2)
buyList = getBuyList(currSignalData, currHoldSet)
#print(3)
sellList = getSellList(currSignalData, currHoldSet)
#print(4)
prevHoldList = getPrevHoldList(currSignalData, currHoldSet)
#print(currSignalData)
"""
if (dateStr >= '2015-01-05') & (dateStr <= '2015-01-05'):
print('-----'+dateStr+'-----')
#print(currSignalData)
#print(buyList)
print(list(currHoldSet.keys()))
for key in currHoldSet.keys():
print(str(key) + ':' + currHoldSet.get(key).openDate)
print('----------------')
"""
#except:
#假期,双休日,原数据问题
#if StockConst.isDebug:
#print(DateUtil.datetime2Str(date) + ': no data')
#continue
dailyChangePCT = 0
actualSellList = []
actualBuyList = []
cannotSellList = []
cannotBuyList = []
#实际买入个数
numOfActualBuy = getNumOfActualBuy(date, buyList, dailyQuote)
#1.sell changePCTSell
handleSellList(date, sellList, dailyQuote, usableVol, stockHoldDF,
stockTradeList, currHoldSet, actualSellList,
cannotSellList, capitalEntity, numOfActualBuy,
signalData, prevHoldList, numOfDailyHolding)
#usableVol = calculateUsableVol(currHoldSet)
#2.buy changePCTBuy
handleBuyList(date, buyList, dailyQuote, usableVol, stockHoldDF,
stockTradeList, currHoldSet, actualBuyList,
cannotBuyList, capitalEntity)
#3.hold
#changePCTHold = handleHoldList(date,prevHoldList,dailyQuote,usableVol,stockHoldDF,stockTradeDF,currHoldSet)
#changePCTHold = 0
currMV = calculateDailyMV(currHoldSet, capitalEntity, dailyQuote, date,
stockHoldDailyList, initialMV)
#handleStockHoldDaily(currHoldSet, stockHoldDailyList, date)
buyCnt = len(actualBuyList)
sellCnt = len(actualSellList)
prevHoldCnt = len(prevHoldList)
currHoldCnt = len(currHoldSet)
cannotSellCnt = len(cannotSellList)
cannotBuyCnt = len(cannotBuyList)
#if StockConst.isDebug:
#print("dateStr:" + dateStr + " changePCTBuy:" + str(changePCTBuy) + " changePCTSell:" + str(changePCTSell) +
#" changePCTHold:" + str(changePCTHold))
#dailyChangePCT = changePCTBuy+changePCTSell+changePCTHold
#print("dailyChangePCT:"+str(dailyChangePCT))
#netValue = netValue * (1 + dailyChangePCT / 100)
#每日净值
netValue = currMV / initialMV
#print("netValue:" + str(netValue))
#每日收益
dailyChangePCT = NumUtil.get_change_pct(lastMV, currMV, 2)
#每日可用现金
usableCach = capitalEntity.get_usable_cash()
stockStatDailyDf.ix[
dateStr] = netValue, dailyChangePCT, buyCnt, sellCnt, prevHoldCnt, currHoldCnt, cannotSellCnt, cannotBuyCnt, usableCach, currMV
lastMV = currMV
#debug 行情数据
debugDailyQuote(groupedSignalData)
# 信号数据
#groupedSignalData.to_csv(StockConst.root + '\export\groupedSignalData.csv')
# 每日交易
# print('每日交易:')
stockTradeDailyDf = pd.DataFrame(stockTradeList)
stockTradeDailyDf.sort_values(by=['tradingDate'], ascending=True)
stockTradeDailyDf.to_csv(StockConst.ROOT + '\export\stockTradeDaily.csv')
# 每日持仓
#print('每日持仓:')
stockHoldDailyDf = pd.DataFrame(stockHoldDailyList)
stockHoldDailyDf.sort_values(by=['tradingDate'], ascending=True)
stockHoldDailyDf.to_csv(StockConst.ROOT + '\export\stockHoldDaily.csv')
#每日统计(收益，净值，买入数，卖出数，持有数)
stockStatDailyDf = stockStatDailyDf.dropna(how='all')
print('每日统计:')
print(stockStatDailyDf)
stockStatDailyDf.to_csv(StockConst.ROOT + '\export\stockStatDaily.csv')
# 每年统计
yearDf = StockYearService.main(stockStatDailyDf)
print('每年统计:')
print(yearDf)
# 最大回撤
maxdrop = StockMaxDropNewService.get_max_drop(stockStatDailyDf)
print('最大回撤:')
print(maxdrop)
#每年的最大回撤
maxdropDf = StockMaxDropNewService.get_max_drop_for_each_year(
stockStatDailyDf)
maxdropDf.sort_values(by=["year"])
print('每年的最大回撤:')
print(maxdropDf)
#夏普比率
sharpRatio = SharpRatioNewService.get_sharp_ratio(stockStatDailyDf)
print('夏普比率:')
print(sharpRatio)
#每年的夏普比率
sharpRatioDf = SharpRatioNewService.get_sharp_ratio_for_each_year(
stockStatDailyDf)
sharpRatioDf.sort_values(by=["year"])
print('每年的夏普比率:')
print(sharpRatioDf)
def main():
signalData = SourceDataDao.getSignalData()
#dailyQuote = SourceDataDao.getDailyQuote()
dailyQuote = SourceDataDao.getNewDailyQuote()
