Last commit

README.md

@@ -1,23 +1,17 @@
 # Mutual Fund Indicators
 
 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.
+This project is written in Python 3 and will examine market capitalization, persistence, turnover, and expense ratios.
 
 ### Prerequisites
 
 `$ pip install -r requirements.txt`
 
-or
-
-`$ pip install requests`
-
-`$ pip install numpy`
-
 ### Quickstart
 
 To begin, run
 
-`$ python(3) main.py`
+`$ python main.py`
 
 Some ticker values to try:
 SPY, VFINX, AAPL, GOOGL

StockData.py

@@ -477,6 +477,8 @@ class StockData:
     return False
 
   def main(self):
+    print('Beginning StockData.py')
+    
     import importlib.util, sys # To check whether a package is installed
 
     packages = ['requests']
@@ -495,6 +497,7 @@ class StockData:
     self.allLists = []
 
     print('\nNOTE: Only IEX and Alpha Vantage support adjusted returns')
+    print('NOTE: Only Alpha Vantage and Tiingo support mutual fund data')
 
     # IEX
     print("\nIEX")
@@ -526,7 +529,7 @@ class StockData:
     #print(self.allLists)
     #print(listOfFirstLastDates)
     if (len(self.allLists) > 0):
-      print("\n")
+      print("\n", end='')
       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])
@@ -541,7 +544,7 @@ class StockData:
       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")
+      print("\nConverting list of final dates to datetime\n")
       self.finalDatesAndClose2 = StockData.datetimeDates(self)
       #print(self.finalDatesAndClose2[0][0])
 

StockReturn.py

@@ -4,7 +4,7 @@
 # Description:
 '''
 Calculates return for each stock from the lists from ExpenseRatio.py
-listOfReturn = [Unadjsted Return, Sharpe Ratio, Sortino Ratio, Treynor Ratio, Jensen's Alpha]
+listOfReturn = [Unadjusted Return, Sharpe Ratio, Sortino Ratio, Treynor Ratio, Jensen's Alpha]
 '''
 
 from StockData import StockData
@@ -14,7 +14,7 @@ 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.timeFrame = newTimeFrame # [years, months (30 days)]
         self.beta = newBeta
         self.standardDeviation = newStandardDeviation
         self.negativeStandardDeviation = newNegativeStandardDeviation
@@ -23,6 +23,12 @@ class Return:
         self.sizeOfNeg = newSizeOfNeg
         self.firstLastDates = newFirstLastDates
 
+    def returnTimeFrame(self):
+        return self.timeFrame
+
+    def setTimeFrame(self, newTimeFrame):
+        self.timeFrame = newTimeFrame
+
     def getFirstLastDates(self, stock):
         firstLastDates = []
         timeFrame = self.timeFrame
@@ -77,7 +83,6 @@ class Return:
 
     def getUnadjustedReturn(self, stock):
         finalDatesAndClose = StockData.returnFinalDatesAndClose(stock)
-        finalDatesAndClose2 = StockData.returnFinalDatesAndClose2(stock)
         firstDate = self.firstLastDates[0]
         lastDate = self.firstLastDates[1]
         finalDates = finalDatesAndClose[0]
@@ -91,15 +96,34 @@ class Return:
                 i = len(finalDates)
 
         print('Close values:', firstClose, '...', lastClose)
-        unadjustedReturn = float(lastClose/firstClose)
+        fullUnadjustedReturn = float(lastClose/firstClose)
-        unadjustedReturn = unadjustedReturn * 100
+        unadjustedReturn = fullUnadjustedReturn**(1/(self.timeFrame[0]+(self.timeFrame[1])*.1))
         return unadjustedReturn
 
-#    def getBeta(self, timeFrame):
+    def getBeta(self):
+        # Can be calculated with correlation
+        import numpy as np
+
+        finalDatesAndClose = StockData.returnFinalDatesAndClose(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]
+55ggbh
+        #list1 = 
+        list2 = [1,2,4,1]
+
+        print(numpy.corrcoef(list1, list2)[0, 1])
 
 #    def getStandardDeviation(self, timeFrame):
 
-    def main(self, stock):
+    def mainBenchmark(self, stock):
+        print('Beginning StockReturn.py')
+
         # Find date to start from and last date
         self.timeFrame = []
         self.listOfReturn = []
@@ -125,8 +149,31 @@ class Return:
         print('\nGetting unadjusted return')
         unadjustedReturn = Return.getUnadjustedReturn(self, stock)
         self.listOfReturn.append(unadjustedReturn)
-        print(self.listOfReturn[0])
+        print('Average annual return for the past', self.timeFrame[0], 'years and', self.timeFrame[1], 'months: ', end='')
-        print(self.listOfReturn[0]/timeFrameYear, '%')
+        print((self.listOfReturn[0]-1)*100, '%', sep='')
+
+
+    def main(self, stock):
+        print('Beginning StockReturn.py')
+
+        # Find date to start from and last date
+        self.listOfReturn = []
+
+        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('Average annual return for the past', self.timeFrame[0], 'years and', self.timeFrame[1], 'months: ', end='')
+        print((self.listOfReturn[0]-1)*100, '%', sep='')
+
+        #print('\nGetting beta')
+        #beta = Return.getBeta(self, stock)
 
