def run():
# 初始化
load = loader()
m = load.load("my.py_")
#my.init()
func_init = m["init"]
func_init()
conn = bt.getConnection()
#print c.startDateStr
#print c.endDateStr
df = bt.getTradeDay(conn,
start_date_str=c.startDateStr,
end_date_str=c.endDateStr,
type=1)
print df
# 按日期执行策略
datelist = df['tradedate'].tolist()
#load = loader()
#m = load.load("my.py_")
func = m["handle_data"]
for d in datelist:
# print d
#sd.handle_data(datelist[d])
func(d)
def execute(strategyId, periodType, changePeriod, startDateStr, endDateStr,
initMoney, stocktype_list, stocklist, stockExpression,
baseVariableExpression, conditionVariableExpression,
buyConditionlist, sellConditionlist):
benchCode = '000300.SH'
stocklistStr = ''
for index in range(len(stocklist)):
i = index + 1
stocktype = stocktype_list[index]
stocklistStr += " s" + str(
i
) + " = str(tbd.get_stocklist_by_type(tradedate, '" + stocktype + "'))\n"
stocklistStr += " s = \"" + stockExpression + "\"\n"
template = env.get_template('mytemplate.html')
codestr = template.render(stockExpression='', stocklistStr=stocklistStr, baseVariableExpression=baseVariableExpression, \
conditionVariableExpression=conditionVariableExpression ,buyConditionlist=buyConditionlist, sellConditionlist=sellConditionlist)
# print codestr
#filename = str(int(time.time()))+'.py'
filename = "my_" + strategyId + ".py"
#os.mknod("test.txt")
# print filename
f = file(filename, 'w')
f.write(codestr)
f.close()
load = loader()
m = load.load(filename)
conn = bt.getConnection()
st.deleteByStrategyId(strategyId, conn)
df = bt.getTradeDay(conn,
start_date_str=startDateStr,
end_date_str=endDateStr,
type=1)
# 按日期执行策略
ip = InitParam.InitParam(strategyId, periodType, changePeriod,
startDateStr, endDateStr, initMoney)
datelist = df['tradedate'].tolist()
func = m["handle_data"]
for d in datelist:
# print d
# print ip
func(d, ip)
summary = getSummary(strategyId, benchCode, startDateStr, endDateStr)
# print summary
os.remove(filename)
return summary
def min_cal_new(string):
#print string
if string.count('U') == 1:
#print string[:string.find('U')]
#print string[string.find('U') + 1:]
# [12,3,5] [4] 是字符串，首先转成list
lst = bt.union(string[:string.find('U')].split(','),
string[string.find('U') + 1:].split(','))
return ",".join(lst)
if string.count('N') == 1:
#print string[:string.find('N')]
#print string[string.find('N') + 1:]
lst = bt.intersection(string[:string.find('N')].split(','),
string[string.find('N') + 1:].split(','))
return ",".join(lst)
def trade(tradedate):
'''
调仓周期
'''
conn = cbt.getConnection()
# 如果当前没有到调仓周期,跳过
if cc.currentPeriod != cc.changePeriod:
cc.currentPeriod = cc.currentPeriod + 1
return
cc.currentPeriod = 1
# 获取票池
stocklist = getStockList()
if len(stocklist) == 0:
return
price = 0
positionList = cc.positionList
'''
通过买入条件获取买入股票,取并集或者交集
'''
techFactor = TechFactorService.TechFactorService()
# 传入股票池、收盘价标识、交易日期、5日、10日、金叉参数
stocklist1 = techFactor.ma(stocklist, 'close', tradedate, 5, 10, 1)
t = TushareBasedata.TushareBasedata()
trade_date_str = datetime.strftime(tradedate, '%Y-%m-%d')
# 穿入股票，查询股票的市值因子列表，mv
df = t.get_factor_data_by_stocklist(trade_date_str, stocklist, 'roe', 0)
