Merge pull request #7 from andrewkdinh/personal-pc

Personal pc
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Andrew Dinh 2019-01-22 18:56:17 +00:00 committed by GitHub
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7 changed files with 282 additions and 73 deletions

3
.gitignore vendored
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@ -3,3 +3,6 @@ __pycache__/
*.pyc
quickstart.py
creds.json
test/
.vscode/
listGoogle.py

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@ -12,6 +12,10 @@ import numpy
from urllib.request import urlopen
import re
class ExpenseRatio:
def __init__(self):
def main(): # For testing purposes
'''
a = [1,2,3]
@ -19,21 +23,6 @@ def main(): # For testing purposes
c = numpy.corrcoef(a, b)[0, 1]
print(c)
'''
#http://finance.yahoo.com/q/pr?s=spy+profile
stockSymbols = [ "VDIGX", "VFIAX" ]
expenses = [ [ "Fund", "Most Recent Expense Ratio" ] ]
for stockSymbol in stockSymbols:
page = urlopen("http://finance.yahoo.com/q/pr?s=" + stockSymbol + "+profile" )
data = str(page.read())
row = re.findall("Annual Report Expense Ratio.*?</tr>", data)
if len(row) > 0:
ER = re.findall("<td.*?>(\d+\.\d+).*?</td>", row[0] )[0]
expenses.append( [ stockSymbol, ER ] )
else:
print(stockSymbol, "does not appear to be a fund with an expense ratio")
print("\n".join( i[0] + "," + i[1] for i in expenses))
if __name__ == "__main__":
main()

24
Functions.py Normal file
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@ -0,0 +1,24 @@
# Python file for general functions
class Functions:
def getNearest(items, pivot):
return min(items, key=lambda x: abs(x - pivot))
def stringToDate(date):
from datetime import datetime
#datetime_object = datetime.strptime('Jun 1 2005 1:33PM', '%b %d %Y %I:%M%p')
datetime_object = datetime.strptime(date, '%Y-%m-%d').date()
return(datetime_object)
'''
dateSplit = date.split('-')
year = int(dateSplit[0])
month = int(dateSplit[1])
day = int(dateSplit[2])
datetime_object = datetime.date(year, month, day)
'''
return datetime_object
def main():
exit()
if __name__ == "__main__":
main()

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@ -4,9 +4,11 @@ A project to determine indicators of overperforming mutual funds.
This project is written in Python and will examine market capitalization, persistence, turnover, and expense ratios.
### Prerequisites
```sh
$ pip install requests
$ pip install numpy
```
`$ pip install -r requirements.txt`
or
`$ pip install requests`
Created by Andrew Dinh from Dr. TJ Owens Gilroy Early College Academy

