andrewkdinh/fund-indicators
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Added options to restart program and plot indicator linear regression

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Added link to the essay that was the basis of this project
This commit is contained in:
Andrew Dinh 2019-04-15 23:08:01 -07:00
parent fa3be3d7b9
commit a8b7b794ec
4 changed files with 209 additions and 134 deletions
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2
CONTRIBUTING.md
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@ -30,7 +30,7 @@ To develop on fund-indicators you'll probably want to:
1. Read the [code of conduct](https://github.com/andrewkdinh/fund-indicators/blob/master/CODE-OF-CONDUCT.md)
2. Install normally, as documented in the [README](https://github.com/andrewkdinh/fund-indicators#quickstart)
3. Read the [documentation](https://github.com/andrewkdinh/fund-indicators/wiki) (although it's not much)
4. Read the section below to understand the ways you could best help this project
4. Read the section above to understand the ways you could best help this project
## Questions?

34
Functions.py
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@ -216,6 +216,40 @@ def getWeather():
print(colored('Current weather in ' + f.text, 'green'), end='')
def detectDisplay():
import os
try:
t = os.environ["DISPLAY"]
except KeyError:
return False
if t == ':0.0':
return True
else:
return False
def trueOrFalse():
found = False
print('[1] Yes\n[2] No')
while found is False:
answer = str(input('Answer: '))
if stringIsInt(answer) is True:
temp = int(answer)
if temp == 1:
return True
elif temp == 2:
return False
else:
print('Please choose either 1 or 2')
pass
elif answer.lower() == 'yes':
return True
elif answer.lower() == 'no':
return False
else:
print('Please either choose a number or type an answer')
def main():
exit()

22
README.md
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@ -6,16 +6,10 @@
![](https://img.shields.io/github/languages/code-size/andrewkdinh/fund-indicators.svg)
[![CII Best Practices](https://bestpractices.coreinfrastructure.org/projects/2667/badge)](https://bestpractices.coreinfrastructure.org/projects/2667)
A project to determine relationships between mutual fund performance and different factors.
fund-indicators is a cross-platform Python application that allows users to easily find relationships between various attributes of mutual funds and previous performance. This project is based on research from [*Performance Indicators of Mutual Funds*](https://nextcloud.andrewkdinh.com/s/xNgGQ4nPNkSqJti).
[![asciicast demo](https://asciinema.org/a/jLmZapnMFGCRiiSUITY21erLW.svg)](https://asciinema.org/a/jLmZapnMFGCRiiSUITY21erLW?autoplay=1&preload=1)
Calculates relationships between: Previous performance, Alpha, Sharpe Ratio, Sortino Ratio
and Expense ratios, Turnover, Market Capitalization (Asset Size), Persistence
Give it a try at [repl.run](https://fund-indicators.andrewkdinh.repl.run) or [repl.it](https://repl.it/@andrewkdinh/fund-indicators).
## Key Features
- 100% automated
@ -26,9 +20,14 @@ Give it a try at [repl.run](https://fund-indicators.andrewkdinh.repl.run) or [re
- Optional graphs to easily visualize linear regression results
- A new joke every time
- Cross-platform (tested on Windows and Linux)
- Simple to use
## Quickstart
Give it a try at [repl.run](https://fund-indicators.andrewkdinh.repl.run) or [repl.it](https://repl.it/@andrewkdinh/fund-indicators).
If you would like to clone to your own machine:
```shell
git clone https://github.com/andrewkdinh/fund-indicators.git && cd fund-indicators
pip install -r requirements.txt
@ -38,7 +37,12 @@ python main.py
- Common mutual funds are listed in `stocks.txt`
- Configure and rename `config.example.json` to `config.json` if you would like to skip beginning questions (only for advanced users)
### Contributing
## Planned Features
- Graphical user interface (GUI)
- Multithreading/asynchronous requests
## Contributing
Want to help? Great! Check out the [CONTRIBUTING.md](https://github.com/andrewkdinh/fund-indicators/blob/master/CONTRIBUTING.md) file!
