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#!/usr/bin/env python
# Graph a bunch of financial assets (stocks or mutual funds)
# specified on the commandline by ticker symbols.
# (Downloads data from Yahoo finance.)
# Usage: fund fund ...
# You can also specify modules that do custom loading,
# in case you need to parse CSV or Excel files or any other local files.
# Just add those on the commandline, e.g. fincompare IRCAX SCALX
# The name of the module must end in .py, e.g.
# It may include a full path to the file, e.g. ~/mydata/
# Your module must provide a function with this signature:
# plot_fund(color='b', marker='o')
# (of course you can choose your own defaults for color and marker).
# The function should return a triplet initial, start, end
# where initial is the initial value of the investment in dollars,
# and start and end are datetimes.
# You can't currently specify the date range unless you use a custom module.
# Copyright 2013 by Akkana Peck.
# Share and enjoy under the terms of the GPL v2 or later.
import sys, os
import datetime
import math
import numpy
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
# from import quotes_historical_yahoo_ohlc as yahoo
from mpl_finance import quotes_historical_yahoo_ohlc as yahoo
start = None
initial = None
# Read the list of funds to plot.
# If any of these ends in .py, assume it's a custom module;
# we'll try to load the module, which should include this function:
# plot_fund(color='b', marker='o')
imported_modules = {}
if len(sys.argv) < 2:
print("Usage: %s [-iinitialval] [-sstarttime] fund [fund fund ...]" % sys.argv[0])
print("No spaces between -i or -s and their values!")
print("e.g. fincompare -i200000 -s2008-1-1 FMAGX FIRPX")
funds = []
for f in sys.argv[1:]:
if f.endswith('.py'):
# First split off any pathname included,
# since python isn't smart about importing from a pathname.
fpath, ffile = os.path.split(f)
if fpath:
imported_modules[f] = __import__(ffile[:-3])
except Exception as e:
print("Couldn't import", f)
elif f.startswith('-s'):
# Parse the start time:
start = datetime.datetime.strptime(f[2:], '%Y-%m-%d')
elif f.startswith('-i'):
print("Minus i!")
print("Trying initial from '%s'" % f[2:])
initial = int(f[2:])
# Set up the plots:
fig = plt.figure(figsize=(12, 8)) # width, height in inches
ax1 = plt.subplot(111)
# Pick a different color and style for each plot.
# Sure would be nice if matplotlib could handle stuff like this for us.
# The impossible-to-find documentation for line styles is at:
# For colors, to use anything beyond the standard list, see
colors = [ 'b', 'r', 'g', 'c', 'y', 'k' ]
styles = [ '-', '--', ':', '-.' ]
markers = [ 'o', '*', 's', '^', 'p', '+', 'D', 'x', '|', 'h' ]
def pick_color(i):
'''Pick a color that tries to be reasonably different
from other colors so far picked.
return colors[i % len(colors)] \
+ styles[int(i / len(colors))]
# + markers[i%len(markers)]
def plot_funds(tickerlist, initial, start, end):
'''Plot a fund by its ticker symbol,
normalized to a given initial value.
numdays = (end - start).days
daysinyear = 365.0
print('%9s %9s %9s %9s' % ('Ticker', 'daily', 'CC', 'abs'))
# For testing, use something like
# FUSVX = yahoo('FUSVX', datetime.datetime(2012, 10, 1),
# datetime.datetime(2013, 4, 1),
# asobject=True)
for i, ticker in enumerate(tickerlist):
# This gives a runtime warning for SCAL, and all the aclose vals
# come out zero. Catching a RuntimeWarning isn't as simple as try;
fund_data = yahoo(ticker, start, end, asobject=True)
print("Couldn't get data for", ticker)
# Guard against failures of quotes_historical_yahoo;
# without this check you'll see more uncatchable RuntimeWarnings.
if fund_data['aclose'][0] == 0:
print(ticker, ": First adjusted close is 0!")
# Calculate effective daily-compounded interest rate
fixed_pct = fund_data['aclose'][-1]/fund_data['aclose'][0] - 1.
Rcc = daysinyear / numdays * \
numpy.log(fund_data['aclose'][-1] / fund_data['aclose'][0])
# Convert CC return to daily-compounded return:
Rdaily = daysinyear * (math.exp(Rcc / daysinyear) - 1.)
# Another attempt to compute the daily rate, but it's wrong.
# Reff = daysinyear * (math.exp(math.log(fund_data['aclose'][-1]
# - fund_data['aclose'][0])
# /numdays) - 1)
print("%9s %9.2f %9.2f %9.2f" % (ticker,
Rdaily*100, Rcc*100, fixed_pct*100))
# Normalize to the initial investment:
fund_data['aclose'] *= initial / fund_data['aclose'][0]
# and plot
ax1.plot_date(x=fund_data['date'], y=fund_data['aclose'],
fmt=pick_color(i), label=ticker)
for i, f in enumerate(imported_modules.keys()):
# XXX This will overwrite any -i and -s.
# Should instead normalize the value read to the -i value passed in.
initial, start, end = imported_modules[f].plot_fund(color='k',
except Exception as e:
print("Couldn't plot", f)
if not initial:
initial = 100000
if not start:
start = datetime.datetime(2011, 1, 1)
end =
# Baseline at the initial investment:
plt.axhline(y=initial, color='k')
# This used to happen automatically, but then matplotlib started
# starting at 2000 rather than following the data. So better be sure:
ax1.set_xlim(start, end)
plot_funds(funds, initial, start, end)
plt.legend(loc='upper left')
# Rotate the X date labels. I wonder if there's any way to do this
# only for some subplots? Not that I'd really want to.
# In typical matplotlib style, it's a completely different syntax
# depending on whether you have one or multiple plots.
# There is apparently no way to do this through the subplot.
# ax1.set_xticklabels(rotation=20)
# fig = plt.figure(1)
ax1.set_title("Investment options")
# This is intended for grouping muultiple plots, but it's also the only
# way I've found to get rid of all the extra blank space around the outsides
# of the plot and devote more space to the content itself.