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@ -29,17 +29,16 @@ Daily Requests = 20,000
Symbol Requests = 500
'''
import requests, json, socket
import importlib.util, sys # To check whether a package is installed
import requests, json
from datetime import datetime
class Stock:
class StockData:
def __init__(self, newName = '', newFirstLastDates = [], newAbsFirstLastDates = [], newFinalDatesAndClose = [], newAllLists = []):
def __init__(self, newName = '', newAbsFirstLastDates = [], newFinalDatesAndClose = [], newFinalDatesAndClose2 = [],newAllLists = []):
self.name = newName # Name of stock
self.firstLastDates = newFirstLastDates # Dates that at least 2 sources have (or should it be all?) - Maybe let user decide
self.absFirstLastDates = newAbsFirstLastDates # Absolute first and last dates from all sources
self.finalDatesAndClose = newFinalDatesAndClose # All available dates
self.finalDatesAndClose = newFinalDatesAndClose # All available dates with corresponding close values
self.finalDatesAndClose2 = newFinalDatesAndClose2 # After some consideration, I decided to keep what I had already done here and make a new list that's the same except dates are in datetime format
self.allLists = newAllLists
'''
Format:
@ -59,9 +58,18 @@ class Stock:
def setName(self, newName):
self.name = newName
def getAllLists(self):
def returnName(self):
return self.name
def returnAllLists(self):
return self.allLists
def returnAbsFirstLastDates(self):
return self.absFirstLastDates
def returnAllLists(self):
return self.allLists
def returnFinalDatesAndClose(self):
return self.finalDatesAndClose
def returnFinalDatesAndClose2(self):
return self.finalDatesAndClose2
def getIEX(self):
url = ''.join(('https://api.iextrading.com/1.0/stock/', self.name, '/chart/5y'))
@ -133,9 +141,17 @@ class Stock:
def getAV(self):
listAV = []
url = ''.join(('https://www.alphavantage.co/query?function=TIME_SERIES_MONTHLY&symbol=', self.name, '&apikey=', apiAV))
#url = ''.join(('https://www.alphavantage.co/query?function=TIME_SERIES_MONTHLY&symbol=', self.name, '&apikey=', apiAV))
# https://www.alphavantage.co/query?function=TIME_SERIES_MONTHLY&symbol=MSFT&apikey=demo
#url = ''.join(('https://www.alphavantage.co/query?function=TIME_SERIES_DAILY&symbol=', self.name, '&outputsize=full&apikey=', apiAV))
# https://www.alphavantage.co/query?function=TIME_SERIES_DAILY&symbol=MSFT&outputsize=full&apikey=demo
url = ''.join(('https://www.alphavantage.co/query?function=TIME_SERIES_DAILY_ADJUSTED&symbol=', self.name, '&outputsize=full&apikey=', apiAV))
# https://www.alphavantage.co/query?function=TIME_SERIES_DAILY_ADJUSTED&symbol=MSFT&outputsize=full&apikey=demo
print("\nSending request to:", url)
print("(This will take a while)")
f = requests.get(url)
json_data = f.text
loaded_json = json.loads(json_data)
@ -148,9 +164,9 @@ class Stock:
return 'Not available'
#print(loaded_json['Monthly Time Series'])
monthlyTimeSeries = loaded_json['Monthly Time Series']
dailyTimeSeries = loaded_json['Time Series (Daily)']
#print(monthlyTimeSeries)
listOfDates = list(monthlyTimeSeries)
listOfDates = list(dailyTimeSeries)
#print(listOfDates)
firstDate = listOfDates[-1]
@ -171,8 +187,9 @@ class Stock:
values = []
for i in range(0, len(listOfDates), 1):
temp = listOfDates[i]
loaded_json2 = monthlyTimeSeries[temp]
value = loaded_json2['4. close']
loaded_json2 = dailyTimeSeries[temp]
#value = loaded_json2['4. close']
value = loaded_json2['5. adjusted close']
values.append(value)
listAV.append(values)
#print(listOfDates[0])
@ -430,7 +447,25 @@ class Stock:
finalDatesAndClose.append(finalClose)
return finalDatesAndClose
def datetimeDates(self):
finalDatesAndClose2 = []
finalDatesAndClose = self.finalDatesAndClose
finalDatesStrings = finalDatesAndClose[0]
finalClose = finalDatesAndClose[1]
finalDates = []
from Functions import Functions
for i in range(0, len(finalDatesStrings), 1):
temp = Functions.stringToDate(finalDatesStrings[i])
finalDates.append(temp)
#print(finalDates)
finalDatesAndClose2.append(finalDates)
finalDatesAndClose2.append(finalClose)
return(finalDatesAndClose2)
def is_connected():
import socket # To check internet connection
try:
# connect to the host -- tells us if the host is actually
# reachable
@ -442,6 +477,7 @@ class Stock:
return False
def main(self):
import importlib.util, sys # To check whether a package is installed
packages = ['requests']
for i in range(0, len(packages), 1):
@ -451,16 +487,18 @@ class Stock:
print(package_name +" is not installed\nPlease type in 'pip install -r requirements.txt' to install all required packages")
# Test internet connection
internetConnection = Stock.is_connected()
internetConnection = StockData.is_connected()
if internetConnection == False:
return
listOfFirstLastDates = []
self.allLists = []
print('\nNOTE: Only IEX and Alpha Vantage support adjusted returns')
# IEX
print("\nIEX")
listIEX = Stock.getIEX(self)
listIEX = StockData.getIEX(self)
#print(listIEX)
if listIEX != 'Not available':
listOfFirstLastDates.append((listIEX[0], listIEX[1]))
@ -468,7 +506,7 @@ class Stock:
# Alpha Vantage
print("\nAlpha Vantage (AV)")
listAV = Stock.getAV(self)
listAV = StockData.getAV(self)
#print(listAV)
if listAV != 'Not available':
listOfFirstLastDates.append((listAV[0], listAV[1]))
@ -477,7 +515,8 @@ class Stock:
# COMMENTED OUT FOR NOW B/C LIMITED
'''
print("\nTiingo")
listTiingo = Stock.getTiingo(self)
print("NOTE: Tiingo does not return adjusted returns!!")
listTiingo = StockData.getTiingo(self)
#print(listTiingo)
if listTiingo != 'Not available':
listOfFirstLastDates.append((listTiingo[0], listTiingo[1]))
@ -488,27 +527,32 @@ class Stock:
#print(listOfFirstLastDates)
if (len(self.allLists) > 0):
print("\n")
print(len(self.allLists), "available sources for", self.name)
self.absFirstLastDates = Stock.getFirstLastDate(self, listOfFirstLastDates)
print(len(self.allLists), "available source(s) for", self.name)
self.absFirstLastDates = StockData.getFirstLastDate(self, listOfFirstLastDates)
print("\nThe absolute first date with close values is:", self.absFirstLastDates[0])
print("The absolute last date with close values is:", self.absFirstLastDates[1])
print("\nCombining dates and averaging close values")
self.finalDatesAndClose = Stock.getFinalDatesAndClose(self) # Returns [List of Dates, List of Corresponding Close Values]
self.finalDatesAndClose = StockData.getFinalDatesAndClose(self) # Returns [List of Dates, List of Corresponding Close Values]
#print("All dates available:", self.finalDatesAndClose[0])
#print("All close values:\n", self.finalDatesAndClose[1])
finalDates = self.finalDatesAndClose[0]
finalClose = self.finalDatesAndClose[1]
print(len(finalDates), "unique dates:", finalDates[len(finalDates)-1], "...", finalDates[0])
print(len(finalClose), "close values:", finalClose[len(finalClose)-1], "...", finalClose[0])
print("\nConverting list of final dates to datetime")
self.finalDatesAndClose2 = StockData.datetimeDates(self)
#print(self.finalDatesAndClose2[0][0])
else:
print("No sources have data for", self.name)
def main(): # For testing purposes
stockName = 'spy'
stock1 = Stock(stockName)
stock1 = StockData(stockName)
print("Finding available dates and close values for", stock1.name)
Stock.main(stock1)
StockData.main(stock1)
if __name__ == "__main__":
main()

