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XATrends.py
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XATrends.py
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__author__ = '최재혁'
from XAUtil import *
import jongmokgroup
import plotjongmok
import statistics as stat
from scipy import stats
def saveJongMokGroupProfitTrends(filename,dictJongMokGroup, BaseDate, listAfterDates ):
basedate = DateStrformat(BaseDate)
listDateStr = [ basedate.getDateStr_nDay( aa) for aa in listAfterDates ]
listlistRatioMeans = []
for keyJongMokGroup in dictJongMokGroup :
print("--- JongMokGroup : %s ----------------------------------------------------------"%(keyJongMokGroup))
listdict종가fromJongmokDate = get종가fromListJongmokListday(dictJongMokGroup[keyJongMokGroup], listDateStr)
# saveListDictToCSV("종목가격0.csv", ["종목명"]+listDateStr, listdict종가fJongmokDate)
# exit()
if len(listdict종가fromJongmokDate) == 0 :
print("??? No 종가 정보 --> skip ")
continue
listProportMeans = getProfieLossProportionBasedOnStartDate(listDateStr,listdict종가fromJongmokDate )
listlistRatioMeans.append([keyJongMokGroup] + listProportMeans)
saveListListToCSV(filename, ["종목그룹이름"] + listAfterDates[1:], listlistRatioMeans )
def createJongMokProfitTrends():
'''
purpose : 종목 group을 구성하고, 종목 group별로 201310을 기준으로 이익률를 계산하여 파일로 저장한다.
:return:
'''
dictJongMokGroup = jongmokgroup.dictJongMokGroup
listAfterDates = [ 0, 30, 60, 90, 120, 150, 180, 210, 240, 270, 300, 330, 360, 390, 420, 450, 480, 510, 540, 570, 600, 630, 660, 690]
BaseDate = 20131015
filename = "매수후기간별손익증감_구성종목.csv"
saveJongMokGroupProfitTrends(filename, dictJongMokGroup, BaseDate, listAfterDates)
def createJongMokMatchingPBRPER():
'''
PBR이 1이하, PER가 7이하인 종목들에 대해 20131015을 기준으로 2년간 이익률을 계산.
:return:
'''
listAfterDates = [ 0, 30, 60, 90, 120, 150, 180, 210, 240, 270, 300, 330, 360, 390, 420, 450, 480, 510, 540, 570, 600, 630, 660, 690]
BaseDate = 20131015
listJongmokHan = getJongMokMatchingPBRPER(1.0, 7.0)
#한 좀목으로 group을 만들어 list으로 담는다.
dictJongMokGroup = {}
for JongmokHan in listJongmokHan :
dictJongMokGroup.update({JongmokHan:[JongmokHan]})
filename = "매수후기간별손익증감_PBRPER.csv"
saveJongMokGroupProfitTrends(filename, dictJongMokGroup, BaseDate, listAfterDates)
def plotchart(jongmokname) :
'''
purpose : 주식 종목을 input parameter으로, DB에 있는 chart 정로를 읽어와서, plotchart을 보여준다.
상단에는 종가의 흐름을, 하단에는 거래량을 그려준다.
:param jongmokname:
:return: 단순히 chart만 그려준다.
