disMoney = shareTotal * d[1]
if stype == BONUS_SHARE: # 红利再投
shareTotal += disMoney / sT.getFundPrice(code[i], d[2])[1]
else: # 现金红利
bonusTotal += disMoney
d0 = date
moneyTotal = moneyTotal + float(t[2].replace(",", ""))
diff = float(t[1]) * shareTotal - moneyTotal
rate = diff / moneyTotal
rateList.append(rate * 100.0)
#print((dateList)
dataList.append([dateList, rateList])
for i in range(len(dataList)): #日期选择一个日期，坐标轴不能有两种不同的日期表示
plt.plot(dataList[0][0], dataList[i][1], label=name[i])
ax = plt.gca()
ax.yaxis.set_major_locator(
mpl.ticker.MultipleLocator(1 if sT.createCalender().dayDiff(
STARTYEAR, STARTMONTH, STARTDAY, ENDYEAR, ENDMONTH, ENDDAY) < 365 *
3 else 5))
ax.yaxis.set_major_formatter(mpl.ticker.FormatStrFormatter("%.0f%%"))
ax.axhline(color='black', y=0)
mpl.rcParams['font.sans-serif'] = ['SimHei'] # 指定默认字体
plt.legend(loc=0, ncol=len(dataList), mode="expand", borderaxespad=0.0)
plt.gcf().autofmt_xdate()
plt.grid(True)
plt.show()
bestRate = rate
bestRateTime = tradeDate
bestEarn = profit
if ENDMONTH==12:
year = ENDYEAR+1
month = 1
else:
year = ENDYEAR
month = ENDMONTH+1
foundData,closePrice,actualMonth, day=sT.getClosePriceBackward(code[i],ENDYEAR, ENDMONTH, ENDDAY)
if foundData==True:
nCapitalTotal = nStockTotal*closePrice+ndividend
income = nCapitalTotal-nCapitalInvest
incomeRate = income/nCapitalInvest
investPeriod = round(sT.createCalender().dayDiff(STARTYEAR,STARTMONTH,1,year,actualMonth,day)/365.0, 2)
dictColumnValues[u'代码'] = code[i]
dictColumnValues[u'名称'] = name[i]
dictColumnValues[u'投资年数'] = investPeriod
dictColumnValues[u'投资起始时间'] = sT.getDateString(STARTYEAR,STARTMONTH,1)
dictColumnValues[u'卖出股份时间'] = sT.getDateString(ENDYEAR,ENDMONTH,ENDDAY)
dictColumnValues[u'投资总成本'] = nCapitalInvest
dictColumnValues[u'投资总市值'] = nCapitalTotal
dictColumnValues[u'投资总收益'] = income
dictColumnValues[u'分红'] = ndividend
dictColumnValues[u'平均年收益'] = round(income/investPeriod,2)
dictColumnValues[u'投资收益率'] = round(incomeRate,4)
dictColumnValues[u'投资年化复合收益率'] = round(((incomeRate+1)**(1.0/investPeriod)-1),4)
dictColumnValues[u'总股本'] = nStockTotal
dictColumnValues[u'购买股本'] = nStockInvest
dictColumnValues[u"每月最小投资额"] = nMinInvPerMonth
if year > LASTYEAR:
_, closePrice, _, _ = sT.getClosePriceForward(code, date)
else:
_, closePrice, m2, d2 = sT.getClosePriceForward(code, year, 12, 31)
PEList.append(0 if EPS <= 0 else closePrice / EPS)
PEDiscList.append(0 if epsdic <= 0 else closePrice / epsdic)
PriceList.append(closePrice * totalStock) # 得到当年总市值
print( sT.getDateString(year,m2,d2),",BasicPETTM=",PEList[-1],", ","discountPETTM=",PEDiscList[-1],\
"stockcount=",totalStock,"priceTotal=", round(PriceList[-1]/10**4,0), ",EPSTTM=",EPS,\
",EPSDicountTTM=",epsdic)
drawPE = PEList[-1]
for dt in DATA2WATCH:
y1, m1, d1 = sT.splitDateString(dt)
if y1 == year:
foundData = False
qt = sT.createCalender().getQuarter(m1)
if qt == 1:
foundData, EPSTTM = sT.getStockEPSTTM(code, y1 - 1, 4)
_, EPSdiscountTTM = sT.getStockEPSdiscountTTM(code, y1 - 1, 4)
#totalStock = sT.getStockCountQuarter(code, y1 - 1, 4)
totalStock = sT.getStockCount(code, y1, m1, d1)
else:
qt = qt - 1 #本季度报表没有出来，因此使用上季度报表
while qt > 0 and not foundData:
foundData, EPSTTM = sT.getStockEPSTTM(code, y1, qt)
if not foundData:
qt = qt - 1
continue
#totalStock = sT.getStockCountQuarter(code, y1, qt)
totalStock = sT.getStockCount(code, y1, m1, d1)
_, EPSdiscountTTM = sT.getStockEPSdiscountTTM(code, y1, qt)
rateWorst = rate
dateRateWorst = t[0]
lostWorst = diff
if rateBest < rate:
rateBest = rate
dateRateBest = t[0]
earnBest = diff
# print(totalValue-investTotal)
# print(shareTotal*sT.getFundPrice(code[i], endDate)[1]-moneyTotal)
# print(totalValue==shareTotal*sT.getFundPrice(code[i], endDate)[1],investTotal==moneyTotal )
# print shareTotal, totalValue/sT.getFundPrice(code[i], endDate)[1]
rate = (totalValue -
investTotal) / investTotal #float(infoStr[6][:-1])/100.0
investPeriod = round(
sT.createCalender().dayDiff(STARTYEAR, STARTMONTH, STARTDAY, ENDYEAR,
ENDMONTH, ENDDAY) / 365.0, 2)
