Class03 Answer:

Show a plot of the fitted line on top of the 2016 prices

I use NumPy, Pandas below.


This script should plot a fitted line on top of the 2016 prices

import pandas as pd
import numpy  as np
import matplotlib.pyplot as plt

csvfile   = ''
cp_df     = pd.read_csv(csvfile).sort_values(['cdate'])
cp2016_sr = (cp_df.cdate > '2016') & (cp_df.cdate < '2017')
cp2016_df = cp_df[['cdate','cp']][cp2016_sr]

def colvec(arylst):
    # This should help me create column vectors from arrays or lists:
    return np.array(arylst).reshape((len(arylst),1))

x_a      = colvec(range(len(cp2016_df)))
ones_l   = [1]*len(cp2016_df)
ones_a   = colvec(ones_l)
xvals_a  = np.hstack((ones_a,x_a))
yvals_a  = colvec(cp2016_df.cp)
middle_a = np.linalg.pinv(np.matmul(xvals_a.T,xvals_a))
rhs_a    = np.matmul(xvals_a.T,yvals_a)
beta_a   = np.matmul(middle_a,rhs_a)
x_in_a   = xvals_a
yhat_a   = np.matmul(x_in_a,beta_a)
cp2016_df['yhat'] = yhat_a

# To make a better plot I should convert X-values from integers to series of strings:
cpdate2016_df = cp2016_df.set_index(['cdate'])
# I should plot cp (closing price), and fitted line:
cpdate2016_df.plot.line(title="GSPC 2016")


I ran the above script and saw this:

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