# 按因子排序，计算得到前10%的股票代码
df = df.sort_values(by='fv')
stocklist2 = df.code.tolist()
# 取并集
stocklist = stocklist1 + stocklist2
# 订单列表
orderlist = []
'''
调整仓位：卖出不在票池的股票
'''
# 卖出
for position in positionList:
code = position.code
if code in stocklist:
stocklist.remove(code)
continue
# cst.order(tradedate, code, price, 0)
o = StockOrder.StockOrder(cc.strategyId, code, tradedate, price, 0)
orderlist.append(o)
'''
调整仓位：买入符合条件的股票
'''
# 买入
for code in stocklist:
o = StockOrder.StockOrder(cc.strategyId, code, tradedate, price, 100)
orderlist.append(o)
# 订单入库，并更新仓位
cst.order(orderlist, conn)
if len(orderlist) == 0:
return 0
return 1
def updatePositionAccount(tradedate):
conn = cbt.getConnection()
print cc.initMoney
print cc.tradeMoney
# 记录资金账户信息
money = cc.initMoney + cc.tradeMoney
cst.saveAccount(cc.strategyId, tradedate, money, conn)
cc.tradeMoney = 0
cc.initMoney = money
def json_index():
conn = bt.getConnection()
# print request
print request.args.get('strategyId')
strategyId = request.args.get('strategyId')
assetsDf = pd.read_csv('asserts_' + strategyId + '.csv')
assetsList = [list(x) for x in assetsDf.values]
#print st.getPositionListByStrategyId(strategyId, conn)
#print assetsList
return Response(json.dumps(assetsList), mimetype='application/json')
def getSummary(strategyId, benchCode, startDateStr, endDateStr):
conn = cbt.getConnection()
t = MysqlBasedata.MysqlBasedata()
df_bench = t.get_history_index_data_by_date(benchCode, startDateStr,
endDateStr, None)
df_bench = df_bench.sort_values(by='tradedate', ascending=True)
#sql = "SELECT * from r_position where strategy_id='"+stategyId+"' and tradedate ORDER BY tradedate"
#df_position = pd.read_sql(sql, conn)
df_position = st.getPositionListByTradedate(strategyId, startDateStr,
endDateStr, conn)
rsumm = returnSummary.ReturnSummary(df_position, df_bench)
summ = rsumm.get_summary()
print summ
# total asset data
print rsumm.df_assets
# rsumm.df_assets = rsumm.df_assets[rsumm.df_assets]
rsumm.df_assets.to_csv('asserts_.csv', index=False, sep=',')
print pd.read_csv('asserts_.csv')
return rsumm, summ
def endTrade(d, flag):
conn = cbt.getConnection()
# 查询最新的交易日
lastAccountDateStr = cst.getLastAccountDate(cc.strategyId, conn)
# 记录资金账户信息
money = cc.initMoney + cc.tradeMoney
cst.saveAccount(cc.strategyId, d, money, conn)
cc.tradeMoney = 0
# 如果没有订单，查询最新的仓位交易日
if flag == 0:
# 如果仓位交易日不为空，查询仓位信息，复制仓位信息到新的交易日
if lastAccountDateStr != None:
lastPositionDf = cst.getPositionList(cc.strategyId,
lastAccountDateStr, conn)
if len(lastPositionDf) > 0:
positionDf = lastPositionDf.copy()
# 更新仓位日期
positionDf['TRADEDATE'] = d
positionList = [tuple(x) for x in positionDf.values]
cst.savePosition(positionList, conn)
def tradeNew(tradedate):
# 数据库操作类初始化
t = MysqlBasedata.MysqlBasedata()
# 连接池初始化
conn = cbt.getConnection()
# 日期格式转换
trade_date_str = datetime.strftime(tradedate, '%Y-%m-%d')
# 查询股票行情接口
stockPriceDf = t.get_history_data_by_stocklist(trade_date_str, None, 'D',
'B')
# 验证调仓日期：验证是否到达调仓日期
# 如果当前不是到调仓日期，新增资金账户信息
# 查询前一天是否存在仓位，如果存在，拷贝前一天仓位信息
if cc.currentPeriod % cc.changePeriod != 1:
# 如果是第一天，记录账户资金信息
# todo 否则，判断是否
# 拷贝前一天的仓位信息，更新仓位中的股票价格
updatePosition(tradedate, stockPriceDf, conn)
