Added data and first two projects

Renamed the projects so they're easier to distinguish. Will add further projects
as we finalize them.

Author: bhrolenok

assess_portfolio_mc1p1/analysis.py

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+"""MC1-P1: Analyze a portfolio."""
+
+import pandas as pd
+import matplotlib.pyplot as plt
+import numpy as np
+import datetime as dt
+from util import get_data, plot_data
+
+# This is the function that will be tested by the autograder
+# The student must update this code to properly implement the functionality
+def assess_portfolio(sd = dt.datetime(2008,1,1), ed = dt.datetime(2009,1,1), \
+    syms = ['GOOG','AAPL','GLD','XOM'], \
+    allocs=[0.1,0.2,0.3,0.4], \
+    sv=1000000, rfr=0.0, sf=252.0, \
+    gen_plot=False):
+
+    # Read in adjusted closing prices for given symbols, date range
+    dates = pd.date_range(sd, ed)
+    prices_all = get_data(syms, dates)  # automatically adds SPY
+    prices = prices_all[syms]  # only portfolio symbols
+    prices_SPY = prices_all['SPY']  # only SPY, for comparison later
+
+    # Get daily portfolio value
+    port_val = prices_SPY # add code here to compute daily portfolio values
+
+    # Get portfolio statistics (note: std_daily_ret = volatility)
+    cr, adr, sddr, sr = [0.25, 0.001, 0.0005, 2.1] # add code here to compute stats
+
+    # Compare daily portfolio value with SPY using a normalized plot
+    if gen_plot:
+        # add code to plot here
+        df_temp = pd.concat([port_val, prices_SPY], keys=['Portfolio', 'SPY'], axis=1)
+        pass
+
+    # Add code here to properly compute end value
+    ev = sv
+
+    return cr, adr, sddr, sr, ev
+
+def test_code():
+    # This code WILL NOT be tested by the auto grader
+    # It is only here to help you set up and test your code
+
+    # Define input parameters
+    # Note that ALL of these values will be set to different values by
+    # the autograder!
+    start_date = dt.datetime(2009,1,1)
+    end_date = dt.datetime(2010,1,1)
+    symbols = ['GOOG', 'AAPL', 'GLD', 'XOM']
+    allocations = [0.2, 0.3, 0.4, 0.1]
+    start_val = 1000000  
+    risk_free_rate = 0.0
+    sample_freq = 252
+
+    # Assess the portfolio
+    cr, adr, sddr, sr, ev = assess_portfolio(sd = start_date, ed = end_date,\
+        syms = symbols, \
+        allocs = allocations,\
+        sv = start_val, \
+        gen_plot = False)
+
+    # Print statistics
+    print "Start Date:", start_date
+    print "End Date:", end_date
+    print "Symbols:", symbols
+    print "Allocations:", allocations
+    print "Sharpe Ratio:", sr
+    print "Volatility (stdev of daily returns):", sddr
+    print "Average Daily Return:", adr
+    print "Cumulative Return:", cr
+
+if __name__ == "__main__":
+    test_code()

assess_portfolio_mc1p1/feedback/.gitignore

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+# Ignore everything in this directory
+*
+# Except this file
+!.gitignore

assess_portfolio_mc1p1/util.py

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+"""MLT: Utility code."""
+
+import os
+import pandas as pd
+import matplotlib.pyplot as plt
+
+def symbol_to_path(symbol, base_dir=os.path.join("..", "data")):
+    """Return CSV file path given ticker symbol."""
+    return os.path.join(base_dir, "{}.csv".format(str(symbol)))
+
+def get_data(symbols, dates, addSPY=True, colname = 'Adj Close'):
+    """Read stock data (adjusted close) for given symbols from CSV files."""
+    df = pd.DataFrame(index=dates)
+    if addSPY and 'SPY' not in symbols:  # add SPY for reference, if absent
+        symbols = ['SPY'] + symbols
+
+    for symbol in symbols:
+        df_temp = pd.read_csv(symbol_to_path(symbol), index_col='Date',
+                parse_dates=True, usecols=['Date', colname], na_values=['nan'])
+        df_temp = df_temp.rename(columns={colname: symbol})
+        df = df.join(df_temp)
+        if symbol == 'SPY':  # drop dates SPY did not trade
+            df = df.dropna(subset=["SPY"])
+
+    return df
+
+def plot_data(df, title="Stock prices", xlabel="Date", ylabel="Price"):
+    """Plot stock prices with a custom title and meaningful axis labels."""
+    ax = df.plot(title=title, fontsize=12)
+    ax.set_xlabel(xlabel)
+    ax.set_ylabel(ylabel)
+    plt.show()