def IntradayFryWin(symbolinfo, rawdata, paraSet):
setname = paraSet['Setname']
MACD_S = paraSet['MACD_S']
MACD_L = paraSet['MACD_L']
MACD_M = paraSet['MACD_M']
MA_N = paraSet['MA_N']
# print setname
rawdata['Unnamed: 0'] = range(rawdata.shape[0])
#beginindex = rawdata.ix[0, 'Unnamed: 0']
# 计算MACD
macd = MA.calMACD(rawdata['close'], MACD_S, MACD_L, MACD_M)
rawdata['DIF'] = macd[0]
rawdata['DEA'] = macd[1]
rawdata['MA'] = MA.calEMA(rawdata['close'], MA_N)
# 计算MACD的金叉和死叉
rawdata['MACD_True'], rawdata['MACD_Cross'] = MA.dfCross(rawdata, 'DIF', 'DEA')
# ================================ 找出买卖点================================================
# 1.先找出SAR金叉的买卖点
# 2.找到结合判决条件的买点
# 3.从MA买点中滤出真实买卖点
# 取出金叉点
goldcrosslist = pd.DataFrame({'goldcrosstime': rawdata.loc[rawdata['MACD_Cross'] == 1, 'strtime']})
goldcrosslist['goldcrossutc'] = rawdata.loc[rawdata['MACD_Cross'] == 1, 'utc_time']
goldcrosslist['goldcrossindex'] = rawdata.loc[rawdata['MACD_Cross'] == 1, 'Unnamed: 0']
goldcrosslist['goldcrossprice'] = rawdata.loc[rawdata['MACD_Cross'] == 1, 'close']
# 取出死叉点
deathcrosslist = pd.DataFrame({'deathcrosstime': rawdata.loc[rawdata['MACD_Cross'] == -1, 'strtime']})
deathcrosslist['deathcrossutc'] = rawdata.loc[rawdata['MACD_Cross'] == -1, 'utc_time']
deathcrosslist['deathcrossindex'] = rawdata.loc[rawdata['MACD_Cross'] == -1, 'Unnamed: 0']
deathcrosslist['deathcrossprice'] = rawdata.loc[rawdata['MACD_Cross'] == -1, 'close']
goldcrosslist = goldcrosslist.reset_index(drop=True)
deathcrosslist = deathcrosslist.reset_index(drop=True)
# 生成多仓序列（金叉在前，死叉在后）
if goldcrosslist.ix[0, 'goldcrossindex'] < deathcrosslist.ix[0, 'deathcrossindex']:
longcrosslist = pd.concat([goldcrosslist, deathcrosslist], axis=1)
else: # 如果第一个死叉的序号在金叉前，则要将死叉往上移1格
longcrosslist = pd.concat([goldcrosslist, deathcrosslist.shift(-1).fillna(0)], axis=1)
longcrosslist = longcrosslist.set_index(pd.Index(longcrosslist['goldcrossindex']), drop=True)
# 生成空仓序列（死叉在前，金叉在后）
if deathcrosslist.ix[0, 'deathcrossindex'] < goldcrosslist.ix[0, 'goldcrossindex']:
shortcrosslist = pd.concat([deathcrosslist, goldcrosslist], axis=1)
else: # 如果第一个金叉的序号在死叉前，则要将金叉往上移1格
shortcrosslist = pd.concat([deathcrosslist, goldcrosslist.shift(-1).fillna(0)], axis=1)
shortcrosslist = shortcrosslist.set_index(pd.Index(shortcrosslist['deathcrossindex']), drop=True)
# 取出开多序号和开空序号
openlongindex = rawdata.loc[
(rawdata['MACD_Cross'] == 1) & (rawdata['close'] > rawdata['MA']) & (rawdata['ATR'] > 6)].index
openshortindex = rawdata.loc[
(rawdata['MACD_Cross'] == -1) & (rawdata['close'] < rawdata['MA']) & (rawdata['ATR'] > 6)].index
# 从多仓序列中取出开多序号的内容，即为开多操作
longopr = longcrosslist.loc[openlongindex]
longopr['tradetype'] = 1
longopr.rename(columns={'goldcrosstime': 'opentime',
