forked from luhouzi12/2022-summer
-
Notifications
You must be signed in to change notification settings - Fork 0
/
backflow_test.py
188 lines (168 loc) · 8.8 KB
/
backflow_test.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
import copy
from datetime import date
import pandas as pd
import warnings
import os
warnings.filterwarnings("ignore") #狗狗
basePath = r'C:\xyz\quote_test'
# basePath = r'C:\Users\xyz\Desktop\202207\data\stock_quote\quote'
stockCodeColumnIndex = 1
preCloseColumnIndex = 2
closeColumnIndex = 6
stContent = pd.read_csv(r'C:\xyz\st.csv')
industryContent = pd.read_csv(r'C:\xyz\zx_industry.csv')
yearList = [2022]
stStockCodeList = []
for index in stContent.index:
stStockCodeList.append(stContent.loc[index][0])
industryCodeStockCodeListdict = {}
for index in industryContent.index:
stockCode = industryContent.loc[index][0]
industryCode = industryContent.loc[index][3]
if industryCode not in industryCodeStockCodeListdict.keys():
industryCodeStockCodeListdict[industryCode] = []
industryCodeStockCodeListdict[industryCode].append(stockCode)
def readCsv (fileName):
return pd.read_csv(fileName)
def convertStringToDate(dateNumber):
if dateNumber != dateNumber:
return date.today()
dateString = str(dateNumber)
year = int(dateString[:4])
month = int(dateString[4:6])
day = int(dateString[6:8])
return date(year, month, day)
def getAvailableStocks(csvContent):
resultCsvContent = copy.deepcopy(csvContent)
for index in csvContent.index:
stockCode = csvContent.loc[index][stockCodeColumnIndex]
if stockCode in stStockCodeList:
stIndexs = [i for i,x in enumerate(stStockCodeList) if x==stockCode]
Tdate = convertStringToDate(csvContent.loc[index][0])
for stIndex in stIndexs:
entryDate = convertStringToDate(stContent.loc[stIndex][2])
endDate = convertStringToDate(stContent.loc[stIndex][3])
if Tdate < endDate and Tdate > entryDate and index in resultCsvContent.index:
resultCsvContent.drop(index=index,inplace=True)
return resultCsvContent
def generateAvailableCsvContentFilePathList():
yearPathList = []
for year in yearList:
yearPath = basePath + '\\' + str(year)
yearPathList.append(yearPath)
monthPathList = []
for yearPath in yearPathList:
thisYearMonthPathList = os.listdir(yearPath)
for monthPath in thisYearMonthPathList:
monthPathList.append(yearPath + '\\' + monthPath)
csvPathList = []
for monthPath in monthPathList:
for fileName in os.listdir(monthPath):
csvPathList.append(monthPath + '\\' + fileName)
resultCsvPathList = copy.deepcopy(csvPathList)
for csvPath in csvPathList:
csvContent = readCsv(csvPath)
if len(csvContent) == 0:
resultCsvPathList.remove(csvPath)
return resultCsvPathList
def generate5dr(csvFilePathList):
for csvFilePath in csvFilePathList:
if csvFilePathList.index(csvFilePath) > 5:
TCsvContent = readCsv(csvFilePath) # Today's CSV content
availableTCsvContent = getAvailableStocks(TCsvContent) # filter out st stocks
TStockCodeAlphaRawDict = {}
TM5CsvFilePath = csvFilePathList[csvFilePathList.index(csvFilePath) - 5]
TM5CsvContent = readCsv(TM5CsvFilePath) # T-5 's CSV Content
for index in availableTCsvContent.index: # loop today's available stocks
stockCode = availableTCsvContent.loc[index][stockCodeColumnIndex]
stockTClose = availableTCsvContent.loc[index][closeColumnIndex] # close
# f.loc[df['column_name'] == some_value]
stockLinesInTM5 = TM5CsvContent[TM5CsvContent['S_INFO_WINDCODE:1'].isin([str(stockCode)])]
if len(stockLinesInTM5):
TM5Close = stockLinesInTM5.loc[stockLinesInTM5.index[0]]['S_DQ_CLOSE:6']
TStockCodeAlphaRawDict[stockCode] = stockTClose - TM5Close
TStockCodeAlphaRawDictList.append(TStockCodeAlphaRawDict)
return
csvFilePathList = generateAvailableCsvContentFilePathList()
TStockCodeAlphaRawDictList = []
for csvFilePath in csvFilePathList:
if csvFilePathList.index(csvFilePath) > 5:
TCsvContent = readCsv(csvFilePath) # Today's CSV content
availableTCsvContent = getAvailableStocks(TCsvContent) # filter out st stocks
TStockCodeAlphaRawdict = {}