'''
coll주식종목Data = pymongo.MongoClient('localhost', 27017).get_database("xadb").get_collection("주식종목Data")
dictcondi = {'종목명':jongmokname }
dictproj = {"주식차트_일주월.날짜":1, "주식차트_일주월.종가":1, "주식차트_일주월.거래량":1, "_id":0}
objret = coll주식종목Data.find_one(dictcondi, dictproj)
listdictdatestrprice = objret["주식차트_일주월"]
listdatestr = []
listprice = []
listdealquantity = []
for dictdatestrprice in listdictdatestrprice :
listdatestr.append(dictdatestrprice["날짜"])
listprice.append(dictdatestrprice["종가"])
listdealquantity.append(dictdatestrprice["거래량"])
plotjongmok.plotjongmok(jongmokname, listdatestr, listprice, listdealquantity)
def getMedianAverageCenterIndexOfJongmokGroup(jongmokgroup):
coll주식종목Data = pymongo.MongoClient('localhost', 27017).get_database("xadb").get_collection("주식종목Data")
dictdictdictret = {}
listproj = ["PER", "PBR", "EPS", "ROA", "ROE", "EVEBITDA", "SPS","CPS","BPS","PEG"]
#make the project for find_one()
dictproj ={}
for proj in listproj :
dictproj[proj] = 1
dictproj["_id"] = 0
for keygroup in jongmokgroup :
print("making median, average,.. of %s"%keygroup)
listjongmokhan = jongmokgroup[keygroup]
# dictproj = {"PER":1, "PBR":1, "EPS":1, "ROA":1, "ROE":1, "EVEBITDA":1, "SPS":1,"CPS":1,"BPS":1,"PEG":1, "_id":0}
listPER = []
listPBR = []
listEPS = []
listROA = []
listROE = []
listEVEBITDA = []
listSPS = []
listCPS = []
listBPS = []
listPEG = []
for jongmokhan in listjongmokhan :
dictcondi = {'종목명':jongmokhan }
objret = coll주식종목Data.find_one(dictcondi, dictproj)
if objret == None:
continue
listPER.append(objret["PER"])
listPBR.append(objret["PBR"])
listEPS.append(objret["EPS"])
listROA.append(objret["ROA"])
listROE.append(objret["ROE"])
listEVEBITDA.append(objret["EVEBITDA"])
listSPS.append(objret["SPS"])
listCPS.append(objret["CPS"])
listBPS.append(objret["BPS"])
listPEG.append(objret["PEG"])
dictdictdictret[keygroup] = \
{"PER":{"min":min(listPER), "max":max(listPER), "median":stat.median(listPER), "mean":stat.mean(listPER), "stdev":stat.stdev(listPER, stat.mean(listPER))},
"PBR":{"min":min(listPBR), "max":max(listPBR), "median":stat.median(listPBR), "mean":stat.mean(listPBR), "stdev":stat.stdev(listPBR, stat.mean(listPBR))},
"EPS":{"min":min(listEPS), "max":max(listEPS), "median":stat.median(listEPS), "mean":stat.mean(listEPS), "stdev":stat.stdev(listEPS, stat.mean(listEPS))},
"ROA":{"min":min(listROA), "max":max(listROA), "median":stat.median(listROA), "mean":stat.mean(listROA), "stdev":stat.stdev(listROA, stat.mean(listROA))},
"ROE":{"min":min(listROE), "max":max(listROE), "median":stat.median(listROE), "mean":stat.mean(listROE), "stdev":stat.stdev(listROE, stat.mean(listROE))},
"EVEBITDA":{"min":min(listEVEBITDA), "max":max(listEVEBITDA), "median":stat.median(listEVEBITDA), "mean":stat.mean(listEVEBITDA), "stdev":stat.stdev(listEVEBITDA, stat.mean(listEVEBITDA))},
"SPS":{"min":min(listSPS), "max":max(listSPS), "median":stat.median(listSPS), "mean":stat.mean(listSPS), "stdev":stat.stdev(listSPS, stat.mean(listSPS))},
"CPS":{"min":min(listCPS), "max":max(listCPS), "median":stat.median(listCPS), "mean":stat.mean(listCPS), "stdev":stat.stdev(listCPS, stat.mean(listCPS))},
"BPS":{"min":min(listBPS), "max":max(listBPS), "median":stat.median(listBPS), "mean":stat.mean(listBPS), "stdev":stat.stdev(listBPS, stat.mean(listBPS))},
"PEG":{"min":min(listPEG), "max":max(listPEG), "median":stat.median(listPEG), "mean":stat.mean(listPEG), "stdev":stat.stdev(listPEG, stat.mean(listPEG))}
}
return dictdictdictret, listproj, ["min", "max", "median", "mean", "stdev"]
def createMedianAveragePBRPEROfJongmokGroup():
'''
purpose : 종목group을 만들고, 각 group에 대해, 주요 지표(PBR, PER, EPS등) 의 중앙값(median), 평균(mean),
중심값(center )을 구한다.
