import numpy as np

import os

import pandas as pd

import pandas.io.data

from pandas import Series, DataFrame

from pandas import ExcelWriter

from pandas import read_csv

import matplotlib.pyplot as plt

import datetime

from scipy.stats import ttest_1samp

import matplotlib.pyplot as plt

from random import randint

import math

test = 10

results = []

while test > 0:

### Establish Time and Get Stock Returns

now = datetime.datetime.now()

list = ['IVE', 'IVW', 'SPY']

start = datetime.datetime(randint(2000,2015),randint(1,12),randint(1,28))

print(start)

end = datetime.datetime(now.year,now.month,now.day)

df = pd.io.data.get_data_yahoo(list, start, end)['Adj Close']

df = DataFrame(df)

df['IVEReturn'] = df['IVE'].pct_change()

df['IVWReturn'] = df['IVW'].pct_change()

df['SP500Return'] = df['SPY'].pct_change()

df['Date'] = df.index

df['Date'] = [time.date() for time in df['Date']]

l = df.index.values

for i in range(0,len(l)):

df.loc[l[i], 'Year'] = datetime.datetime.strptime(str(df.loc[l[i], 'Date']), '%Y-%m-%d').strftime('%Y')

### Create Investment Test

### Set DataFrame Variables

df['InvestmentTotal'] = ''

df['Growth'] = ''

df['Value'] = ''

df['InvestmentTotal'][0] = 100000

df['Growth'] = df['InvestmentTotal'][0]/2

df['Value'] = df['InvestmentTotal'][0]/2

df['SP500Total'] = ''

df['SP500Total'][0] = 100000

### Rebalance Decision Rule Loop

for i in range(1,len(l)):

if df.loc[l[i], 'Year'] != df.loc[l[i-1], 'Year']:

df.loc[l[i-1], 'Rebalance'] = 'Yes'

else:

df.loc[l[i-1], 'Rebalance'] = 'No'

### Investment Returns Loop

for i in range(1, len(l)):

df.loc[l[i], 'Growth'] = df.loc[l[i-1], 'Growth'] * (1 + df.loc[l[i], 'IVWReturn'])

df.loc[l[i], 'Value'] = df.loc[l[i-1], 'Value'] * (1 + df.loc[l[i], 'IVEReturn'])

df.loc[l[i], 'InvestmentTotal'] = df.loc[l[i], 'Value'] + df.loc[l[i], 'Growth']

df.loc[l[i], 'SP500Total'] = df.loc[l[i-1], 'SP500Total'] * (1 + df.loc[l[i], 'SP500Return'])

### Growth vs Value allocation

df.loc[l[i], 'Growth%'] = df.loc[l[i],'Growth']/df.loc[l[i],'InvestmentTotal']

df.loc[l[i], 'Value%'] = df.loc[l[i],'Value']/df.loc[l[i], 'InvestmentTotal']

df.loc[l[i], 'Total%'] = df.loc[l[i], 'Growth%'] + df.loc[l[i], 'Value%']

### Execute Rebalance

if df.loc[l[i-1], 'Rebalance'] == 'Yes':

if df.loc[l[i-1], 'Growth%'] > .5:

trade_value = .5 * (df.loc[l[i-1], 'Growth'] - df.loc[l[i-1], 'Value'])

df.loc[l[i], 'Value'] = (df.loc[l[i-1], 'Value'] + trade_value) * (1 + df.loc[l[i], 'IVEReturn'])

df.loc[l[i], 'Growth'] = (df.loc[l[i-1], 'Growth'] - trade_value) * (1 + df.loc[l[i], 'IVWReturn'])

df.loc[l[i], 'InvestmentTotal'] = df.loc[l[i], 'Value'] + df.loc[l[i], 'Growth']

df.loc[l[i], 'Growth%'] = df.loc[l[i],'Growth']/df.loc[l[i],'InvestmentTotal']

df.loc[l[i], 'Value%'] = df.loc[l[i],'Value']/df.loc[l[i], 'InvestmentTotal']

df.loc[l[i], 'Total%'] = df.loc[l[i], 'Growth%'] + df.loc[l[i], 'Value%']

else:

trade_value = .5 * (df.loc[l[i-1], 'Value'] - df.loc[l[i-1], 'Growth'])

df.loc[l[i], 'Growth'] = (df.loc[l[i-1], 'Growth'] + trade_value) * (1 + df.loc[l[i], 'IVWReturn'])

df.loc[l[i], 'Value'] = (df.loc[l[i-1], 'Value'] - trade_value) * (1 + df.loc[l[i], 'IVEReturn'])

df.loc[l[i], 'InvestmentTotal'] = df.loc[l[i], 'Value'] + df.loc[l[i], 'Growth']

df.loc[l[i], 'Growth%'] = df.loc[l[i],'Growth']/df.loc[l[i],'InvestmentTotal']

df.loc[l[i], 'Value%'] = df.loc[l[i],'Value']/df.loc[l[i], 'InvestmentTotal']

df.loc[l[i], 'Total%'] = df.loc[l[i], 'Growth%'] + df.loc[l[i], 'Value%']

final_value = df.loc[l[len(l)-1], 'InvestmentTotal'] - df.loc[l[len(l)-1],'SP500Total']

if math.isnan(final_value) == True:

print("result removed it was nan")

test = test + 1

else:

results.append(final_value)

print(results)

test = test - 1

dg = pd.Series(results, name = 'Results')

dff = DataFrame(dg)

print(dff)

dff.hist()

plt.show()

file = ExcelWriter('ValueGrowth.xlsx')

df.to_excel(file, 'Data')

file.close()

os.startfile('ValueGrowth.xlsx')

df.plot(y = ['SP500Total', 'InvestmentTotal'])

plt.show()