'goldcrossutc': 'openutc',
'goldcrossindex': 'openindex',
'goldcrossprice': 'openprice',
'deathcrosstime': 'closetime',
'deathcrossutc': 'closeutc',
'deathcrossindex': 'closeindex',
'deathcrossprice': 'closeprice'}, inplace=True)
# 从空仓序列中取出开空序号的内容，即为开空操作
shortopr = shortcrosslist.loc[openshortindex]
shortopr['tradetype'] = -1
shortopr.rename(columns={'deathcrosstime': 'opentime',
'deathcrossutc': 'openutc',
'deathcrossindex': 'openindex',
'deathcrossprice': 'openprice',
'goldcrosstime': 'closetime',
'goldcrossutc': 'closeutc',
'goldcrossindex': 'closeindex',
'goldcrossprice': 'closeprice'}, inplace=True)
# 结果分析
result = pd.concat([longopr, shortopr])
result = result.sort_index()
result = result.reset_index(drop=True)
# result.drop(result.shape[0] - 1, inplace=True)
result = result.dropna()
# 去掉跨合约的操作
# 使用单合约，不用再去掉跨合约
# result = removeContractSwap(result, contractswaplist)
slip = symbolinfo.getSlip()
result['ret'] = ((result['closeprice'] - result['openprice']) * result['tradetype']) - slip
result['ret_r'] = result['ret'] / result['openprice']
results = {}
'''
# 使用单合约，策略核心内不再计算结果
if calcResult:
result['commission_fee'], result['per earn'], result['own cash'], result['hands'] = RS.calcResult(result,
symbolinfo,
initialCash,
positionRatio)
endcash = result['own cash'].iloc[-1]
Annual = RS.annual_return(result)
Sharpe = RS.sharpe_ratio(result)
DrawBack = RS.max_drawback(result)[0]
SR = RS.success_rate(result)
max_single_loss_rate = abs(result['ret_r'].min())
results = {
'Setname':setname,
'opentimes': result.shape[0],
'end_cash': endcash,
'SR': SR,
'Annual': Annual,
'Sharpe': Sharpe,
'DrawBack': DrawBack,
'max_single_loss_rate': max_single_loss_rate
}
closeopr = result.loc[:, 'closetime':'tradetype']
return result, rawdata, closeopr, results
'''
return result
def HopeMACDWin(symbolInfo,setname,K_MIN_MACD,startdate,enddate,macdParaSet,contractswaplist,calcResult=True):
print setname
rawdata_macd = DC.getBarData(symbolInfo.symbol, K_MIN_MACD, startdate + " 00:00:00", enddate + " 23:59:59")
MACD_S=macdParaSet['MACD_S']
MACD_L = macdParaSet['MACD_L']
MACD_M = macdParaSet['MACD_M']
macd = MA.calMACD(rawdata_macd['close'], MACD_S, MACD_L, MACD_M)
rawdata_macd['DIF'] = macd[0]
rawdata_macd['DEA'] = macd[1]
rawdata_macd['DIF_F']=-1
rawdata_macd['DEA_F']=-1
rawdata_macd.loc[rawdata_macd['DIF']>=0,'DIF_F'] = 1
rawdata_macd.loc[(rawdata_macd['DIF']>=rawdata_macd['DEA']) , 'DEA_F'] = 1
rawdata_macd['OpenF']=rawdata_macd['DIF_F']+rawdata_macd['DEA_F']
rawdata_macd['OpenF1']=rawdata_macd['OpenF'].shift(1).fillna(0)
# ================================ 找出买卖点================================================
# 1.OpenF==2 & (OpenF1 ==-2/0):开多
# 2.OpenF==-2/0& （OpenfF1==2):平多
# 3.OpenF==-2 & （OpenF1 == 2/0）：开空
# 4.OpenF==2/0 & OpenF1==-2 :平空
#开多