:return:
'''
coll주식종목Data = pymongo.MongoClient('localhost', 27017).get_database("xadb").get_collection("주식종목Data")
dictJongMokGroup = jongmokgroup.dictJongMokGroup
# 코스피 종목구성.
dictcondi = {'시장구분':"1" }
dictproj = {"종목명":1, "_id":0}
objret = coll주식종목Data.find(dictcondi, dictproj)
dict코스피 = {"코스피":[obj["종목명"]for obj in objret]}
dictJongMokGroup.update(dict코스피)
# 코스닥 종목구성.
dictcondi = {'시장구분':"2" }
objret = coll주식종목Data.find(dictcondi, dictproj)
dict코스닥 = {"코스닥":[obj["종목명"]for obj in objret]}
dictJongMokGroup.update(dict코스닥)
# 전체 종목 구성.
dict전체 = {"전체": dict코스피["코스피"] +dict코스닥["코스닥"] }
dictJongMokGroup.update(dict전체)
dictdictdictret, listproj, liststat = getMedianAverageCenterIndexOfJongmokGroup(dictJongMokGroup)
savedictdictdictToCSV("종목그룹별지표통계.csv",listproj,liststat, dictdictdictret)
print("Done...")
def createHistorgramOfPERPBRByMarket():
'''
purpose : 코스피, 코스탁, 전체시장에 대해 PER, PBR의 histogram을 그린다.
:return:
'''
coll주식종목Data = pymongo.MongoClient('localhost', 27017).get_database("xadb").get_collection("주식종목Data")
listKOSPIPER = []
listKOSPIPBR = []
# 코스피 종목구성.
dictcondi = {'시장구분':"1" }
dictproj = {"PER":1, "PBR":1, "_id":0}
objret = coll주식종목Data.find(dictcondi, dictproj)
for obj in objret :
per = obj["PER"]
if per > -10 and per <= 100 :
listKOSPIPER.append(per)
pbr = obj["PBR"]
if pbr > -10 and pbr <= 40:
listKOSPIPBR.append(pbr)
listKOSDACPER = []
listKOSDACPBR = []
# 코스피 종목구성.
dictcondi = {'시장구분':"2" }
dictproj = {"PER":1, "PBR":1, "_id":0}
objret = coll주식종목Data.find(dictcondi, dictproj)
for obj in objret :
per = obj["PER"]
if per > -10 and per <= 100 :
listKOSDACPER.append(per)
pbr = obj["PBR"]
if pbr > -10 and pbr <= 40:
listKOSDACPBR.append(pbr)
plotjongmok.plotHistogram([listKOSPIPBR,listKOSDACPBR ], ["PBR_KOSPI", "PBR_KOSDAC"])
plotjongmok.plotHistogram([listKOSPIPER,listKOSDACPER ], ["PER_KOSPI", "PER_KOSDAC"])
chi2, p = stats.chisquare(listKOSPIPER)
print('chisquare output')
print('Z-score = ' + str(chi2))
print('P-value = ' + str(p))
def createHistogramOfJongmok(Jongmokhan) :
'''
종목의 종가를 histogram을 그린다.
:param Jongmokhan:
:return:
'''
coll주식종목Data = pymongo.MongoClient('localhost', 27017).get_database("xadb").get_collection("주식종목Data")
dictcondi = {'종목명':Jongmokhan }
dictproj = { "주식차트_일주월.종가":1, "_id":0 }
objret = coll주식종목Data.find_one(dictcondi, dictproj)
listdictdatestrprice = objret["주식차트_일주월"]
listprice = []
for dictdatestrprice in listdictdatestrprice :
listprice.append(dictdatestrprice["종가"])
plotjongmok.plotHistogram([listprice ], [Jongmokhan])
# 전날 종가대비 가격 변동율의 histogram
listdiffrate =[]
priceprev = listprice[0]
for price in listprice :
listdiffrate.append((price- priceprev)/priceprev)
priceprev = price
plotjongmok.plotHistogram([listdiffrate ], ["price diff rate of " + Jongmokhan])
# chi2, p = stats.normaltest(listdiffrate)
# print('normaltest output')
# print('Z-score = ' + str(chi2))
# print('P-value = ' + str(p))
#
# chi2, p = stats.chisquare(listKOSPIPBR)
# print('chisquare output')
# print('Z-score = ' + str(chi2))
# print('P-value = ' + str(p))