#updatePositionAccount(tradedate)
cc.currentPeriod = cc.currentPeriod + 1
return
cc.currentPeriod = cc.currentPeriod + 1
# 如果是调仓日期，进入策略逻辑
# 获取票池
stocklist = getStockList(tradedate)
print stocklist
# 如果股票池为0
if len(stocklist) == 0:
# 新增资金账户信息，拷贝前一天仓位信息
updatePosition(tradedate, stockPriceDf, conn)
return
# 定义买入股票列表、卖出股票列表
buystocklist = stocklist
# 计算得出中间条件、筛选股票的条件
factor_txt = 'MA5 = MA(trade_closeprice,5)\nMA10 = MA(trade_closeprice, 10)'
filter_txt = 'gx = CROSS(MA5, MA10)\nasc5 = SORT(MA5, desc, 5)'
d1, d2 = intp.interp(factor_txt, filter_txt)
# 通过买入条件得出买入股票列表
for key in ['asc5']:
buystocklist = d2[key].filter(buystocklist, tradedate)
# print 'Stock list by applying filter', key, ':', buystocklist
# 当前订单列表
currentOrderlist = []
lastAccountDateStr = cst.getLastAccountDate(cc.strategyId, conn)
positionList = []
# 如果仓位交易日不为空，查询仓位信息，复制仓位信息到新的交易日
if lastAccountDateStr != None:
positionDf = cst.getPositionList(cc.strategyId, lastAccountDateStr,
conn)
positionList = positionDf.values
# 通过卖出条件得出卖出股票列表,并将卖出股票列表放入订单
for position in positionList:
code = position[1]
if code in buystocklist:
buystocklist.remove(code)
continue
print code
print stockPriceDf.loc[code, 'FACTOR_VALUE']
o = StockOrder.StockOrder(cc.strategyId, code, tradedate,
stockPriceDf.loc[code, 'FACTOR_VALUE'], 0)
print o
currentOrderlist.append(o)
# 买入,并将买入股票列表放入订单
for code in buystocklist:
o = StockOrder.StockOrder(cc.strategyId, code, tradedate,
stockPriceDf.loc[code, 'FACTOR_VALUE'], 100)
currentOrderlist.append(o)
print currentOrderlist
# 订单入库，并更新仓位
cst.order(currentOrderlist, stockPriceDf, conn)
def quant_post():
print "start:", datetime.now()
start = datetime.now()
summaryList = []
orderList = []
positionList = []
# accountList = []
strategyId = None
try:
# 策略参数
startDateStr = request.form['startDate']
endDateStr = request.form['endDate']
changePeriod = int(request.form['interval'])
period = request.form['period']
initMoney = float(request.form['initMoney'])
fee = request.form['fee']
print startDateStr
print endDateStr
print changePeriod
print period
print initMoney
print fee
# 股票筛选条件
constituentStockStr = request.form['constituentStockStr']
print constituentStockStr
areaStr = request.form['areaStr']
conceptStr = request.form['conceptStr']
industryStr = request.form['industryStr']
print constituentStockStr
print areaStr
print conceptStr
print industryStr
# 票池表达式、变量表达式
stockExpression = request.form['stockExpression']
baseVariableExpression = request.form['baseVariableExpression']
conditionVariableExpression = request.form[
'conditionVariableExpression']
print stockExpression
print baseVariableExpression
print conditionVariableExpression
formulastr = baseVariableExpression.split("\r\n")
print formulastr
factorlist = []
baseVariableExpressionStr = ''
for f in formulastr:
baseVariableExpressionStr += f + r"\n"
baseVariableExpression = baseVariableExpressionStr[:-2]
conditionVariableExpressionStr = ''
formulastr = conditionVariableExpression.split("\r\n")
print formulastr
for f in formulastr:
conditionVariableExpressionStr += f + r"\n"
conditionVariableExpression = conditionVariableExpressionStr[:-2]