141
StockReturn.py Normal file
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@ -0,0 +1,141 @@
# ExpenseRatio.py
# Andrew Dinh
# Python 3.6.7
# Description:
'''
Calculates return for each stock from the lists from ExpenseRatio.py
listOfReturn = [Unadjsted Return, Sharpe Ratio, Sortino Ratio, Treynor Ratio, Jensen's Alpha]
'''
from StockData import StockData
import datetime
from Functions import Functions
class Return:
def __init__(self, newListOfReturn = [], newTimeFrame = [], newBeta = 0, newStandardDeviation = 0, newNegativeStandardDeviation = 0, newMarketReturn = 0, newSize = 0, newSizeOfNeg = 0, newFirstLastDates = [], newAllLists = [], newAbsFirstLastDates = ''):
self.listOfReturn = newListOfReturn
self.timeFrame = newTimeFrame # [year, months (30 days)]
self.beta = newBeta
self.standardDeviation = newStandardDeviation
self.negativeStandardDeviation = newNegativeStandardDeviation
self.marketReturn = newMarketReturn
self.size = newSize
self.sizeOfNeg = newSizeOfNeg
self.firstLastDates = newFirstLastDates
def getFirstLastDates(self, stock):
firstLastDates = []
timeFrame = self.timeFrame
firstDate = datetime.datetime.now() - datetime.timedelta(days=timeFrame[0]*365)
firstDate = firstDate - datetime.timedelta(days=timeFrame[1]*30)
firstDate = ''.join((str(firstDate.year),'-', str(firstDate.month), '-', str(firstDate.day)))
lastDate = StockData.returnAbsFirstLastDates(stock)[1]
#print(lastDate)
firstLastDates.append(firstDate)
firstLastDates.append(lastDate)
return firstLastDates
def getFirstLastDates2(self, stock):
finalDatesAndClose = StockData.returnFinalDatesAndClose(stock)
finalDatesAndClose2 = StockData.returnFinalDatesAndClose2(stock)
firstDate = self.firstLastDates[0]
lastDate = self.firstLastDates[1]
finalDates = finalDatesAndClose[0]
firstDateExists = False
lastDateExists = False
for i in range(0, len(finalDates), 1):
if finalDates[i] == str(firstDate):
firstDateExists = True
elif finalDates[i] == lastDate:
lastDateExists = True
i = len(finalDates)
if firstDateExists == False:
print("Could not find first date. Changing first date to closest date")
tempDate = Functions.stringToDate(firstDate) # Change to datetime
print('Original first date:', tempDate)
#tempDate = datetime.date(2014,1,17)
newFirstDate = Functions.getNearest(finalDatesAndClose2[0], tempDate)
print('New first date:', newFirstDate)
firstDate = str(newFirstDate)
if lastDateExists == False:
print("Could not find final date. Changing final date to closest date")
tempDate2 = Functions.stringToDate(lastDate) # Change to datetime
print('Original final date:', tempDate2)
#tempDate2 = datetime.date(2014,1,17)
newLastDate = Functions.getNearest(finalDatesAndClose2[0], tempDate2)
print('New final date:', newLastDate)
lastDate = str(newLastDate)
firstLastDates = []
firstLastDates.append(firstDate)
firstLastDates.append(lastDate)
return firstLastDates
def getUnadjustedReturn(self, stock):
finalDatesAndClose = StockData.returnFinalDatesAndClose(stock)
finalDatesAndClose2 = StockData.returnFinalDatesAndClose2(stock)
firstDate = self.firstLastDates[0]
lastDate = self.firstLastDates[1]
finalDates = finalDatesAndClose[0]
finalClose = finalDatesAndClose[1]
for i in range(0, len(finalDates), 1):
if finalDates[i] == str(firstDate):
firstClose = finalClose[i]
elif finalDates[i] == lastDate:
lastClose = finalClose[i]
i = len(finalDates)
print('Close values:', firstClose, '...', lastClose)
unadjustedReturn = float(lastClose/firstClose)
unadjustedReturn = unadjustedReturn * 100
return unadjustedReturn
# def getBeta(self, timeFrame):
# def getStandardDeviation(self, timeFrame):
def main(self, stock):
# Find date to start from and last date
self.timeFrame = []
self.listOfReturn = []
print("\nPlease enter a time frame in years: ", end='')
#timeFrameYear = int(input())
timeFrameYear = 5
print(timeFrameYear)
self.timeFrame.append(timeFrameYear)
print("Please enter a time frame in months (30 days): ", end='')
#timeFrameMonth = int(input())
timeFrameMonth = 0
print(timeFrameMonth)
self.timeFrame.append(timeFrameMonth)
#print(self.timeFrame)
self.firstLastDates = Return.getFirstLastDates(self, stock)
print('Dates: ', self.firstLastDates)
print('\nMaking sure dates are within list...')
self.firstLastDates = Return.getFirstLastDates2(self, stock)
print('New dates: ', self.firstLastDates)
print('\nGetting unadjusted return')
unadjustedReturn = Return.getUnadjustedReturn(self, stock)
self.listOfReturn.append(unadjustedReturn)
print(self.listOfReturn[0])
print(self.listOfReturn[0]/timeFrameYear, '%')
def main():
stockName = 'spy'
stock1 = StockData(stockName)
print("Finding available dates and close values for", stock1.name)
StockData.main(stock1)
stock1Return = Return()
Return.main(stock1Return, stock1)
if __name__ == "__main__":
main()