@ -46,7 +50,7 @@ Want to help? Great! Check out the [CONTRIBUTING.md](https://github.com/andrewkd
This project utilizes a wide variety of open-source projects:
- [NumPy](https://github.com/numpy/numpy), [Termcolor](https://github.com/hfeeki/termcolor), [Beautiful Soup](https://launchpad.net/beautifulsoup), [yahoofinancials](https://github.com/JECSand/yahoofinancials), [requests-cache](https://github.com/reclosedev/requests-cache), [halo](https://github.com/manrajgrover/halo), [matplotlib](https://github.com/matplotlib/matplotlib), [asciinema](https://github.com/asciinema/asciinema)
- [NumPy](https://github.com/numpy/numpy), [Termcolor](https://github.com/hfeeki/termcolor), [Beautiful Soup](https://launchpad.net/beautifulsoup), [yahoofinancials](https://github.com/JECSand/yahoofinancials), [requests-cache](https://github.com/reclosedev/requests-cache), [halo](https://github.com/manrajgrover/halo), [matplotlib](https://github.com/matplotlib/matplotlib), [asciinema](https://github.com/asciinema/asciinema), [Core Infrastructure Initiative Best Practices Badge](https://github.com/coreinfrastructure/best-practices-badge)
And thank you to those that have helped me with the idea and product:

81
main.py
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@ -19,7 +19,10 @@ from bs4 import BeautifulSoup
import numpy as np
# OPTIONAL
# import matplotlib.pyplot as plt
try:
import matplotlib.pyplot as plt
except:
pass
from halo import Halo
# FOR ASYNC
@ -79,6 +82,7 @@ class Stock:
# CONFIG
removeOutliers = True
sourceList = ['Yahoo', 'Alpha Vantage', 'IEX', 'Tiingo']
plotIndicatorRegression = False
config = 'N/A'
# BENCHMARK VALUES
@ -811,7 +815,7 @@ def benchmarkInit():
benchmarksTicker = ['SPY', 'DJIA', 'VTHR', 'EFT']
print('\nList of benchmarks:')
for i in range(0, len(benchmarks), 1):
print(str(i+1) + '. ' +
print('[' + str(i+1) + '] ' +
benchmarks[i] + ' (' + benchmarksTicker[i] + ')')
while benchmarkTicker == '':
@ -862,7 +866,7 @@ def stocksInit():
'Yahoo top mutual funds (25)']
for i in range(0, len(methods), 1):
print(str(i+1) + '. ' + methods[i])
print('[' + str(i+1) + '] ' + methods[i])
while method == 0 or method > len(methods):
method = str(input('Which method? '))
if Functions.stringIsInt(method) is True:
@ -877,9 +881,9 @@ def stocksInit():
if method == 1:
defaultFiles = ['.gitignore', 'LICENSE', 'main.py', 'Functions.py',
'README.md', 'requirements.txt', 'cache.sqlite',
'yahoofinancials.py', 'termcolor.py',
'README.html', 'config.json',
'config.example.json', '_test_runner.py']
'config.json', 'CONTRIBUTING.md',
'config.example.json', '_test_runner.py',
'CODE-OF-CONDUCT.md']
# Added by repl.it for whatever reason
stocksFound = False
print('Files in current directory (without default files): ')
@ -890,7 +894,7 @@ def stocksInit():
listOfFiles.append(files)
for i in range(0, len(listOfFiles), 1):
if listOfFiles[i][0] != '.':
print(str(i+1) + '. ' + listOfFiles[i])
print('[' + str(i+1) + '] ' + listOfFiles[i])
while stocksFound is False:
fileName = str(input('What is the file number/name? '))
if Functions.stringIsInt(fileName) is True:
@ -921,7 +925,7 @@ def stocksInit():
elif method == 2:
isInteger = False
while isInteger is False:
temp = input('\nNumber of stocks to analyze (2 minimum): ')
temp = input('Number of stocks to analyze (2 minimum): ')
isInteger = Functions.stringIsInt(temp)
if isInteger is True:
if int(temp) >= 2:
@ -1055,6 +1059,7 @@ def stocksInit():
t = k.text.strip()
if len(t) == 5 and Functions.strintIsFloat(t) is False:
if t not in listOfStocksOriginal or listOfStocksOriginal == []:
if t[-1] != '%':
listOfStocksOriginal.append(t)
print(t, end=' ')
listOfStocks.append(k.text.strip())
@ -1156,7 +1161,7 @@ def timeFrameInit():
isInteger = False
while isInteger is False:
print(
'\nPlease enter the time frame in months (<60 months recommended):', end='')
'\nPlease enter the time frame in months (<60 recommended):', end='')
temp = input(' ')
isInteger = Functions.stringIsInt(temp)
if isInteger is True:
@ -1290,12 +1295,12 @@ def returnMain(benchmark, listOfStocks):
listOfStocks[i].sharpe = Stock.calcSharpe(listOfStocks[i])
listOfStocks[i].sortino = Stock.calcSortino(listOfStocks[i])
listOfStocks[i].treynor = Stock.calcTreynor(listOfStocks[i])
listOfStocks[i].linearRegression = Stock.calcLinearRegression(
listOfStocks[i])
# listOfStocks[i].linearRegression = Stock.calcLinearRegression(
# listOfStocks[i])
i += 1
cprint('\nNumber of stocks from original list that fit time frame: ' +
cprint('\nNumber of stocks that fit time frame: ' +
str(len(listOfStocks)), 'green')
if len(listOfStocks) < 2:
