#!/usr/bin/env python
# coding: utf-8

# In[1]:


import pandas as pd
import numpy as np
import tradingWithPython as twp
import tradingWithPython.lib.yahooFinance as yf # yahoo finance module
twp.extra.setNotebookStyle()
import ffn


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data = twp.yahooFinance.getHistoricData('SPY')


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data.head()


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close=data['close']
close.plot()


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data['SMAslow']=data['close'].rolling(window=252).mean()
data['SMAfast']=close.rolling(window=42).mean()


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data.tail()


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data[['close','SMAfast','SMAslow']].plot()


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data['signal'] = data['SMAfast'] - data['SMAslow']


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data.tail()


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X = 0 
data['Stance'] = np.where(data['signal'] > X, 1, 0) 
data['Stance'] = np.where(data['signal'] < X, -1, data['Stance'])
data['Stance'].value_counts()


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data.tail()


# 

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data['Stance'].plot()


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data['Market Returns'] = np.log(data['close'] / data['close'].shift(1))
data['Strateg']=data['Market Returns']*data['Stance'].shift(1)


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data


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data[['Market Returns','Strateg']].cumsum().plot()


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data['equity']=data['Strateg'].cumsum()+100


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data


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writer = pd.ExcelWriter('output.xlsx')
data.to_excel(writer,'Sheet1')
writer.save()


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perf = data['equity'].calc_stats()


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ffn.core.PerformanceStats


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perf.plot()


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perf.display()


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