ratePerYear = round(((rate + 1)**(1.0 / investPeriod) - 1), 4)
dictColumnValues[u'代码'] = code[i]
dictColumnValues[u'名称'] = name[i]
dictColumnValues[u'定投年数'] = investPeriod
dictColumnValues[u'定投起始时间'] = startDate
#dictColumnValues[u'定投结束时间'] = endDate
dictColumnValues[u'卖出基金时间'] = endDate
dictColumnValues[u'投资总成本'] = moneyTotal
dictColumnValues[u'投资总市值'] = moneyTotal * (1 + rate)
dictColumnValues[u'投资总收益'] = moneyTotal * rate
dictColumnValues[u'分红'] = bonusTotal
dictColumnValues[u'平均年收益'] = round(
dictColumnValues[u'投资总收益'] / investPeriod, 2)
dictColumnValues[u'投资收益率'] = round(rate, 4)
dictColumnValues[u'投资年化复合收益率'] = ratePerYear
else:
lost = nStockTotal * price + ndividend - nCapitalInvest
if lostMoneyMax > lost: #由于计算时只计算检查日时的最大回撤，可能有比检查日回撤更大的时候，尤其是最后卖出时。
lostMoneyMax = lost
lostMoneyMaxCaption = nCapitalInvest
lostMoneyMaxTime = sT.getDateString(year, m, d)
foundData, closePrice, saleMonth, actualsaleDay = sT.getClosePriceBackward(
code[i], ENDYEAR, ENDMONTH, saleDay)
#year = ENDYEAR
if foundData == True:
nCapitalTotal = nStockTotal * closePrice + ndividend
income = nCapitalTotal - nCapitalInvest
incomeRate = income / nCapitalInvest
investPeriod = round(
sT.createCalender().dayDiff(STARTYEAR, STARTMONTH, buyDay, ENDYEAR,
ENDMONTH, saleDay) / 365.0, 2)
dictColumnValues[u'代码'] = code[i]
dictColumnValues[u'名称'] = name[i]
dictColumnValues[u'投资时长（年）'] = investPeriod
dictColumnValues[u'投资起始时间'] = sT.getDateString(STARTYEAR, STARTMONTH,
buyDay)
dictColumnValues[u'卖出股份时间'] = sT.getDateString(year, saleMonth,
actualsaleDay)
dictColumnValues[u'投资总成本'] = nCapitalInvest
dictColumnValues[u'投资总市值'] = nCapitalTotal
dictColumnValues[u'投资总收益'] = income
dictColumnValues[u'分红'] = ndividend
dictColumnValues[u'平均年收益'] = round(income / investPeriod, 2)
dictColumnValues[u'投资收益率'] = round(incomeRate, 4)
dictColumnValues[u'投资年化复合收益率'] = round(
((incomeRate + 1)**(1.0 / investPeriod) - 1), 4)
url = "http://fund.eastmoney.com/f10/F10DataApi.aspx?type=lsjz&code=" + code[
i]
url = url + "&page=1&per=20&sdate="
url = url + dateToSearch
url = url + "&edate="
url = url + dateToSearch
url = url + "&rt=0.19110643402290917"
data = urllib.urlopen(url).read()
bs = bs4.BeautifulSoup(data, "html.parser")
try:
closePrice = float(bs.find_all("td")[2].get_text())
foundData = 1
except Exception, e:
print code[i], name[i], u"没有今日数据!", dateToSearch
y, m, d = sT.splitDateString(dateToSearch)
y, m, d = sT.createCalender().getPrevWorkday(y, m, d)
dateToSearch = sT.getDateString(y, m, d)
elif market[i] != "fund":
found, closePrice, am, actualDay = sT.getClosePriceForward(code[i],
date,
autp=None)
dateToSearch = sT.getDateString(y, am, actualDay)
if found == True:
foundData = 1
else:
foundData = 0
if foundData == 1:
print code[i], name[i], closePrice, dateToSearch
#如果中间有既不是股票也不是基金的行，i值也会+1，就相当于在excel中插入不是股票和基金的空行
worksheet.write(i, 0, code[i])
for i in range(count):
foundData = 0
if code[i] == u'' : continue
url = "http://fundex.eastmoney.com/FundWebServices/FundSylCalculator.aspx?fc=" + code[i]
url = url + "&stime=" + startDate + "&etime=" + saleDate
url = url + "&stype=" + stype + "&sgfl=" + "0" + "&shfl=" + "0" + "&sg=" + "10000" + "&lx=1"
data = urllib.urlopen(url).read()
time.sleep(1)
infoStr = data.split(':')
if infoStr[0]=='var Result={"error"':
print data
continue
rateList = data.split(":")[4].split(",")[0].split('"')
rate = float(rateList[1])/100.0
investPeriod = round(sT.createCalender().dayDiff(STARTYEAR,STARTMONTH,1,ENDYEAR,ENDMONTH,endDay)/365.0, 2)
ratePerYear = round(((rate + 1) ** (1.0 / investPeriod) - 1), 4)
worksheet.write(i+1, 0, code[i])
worksheet.write(i+1, 1, name[i])
worksheet.write(i+1, 2, rate, style_percent)
worksheet.write(i+1, 3, ratePerYear, style_percent)
worksheet.write(i+1, 4, startDate)
worksheet.write(i+1, 5, saleDate)
print code[i], name[i], "收益：%.2f%%" % (rate * 100.0), "年化收益：%.2f%%" % (ratePerYear * 100.0)
workbook.save('.\\data\\dataResult.xls')
print "Invest result has been wrotten to dataResult.xls"