openlonglist = pd.DataFrame({'opentime': rawdata_macd.loc[(rawdata_macd['OpenF'] == 2) & (rawdata_macd['OpenF1'] < 2 ), 'strtime']})
openlonglist['openutc'] = rawdata_macd.loc[(rawdata_macd['OpenF'] == 2) & (rawdata_macd['OpenF1'] < 2 ), 'utc_time']
openlonglist['openindex'] = rawdata_macd.loc[(rawdata_macd['OpenF'] == 2) & (rawdata_macd['OpenF1'] < 2 ), 'Unnamed: 0']
openlonglist['openprice'] = rawdata_macd.loc[(rawdata_macd['OpenF'] == 2) & (rawdata_macd['OpenF1'] < 2 ), 'close']
# 平多
closelonglist = pd.DataFrame(
{'closetime': rawdata_macd.loc[(rawdata_macd['OpenF1'] == 2) & (rawdata_macd['OpenF'] < 2), 'strtime']})
closelonglist['closeutc'] = rawdata_macd.loc[
(rawdata_macd['OpenF1'] == 2) & (rawdata_macd['OpenF'] < 2), 'utc_time']
closelonglist['closeindex'] = rawdata_macd.loc[
(rawdata_macd['OpenF1'] == 2) & (rawdata_macd['OpenF'] < 2), 'Unnamed: 0']
closelonglist['closeprice'] = rawdata_macd.loc[
(rawdata_macd['OpenF1'] == 2) & (rawdata_macd['OpenF'] < 2), 'close']
#开空
openshortlist = pd.DataFrame({'opentime': rawdata_macd.loc[(rawdata_macd['OpenF'] == -2) & (rawdata_macd['OpenF1'] > -2 ), 'strtime']})
openshortlist['openutc'] = rawdata_macd.loc[(rawdata_macd['OpenF'] == -2) & (rawdata_macd['OpenF1'] > -2 ), 'utc_time']
openshortlist['openindex'] = rawdata_macd.loc[(rawdata_macd['OpenF'] == -2) & (rawdata_macd['OpenF1'] > -2 ), 'Unnamed: 0']
openshortlist['openprice'] = rawdata_macd.loc[(rawdata_macd['OpenF'] == -2) & (rawdata_macd['OpenF1'] > -2 ), 'close']
# 平空
closeshortlist = pd.DataFrame(
{'closetime': rawdata_macd.loc[(rawdata_macd['OpenF1'] == -2) & (rawdata_macd['OpenF'] > -2), 'strtime']})
closeshortlist['closeutc'] = rawdata_macd.loc[
(rawdata_macd['OpenF1'] == -2) & (rawdata_macd['OpenF'] > -2), 'utc_time']
closeshortlist['closeindex'] = rawdata_macd.loc[
(rawdata_macd['OpenF1'] == -2) & (rawdata_macd['OpenF'] > -2), 'Unnamed: 0']
closeshortlist['closeprice'] = rawdata_macd.loc[
(rawdata_macd['OpenF1'] == -2) & (rawdata_macd['OpenF'] > -2), 'close']
openlonglist.reset_index(drop=True,inplace=True)
closelonglist.reset_index(drop=True,inplace=True)
openshortlist.reset_index(drop=True,inplace=True)
closeshortlist.reset_index(drop=True,inplace=True)
# 生成多仓序列（金叉在前，死叉在后）
if openlonglist.ix[0, 'openindex'] < closelonglist.ix[0, 'closeindex']:
longlist = pd.concat([openlonglist, closelonglist], axis=1)
else: # 如果第一个死叉的序号在金叉前，则要将死叉往上移1格
longlist = pd.concat([openlonglist, closelonglist.shift(-1).fillna(0)], axis=1)
#longlist.set_index('openindex', inplace=True)
longlist['tradetype']=1
# 生成空仓序列（死叉在前，金叉在后）
if openshortlist.ix[0, 'openindex'] < closeshortlist.ix[0, 'closeindex']:
shortlist = pd.concat([openshortlist, closeshortlist], axis=1)