print baseVariableExpression
print conditionVariableExpression
# 买入条件、卖出条件
buyConditionStr = request.form['buyConditionStr']
buyFundPercentStr = request.form['buyFundPercentStr']
buyWeightTypeStr = request.form['buyWeightTypeStr']
sellConditionStr = request.form['sellConditionStr']
sellFundPercentStr = request.form['sellFundPercentStr']
print buyConditionStr
print buyFundPercentStr
print buyWeightTypeStr
print sellConditionStr
print sellFundPercentStr
buyConditionlist = buyConditionStr.split(",")
sellConditionlist = sellConditionStr.split(",")
# todo 待完成
periodType = 'D' # period
#changePeriod = 20
#startDateStr = '2011-1-1'
#endDateStr = '2013-1-1'
#initMoney = 1000000
stocktype_list = constituentStockStr.split(",")
stocklist = constituentStockStr.split(
","
) #[('300', '2010-1-1', '2012-1-1'), ('500', '2017-1-1', '2017-8-1'), ('50', '2017-1-1', '2017-8-1')]
#stockExpression = "(s1Ns2)Us3"
#baseVariableExpression = r'MA5 = MA(trade_closeprice,5)\nMA10 = MA(trade_closeprice, 10)'
#conditionVariableExpression = r'gx = CROSS(MA5, MA10)\nasc5 = SORT(MA5, desc, 5)'
#buyConditionlist = ['asc5']
#sellConditionlist = ['gx', 'asc5']
conn = bt.getConnection()
# todo 获取最大的策略id，加1
strategyId = str(st.getMaxStrategyId(conn) + 1)
print "strategyId start:" + strategyId
# todo 返回策略收益率结果，，策略曲线
result = frameM.execute(strategyId, periodType, changePeriod,
startDateStr, endDateStr, initMoney,
stocktype_list, stocklist, stockExpression,
baseVariableExpression,
conditionVariableExpression, buyConditionlist,
sellConditionlist)
summaryDf = result[1].T
asserts = result[0].df_assets
asserts['date_new'] = asserts['date'].map(
lambda x: time.mktime(x.timetuple()) * 1000)
assetsDf = asserts[['date_new', 'asset']]
assetsDf.to_csv('asserts_' + strategyId + '.csv', index=False, sep=',')
# 基准指数
indexDf = st.getIndexListByTradedate('000300.SH', startDateStr,
endDateStr, conn)
indexDf['date_new'] = indexDf['TRADEDATE'].map(
lambda x: time.mktime(x.timetuple()) * 1000)
indexDf['CLOSEPRICE'] = indexDf['CLOSEPRICE'].map(
lambda x: 3000 / x * initMoney)
indexDf = indexDf[['date_new', 'CLOSEPRICE']]
indexDf.to_csv('baseline_' + strategyId + '.csv', index=False, sep=',')
print indexDf
conn = bt.getConnection()
# 查询订单信息
orderDf = st.getOrderList(strategyId, conn)
# 查询仓位信息
positionDf = st.getPositionListByStrategyId(strategyId, conn)
# 查询资金信息
# accountDf = st.getAccountListByStrategyId(strategyId, conn)
summaryList = [tuple(x) for x in summaryDf.values]
orderList = [tuple(x) for x in orderDf.values]
positionList = [tuple(x) for x in positionDf.values]
# accountList = [tuple(x) for x in accountDf.values]
except Exception, e:
traceback.print_exc()
def quant_index():
conn = bt.getConnection()
factorDf = st.getFactorList(conn)
factorList = [tuple(x) for x in factorDf.values]
print factorList
return render_template('quant_form.html', factorList=factorList)
def execute(strategyId, periodType, changePeriod, startDateStr, endDateStr,
initMoney, stocktype_list, stocklist, stockExpression,
baseVariableExpression, conditionVariableExpression,
buyConditionlist, sellConditionlist):
benchCode = '000300.SH'
stocklistStr = ''
keywordList = []