TM5CsvFilePath = csvFilePathList[csvFilePathList.index(csvFilePath) - 5]
TM5CsvContent = readCsv(TM5CsvFilePath) # T-5 's CSV Content
for index in availableTCsvContent.index: # loop today's available stocks
stockCode = availableTCsvContent.loc[index][stockCodeColumnIndex]
stockTClose = availableTCsvContent.loc[index][closeColumnIndex] # close
stockLinesInTM5 = TM5CsvContent[TM5CsvContent['S_INFO_WINDCODE:1'].isin([str(stockCode)])]
if len(stockLinesInTM5):
TM5Close = stockLinesInTM5.loc[stockLinesInTM5.index[0]]['S_DQ_CLOSE:6']
TStockCodeAlphaRawdict[stockCode] = stockTClose - TM5Close
TStockCodeAlphaRawDictList.append(TStockCodeAlphaRawdict)
def neu(stockCodeAlphaRawdict):
for industryCode in industryCodeStockCodeListdict.keys():
stockCodeList = industryCodeStockCodeListdict[industryCode]
stockCodeInCurrentIndustryAlphadictList = list(filter(lambda stockCode: stockCode in stockCodeList, stockCodeAlphaRawdict))
currentIndustryAlphas = []
for stockCode in stockCodeInCurrentIndustryAlphadictList:
currentIndustryAlphas.append(stockCodeAlphaRawdict[stockCode])
avgAlpha = sum(currentIndustryAlphas) / len(currentIndustryAlphas)
for stockCode in stockCodeInCurrentIndustryAlphadictList:
stockCodeAlphaRawdict[stockCode] = stockCodeAlphaRawdict[stockCode] - avgAlpha
def dk5(stockCodeAlphaRawdictList):
for stockCodeAlphaRawdict in stockCodeAlphaRawdictList:
TIndex = stockCodeAlphaRawdictList.index(stockCodeAlphaRawdict)
if TIndex >= 4:
dropStockCodeList = []
for stockCode in stockCodeAlphaRawdict.keys():
available = True
for i in range(5):
if stockCode not in stockCodeAlphaRawdictList[TIndex - i].keys():
available = False
if available:
stockCodeAlphaRawdict[stockCode] = (5 * stockCodeAlphaRawdict[stockCode] + 4 * stockCodeAlphaRawdictList[TIndex - 1][stockCode] + 3 * stockCodeAlphaRawdictList[TIndex - 2][stockCode] + 2 * stockCodeAlphaRawdictList[TIndex - 3][stockCode] + stockCodeAlphaRawdictList[TIndex - 4][stockCode]) / (1 + 2 + 3 + 4 + 5)
else:
dropStockCodeList.append(stockCode)
for stockCode in dropStockCodeList:
stockCodeAlphaRawdict.pop(stockCode)
def powrank(stockCodeAlphaRawdict):
sortedDict = dict(sorted(stockCodeAlphaRawdict.items(), key=lambda item: item[1]))
for stockCode in sortedDict.keys():
sortedDict[stockCode] = list(sortedDict.keys()).index(stockCode)**2
maxAbsAlpha = max(map(abs, sortedDict.values()))
for stockCode in sortedDict.keys():
sortedDict[stockCode] = sortedDict[stockCode] / maxAbsAlpha
avgAlpha = sum(sortedDict.values()) / len(sortedDict)
for stockCode in sortedDict.keys():
sortedDict[stockCode] = sortedDict[stockCode] - avgAlpha
return sortedDict
for stockCodeAlphaRawdict in TStockCodeAlphaRawDictList:
neu(stockCodeAlphaRawdict)
dk5(TStockCodeAlphaRawDictList)
for index in range(len(TStockCodeAlphaRawDictList)):
TStockCodeAlphaRawDictList[index] = powrank(TStockCodeAlphaRawDictList[index])
def calculateReturn(stockCodeAlphaDict, csvContent):
stockCodeReturnDict = {}
for stockCode in stockCodeAlphaDict.keys():
stockLineInCsvContent = csvContent[csvContent['S_INFO_WINDCODE:1'].isin([str(stockCode)])]
TReturn = stockLineInCsvContent.loc[stockLineInCsvContent.index[0]]['RETURNS:10']
stockCodeReturnDict[stockCode] = stockCodeAlphaDict[stockCode] * TReturn
return stockCodeReturnDict
stockCodeReturnDictList = []
for index in range(len(TStockCodeAlphaRawDictList)):
stockCodeReturnDictList.append(calculateReturn(TStockCodeAlphaRawDictList[index], readCsv(csvFilePathList[index + 6])))
dailyReturnList = []
for stockCodeReturnDict in stockCodeReturnDictList:
sumReturn = 0
for returnValue in stockCodeReturnDict.values():
if returnValue == returnValue:
sumReturn = sumReturn + returnValue
dailyReturnList.append(sumReturn)
print(dailyReturnList)
drawDown = max(dailyReturnList) - min(dailyReturnList)
totalReturn = sum(dailyReturnList)
print('draw down: ' + str(drawDown))
print('total return: ' + str(totalReturn))
# IR IC return rate huanshoulv BPMG bodonglv zuidahuiche
# zhengti/fennian