else: # 如果第一个金叉的序号在死叉前，则要将金叉往上移1格
shortlist = pd.concat([openshortlist, closeshortlist.shift(-1).fillna(0)], axis=1)
#shortlist.set_index('openindex', drop=True)
shortlist['tradetype']=-1
# 结果分析
result = pd.concat([longlist, shortlist])
result = result.set_index(pd.Index(result['openindex']), drop=True)
result = result.sort_index()
result = result.reset_index(drop=True)
result.drop(result.shape[0] - 1, inplace=True)
# 去掉跨合约的操作
result = removeContractSwap(result, contractswaplist)
initial_cash = 20000
margin_rate = 0.2
slip = symbolInfo.getSlip()
multiplier = symbolInfo.getMultiplier()
poundgeType, poundgeFee, poundgeRate = symbolInfo.getPoundage()
result['ret'] = ((result['closeprice'] - result['openprice']) * result['tradetype']) - slip
result['ret_r'] = result['ret'] / result['openprice']
results={}
if calcResult:
firsttradecash = initial_cash / margin_rate
result['commission_fee'] = 0
if poundgeType == symbolInfo.POUNDGE_TYPE_RATE:
result.ix[0, 'commission_fee'] = firsttradecash * poundgeRate * 2
else:
result.ix[0, 'commission_fee'] = firsttradecash / (multiplier * result.ix[0, 'openprice']) * poundgeFee * 2
result['per earn'] = 0 # 单笔盈亏
result['own cash'] = 0 # 自有资金线
result['trade money'] = 0 # 杠杆后的可交易资金线
result.ix[0, 'per earn'] = firsttradecash * result.ix[0, 'ret_r']
result.ix[0, 'own cash'] = initial_cash + result.ix[0, 'per earn'] - result.ix[0, 'commission_fee']
result.ix[0, 'trade money'] = result.ix[0, 'own cash'] / margin_rate
oprtimes = result.shape[0]
for i in np.arange(1, oprtimes):
# 根据手续费类型计算手续费
if poundgeType == symbolInfo.POUNDGE_TYPE_RATE:
commission = result.ix[i - 1, 'trade money'] * poundgeRate * 2
else:
commission = result.ix[i - 1, 'trade money'] / (multiplier * result.ix[i, 'openprice']) * poundgeFee * 2
perearn = result.ix[i - 1, 'trade money'] * result.ix[i, 'ret_r']
owncash = result.ix[i - 1, 'own cash'] + perearn - commission
result.ix[i, 'own cash'] = owncash
result.ix[i, 'commission_fee'] = commission
result.ix[i, 'per earn'] = perearn
result.ix[i, 'trade money'] = owncash / margin_rate
endcash = result.ix[oprtimes - 1, 'own cash']
Annual = RS.annual_return(result)
Sharpe = RS.sharpe_ratio(result)
DrawBack = RS.max_drawback(result)[0]
SR = RS.success_rate(result)
max_single_loss_rate = abs(result['ret_r'].min())
results = {
'Setname':setname,
'MACD_S':MACD_S,
'MACD_L':MACD_L,
'MACD_M':MACD_M,
'opentimes': oprtimes,
'end_cash': endcash,
'SR': SR,
'Annual':Annual,
'Sharpe':Sharpe,
'DrawBack':DrawBack,
'max_single_loss_rate': max_single_loss_rate
}
print results
filename = ("%s%d %s result.csv" % (symbolInfo.symbol, K_MIN_MACD,setname))
result.to_csv(filename)
rawdata_macd.to_csv('macd '+filename)
del rawdata_macd
return results