 def main():
     stockName = 'spy'
@@ -135,6 +182,8 @@ def main():
     StockData.main(stock1)
 
     stock1Return = Return()
+    Return.setTimeFrame(stock1Return, [5, 0])
+
     Return.main(stock1Return, stock1)
 
 if __name__ == "__main__":

main.py

@@ -16,40 +16,83 @@ FIRST TESTING WITH EXPENSE RATIO
 '''
 
 from StockData import StockData
+from StockReturn import Return
 
-listOfStocks = []
+listOfStocksData = []
-numberOfStocks = int(input("How many stocks or mutual funds would you like to analyze? "))
+listOfStocksReturn = []
+#numberOfStocks = int(input("How many stocks or mutual funds would you like to analyze? ")) # CHANGE BACK LATER
+numberOfStocks = 1
 for i in range(0, numberOfStocks, 1):
   	print("Stock", i+1, ": ", end='')
   	stockName = str(input())
-  	listOfStocks.append(i)
+  	listOfStocksData.append(i)
-  	listOfStocks[i] = StockData()
+  	listOfStocksData[i] = StockData()
-  	listOfStocks[i].setName(stockName)
+  	listOfStocksData[i].setName(stockName)
-  	#print(listOfStocks[i].name)
+	# print(listOfStocksData[i].name)
+
+	#listOfStocksReturn.append(i)
+	#listOfStocksReturn[i] = StockReturn()
+
+
+# Decide on a benchmark
+benchmarkTicker = ''
+while benchmarkTicker == '':
+	listOfBenchmarks = ['S&P500', 'DJIA', 'Russell 3000', 'MSCI EAFE']
+	listOfBenchmarksTicker = ['SPY', 'DJIA', 'VTHR', 'EFT']
+	print('\nList of benchmarks:', listOfBenchmarks)
+	#benchmark = str(input('Benchmark to compare to: '))
+	benchmark = 'S&P500'
+
+	for i in range(0,len(listOfBenchmarks), 1):
+		if benchmark == listOfBenchmarks[i]:
+			benchmarkTicker = listOfBenchmarksTicker[i]
+			i = len(listOfBenchmarks)
+
+	if benchmarkTicker == '':
+		print('Benchmark not found. Please type in a benchmark from the list')
+
+print('\n', benchmark, ' (', benchmarkTicker, ')', sep='')
+
+benchmarkName = str(benchmark)
+benchmark = StockData()
+benchmark.setName(benchmarkName)
+StockData.main(benchmark)
+
+benchmarkReturn = Return()
+Return.mainBenchmark(benchmarkReturn, benchmark)
+
+timeFrame = Return.returnTimeFrame(benchmarkReturn)
+print('Time Frame [years, months]:', timeFrame)
 
 sumOfListLengths = 0
 for i in range(0, numberOfStocks, 1):
-  	print(listOfStocks[i].name)
+  	print('\n', listOfStocksData[i].name, sep='')
-  	StockData.main(listOfStocks[i])
+  	StockData.main(listOfStocksData[i])
   	# Count how many stocks are available
-  	temp = StockData.returnAllLists(listOfStocks[i])
+  	sumOfListLengths = sumOfListLengths + len(StockData.returnAllLists(listOfStocksData[i]))
-  	sumOfListLengths = sumOfListLengths + len(temp)
 
 if sumOfListLengths == 0:
     print("No sources have data for given stocks")
     exit()
 
 # Find return over time using either Jensen's Alpha, Sharpe Ratio, Sortino Ratio, or Treynor Ratio
-#from StockReturn import Return
+for i in range(0, numberOfStocks, 1):
+	print('\n', listOfStocksData[i].name, sep='')
+	#StockReturn.main(listOfStocksReturn[i])
 
 
 # Runs correlation or regression study
-#print(listOfStocks[0].name, listOfStocks[0].absFirstLastDates, listOfStocks[0].finalDatesAndClose)
+# print(listOfStocksData[0].name, listOfStocksData[0].absFirstLastDates, listOfStocksData[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='')
+	print("1. Expense Ratio\n2. Asset Size\n3. Turnover\n4. Persistence\nWhich indicator would you like to look at? ", end='')
-	indicator = str(input())
+	
+	#indicator = str(input()) # CHANGE BACK TO THIS LATER
+	indicator = 'Expense Ratio'
+	print(indicator, end='')
+
 	indicatorFound = True
+	print('\n', end='')
 
 	if indicator == 'Expense Ratio' or indicator == '1' or indicator == 'expense ratio':
         #from ExpenseRatio import ExpenseRatio
@@ -66,7 +109,7 @@ while indicatorFound == False:
 
 	else:
 		indicatorFound = False
-		print('\nInvalid input, please enter indicator again')
+		print('Invalid input, please enter indicator again')
 
 '''
 stockName = 'IWV'