for index in range(len(stocklist)):
i = index + 1
stocktype = stocktype_list[index]
stocklistStr += " s" + str(
i
) + " = tbd.get_stocklist_by_type(tradedate, '" + stocktype + "')\n"
stocklistStr += " str" + str(
i) + " = \"\'\"+'\\',\\''.join(s" + str(i) + ")+\"\'\"\n"
# stocklistStr += " str"+str(i) + " = str"+str(i) + ".replace('\'', '')\n"
keywordList.append("str" + str(i))
stocklistStr += " stockExpression = \"" + stockExpression + "\".replace('s', 'str')\n"
stocklistStr += " for str in " + str(keywordList) + ":\n"
stocklistStr += " stockExpression = stockExpression.replace(str, '\"+'+str+'+\"\')\n"
stocklistStr += " print stockExpression\n"
# stocklistStr += " stockExpression = stockExpression.replace(str, '"+'\"+str+'+"'\")\n"
# print stocklistStr
'''
str1 = "'"+'\',\''.join(s1)+"'"
str2 = "'"+'\',\''.join(s2)+"'"
str3 = "'"+'\',\''.join(s3)+"'"
s = "(str1Nstr2)Ustr3"
for str in ['str1', 'str2', 'str3']:
s = s.replace(str, '"+'+str+'+"')
print s
stockExpression = stockExpression.replace('s', 'str') #"(str11Nstr22)Ustr33"
for str in ['str11', 'str22', 'str33']:
s = s.replace(str, '"+' + str + '+"')
print s
# stocklistStr += " s = \""+stockExpression+"\"\n"
'''
template = env.get_template('mytemplate.html')
codestr = template.render(stockExpression='', stocklistStr=stocklistStr, baseVariableExpression=baseVariableExpression, \
conditionVariableExpression=conditionVariableExpression ,buyConditionlist=buyConditionlist, sellConditionlist=sellConditionlist)
# print codestr
#filename = str(int(time.time()))+'.py'
filename = "my_" + strategyId + ".py"
#os.mknod("test.txt")
# print filename
f = file(filename, 'w')
f.write(codestr)
f.close()
load = loader()
m = load.load(filename)
conn = bt.getConnection()
st.deleteByStrategyId(strategyId, conn)
df = bt.getTradeDay(conn,
start_date_str=startDateStr,
end_date_str=endDateStr,
type=1)
# 按日期执行策略
ip = InitParam.InitParam(strategyId, periodType, changePeriod,
startDateStr, endDateStr, initMoney)
datelist = df['tradedate'].tolist()
func = m["handle_data"]
for d in datelist:
# print d
# print ip
func(d, ip)
summary = getSummary(strategyId, benchCode, startDateStr, endDateStr)
# print summary
os.remove(filename)
return summary
"Bench Ann Return", "Alpha", "Beta", "IR", "Strategy Vol",
"Bench Vol", "Win(Daily)", "Max Loss(Daily)"
]
values = [
self.retrn, self.retrn_annual, self.retrn_bench,
self.retrn_bench_annual, self.alpha, self.beta, self.IR, self.vol,
self.vol_bench, self.win_daily, self.max_loss_daily
]
df_summary['FieldName'] = names
df_summary["FieldValue"] = values
return df_summary
if __name__ == "__main__":
# 连接池初始化
conn = cbt.getConnection()
sql = "SELECT * from r_position where strategy_id='2' ORDER BY tradedate"
df = pd.read_sql(sql, conn)
# print df
t = MysqlBasedata.MysqlBasedata()
df_bench_new = t.get_history_index_data_by_date('000300.SH', '2015-05-10',
'2017-05-10', None)
df_bench = pd.read_pickle('test_bench_returnSummary.pkl')
df_position = pd.read_pickle('test_data_returnSummary.pkl')
rsumm = ReturnSummary(df_position, df_bench)
summ = rsumm.get_summary()
print summ.T
print type(summ)
# total asset data
print rsumm.df_assets