# print('Cannot proceed to the next step. Exiting program.')
@ -1306,7 +1311,7 @@ def returnMain(benchmark, listOfStocks):
def outlierChoice():
print('\nWould you like to remove indicator outliers?')
print('1. Yes\n2. No')
print('[1] Yes\n[2] No')
found = False
while found is False:
outlierChoice = str(input('Choice: '))
@ -1333,7 +1338,7 @@ def indicatorInit():
print('\n', end='')
print('List of indicators:')
for i in range(0, len(listOfIndicators), 1):
print(str(i + 1) + '. ' + listOfIndicators[i])
print('[' + str(i + 1) + '] ' + listOfIndicators[i])
while indicatorFound is False:
indicator = str(input('Choose an indicator from the list: '))
@ -1396,7 +1401,8 @@ def calcIndicatorRegression(listOfIndicatorValues, listOfReturns):
regression.append(b[1])
regressionList.append(regression)
# plot_regression_line(x, y, b, i)
if Stock.plotIndicatorRegression is True:
plot_regression_line(x, y, b, i)
return regressionList
@ -1588,20 +1594,42 @@ def checkConfig(fileName):
return r
def continueProgram():
found = False
print('Would you like to rerun the program?')
return Functions.trueOrFalse()
def plotIndicatorRegression():
if Functions.detectDisplay() is True:
if Functions.checkPackage('matplotlib') is False:
print(
'matplotlib is not installed. \nIf you would like to install' +
' it (and have a display), run `pip install matplotlib`')
return False
else:
print('\nWould you like to plot indicator linear regression '
'results?')
plotLinear = Functions.trueOrFalse()
if plotLinear is True:
return True
else:
return False
def main():
'''
Check config file for errors and if not, then use values
#! Only use this if you know it is exactly correct. I haven't spent much time debugging this
#! Only use this if you know it is exactly correct. I haven't spent much
#! time debugging this
'''
Stock.config = checkConfig('config.json')
# Check if matplotlib is installed
if Functions.checkPackage('matplotlib') is False:
print(
'matplotlib is not installed. This is required for plotting linear regression')
runningProgram = True
while runningProgram is True:
# Check that all required packages are installed
if Stock.config == 'N/A':
# Check that all required packages are installed
packagesInstalled = Functions.checkPackages(
['numpy', 'requests', 'bs4', 'requests_cache', 'halo'])
if not packagesInstalled:
@ -1632,7 +1660,7 @@ def main():
# Determine time frame (Years)
timeFrame = timeFrameInit()
Stock.timeFrame = timeFrame # Needs to be a global variable for all stocks
Stock.timeFrame = timeFrame
# Choose indicator
Stock.indicator = indicatorInit()
@ -1642,6 +1670,11 @@ def main():
# Choose whether to remove outliers or not
Stock.removeOutliers = outlierChoice()
# Check if matplotlib is installed and if so, ask user if
# they want to plot
Stock.plotIndicatorRegression = plotIndicatorRegression()
else:
if Stock.config['Check Packages'] is not False:
packagesInstalled = Functions.checkPackages(
@ -1710,7 +1743,11 @@ def main():
# Choose indicator and calculate correlation with indicator
indicatorMain(listOfStocks)
# Decide if running program again
print('')
runningProgram = continueProgram()
print('')
exit()