26
main.py
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@ -15,7 +15,7 @@ Gives correlation value using equation at the end (from 0 to 1)
FIRST TESTING WITH EXPENSE RATIO
'''
from StockData import Stock
from StockData import StockData
listOfStocks = []
numberOfStocks = int(input("How many stocks or mutual funds would you like to analyze? "))
@ -23,30 +23,36 @@ for i in range(0, numberOfStocks, 1):
print("Stock", i+1, ": ", end='')
stockName = str(input())
listOfStocks.append(i)
listOfStocks[i] = Stock()
listOfStocks[i] = StockData()
listOfStocks[i].setName(stockName)
#print(listOfStocks[i].name)
sumOfListLengths = 0
for i in range(0, numberOfStocks, 1):
print(listOfStocks[i].name)
Stock.main(listOfStocks[i])
StockData.main(listOfStocks[i])
# Count how many stocks are available
temp = Stock.getAllLists(listOfStocks[i])
temp = StockData.returnAllLists(listOfStocks[i])
sumOfListLengths = sumOfListLengths + len(temp)
if sumOfListLengths == 0:
print("No sources have stock data for given stocks")
print("No sources have data for given stocks")
exit()
else:
#print(listOfStocks[0].name, listOfStocks[0].absFirstLastDates, listOfStocks[0].finalDatesAndClose)
indicatorFound = False
while indicatorFound == False:
# Find return over time using either Jensen's Alpha, Sharpe Ratio, Sortino Ratio, or Treynor Ratio
#from StockReturn import Return
# Runs correlation or regression study
#print(listOfStocks[0].name, listOfStocks[0].absFirstLastDates, listOfStocks[0].finalDatesAndClose)
indicatorFound = False
while indicatorFound == False:
print("\n1. Expense Ratio\n2. Asset Size\n3. Turnover\n4. Persistence\nWhich indicator would you like to look at? ", end='')
indicator = str(input())
indicatorFound = True
if indicator == 'Expense Ratio' or indicator == '1' or indicator == 'expense ratio':
#from ExpenseRatio import ExpenseRatio
print('\nExpense Ratio')
elif indicator == 'Asset Size' or indicator == '2' or indicator == 'asset size':
@ -66,5 +72,5 @@ else:
stockName = 'IWV'
stock1 = Stock(stockName)
print("Finding available dates and close values for", stock1.name)
Stock.main(stock1)
StockData.main(stock1)
'''