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Parabolic SAR backtest.py
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Parabolic SAR backtest.py
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# coding: utf-8
# In[1]:
#parabolic stop and reverse is very useful for trend following
#sar is an indicator below the price when its an uptrend
#and above the price when its a downtrend
#it is very painful to calculate sar, though
#and many explanations online including wiki cannot clearly explain the process
#hence, the good idea would be to read info on wikipedia
#and download an excel spreadsheet made by joeu2004
#formulas are always more straight forward than descriptions
#links are shown below
# https://en.wikipedia.org/wiki/Parabolic_SAR
# https://www.box.com/s/gbtrjuoktgyag56j6lv0
import matplotlib.pyplot as plt
import numpy as np
import fix_yahoo_finance as yf
import pandas as pd
# In[2]:
#the calculation of sar
#as rules are very complicated
#plz check the links above to understand more about it
def parabolic_sar(new):
#this is common accelerating factors for forex and commodity
#for equity, af for each step could be set to 0.01
initial_af=0.02
step_af=0.02
end_af=0.2
new['trend']=0
new['sar']=0.0
new['real sar']=0.0
new['ep']=0.0
new['af']=0.0
#initial values for recursive calculation
new['trend'][1]=1 if new['Close'][1]>new['Close'][0] else -1
new['sar'][1]=new['High'][0] if new['trend'][1]>0 else new['Low'][0]
new.at[1,'real sar']=new['sar'][1]
new['ep'][1]=new['High'][1] if new['trend'][1]>0 else new['Low'][1]
new['af'][1]=initial_af
#calculation
for i in range(2,len(new)):
temp=new['sar'][i-1]+new['af'][i-1]*(new['ep'][i-1]-new['sar'][i-1])
if new['trend'][i-1]<0:
new.at[i,'sar']=max(temp,new['High'][i-1],new['High'][i-2])
temp=1 if new['sar'][i]<new['High'][i] else new['trend'][i-1]-1
else:
new.at[i,'sar']=min(temp,new['Low'][i-1],new['Low'][i-2])
temp=-1 if new['sar'][i]>new['Low'][i] else new['trend'][i-1]+1
new.at[i,'trend']=temp
if new['trend'][i]<0:
temp=min(new['Low'][i],new['ep'][i-1]) if new['trend'][i]!=-1 else new['Low'][i]
else:
temp=max(new['High'][i],new['ep'][i-1]) if new['trend'][i]!=1 else new['High'][i]
new.at[i,'ep']=temp
if np.abs(new['trend'][i])==1:
temp=new['ep'][i-1]
new.at[i,'af']=initial_af
else:
temp=new['sar'][i]
if new['ep'][i]==new['ep'][i-1]:
new.at[i,'af']=new['af'][i-1]
else:
new.at[i,'af']=min(end_af,new['af'][i-1]+step_af)
new.at[i,'real sar']=temp
return new
# In[3]:
#generating signals
#idea is the same as macd oscillator
#check the website below to learn more
# https://github.com/je-suis-tm/quant-trading/blob/master/MACD%20oscillator%20backtest.py
def signal_generation(df,method):
new=method(df)
new['positions'],new['signals']=0,0
new['positions']=np.where(new['real sar']<new['Close'],1,0)
new['signals']=new['positions'].diff()
return new
# In[4]:
#plotting of sar and trading positions
#still similar to macd
def plot(new,ticker):
fig=plt.figure()
ax=fig.add_subplot(111)
new['Close'].plot(lw=3,label='%s'%ticker)
new['real sar'].plot(linestyle=':',label='Parabolic SAR',color='k')
ax.plot(new.loc[new['signals']==1].index,new['Close'][new['signals']==1],marker='^',color='g',label='LONG',lw=0,markersize=10)
ax.plot(new.loc[new['signals']==-1].index,new['Close'][new['signals']==-1],marker='v',color='r',label='SHORT',lw=0,markersize=10)
plt.legend()
plt.grid(True)
plt.title('Parabolic SAR')
plt.ylabel('price')
plt.show()
# In[5]:
def main():
#download data via fix yahoo finance library
stdate=('2016-01-01')
eddate=('2018-01-01')
ticker=('EA')
#slice is used for plotting
#a two year dataset with 500 variables would be too much for a figure
slicer=450
df=yf.download(ticker,start=stdate,end=eddate)
#delete adj close and volume
#as we dont need them
del df['Adj Close']
del df['Volume']
#no need to iterate over timestamp index
df.reset_index(inplace=True)
new=signal_generation(df,parabolic_sar)
#convert back to time series for plotting
#so that we get a date x axis
new.set_index(new['date'],inplace=True)
#shorten our plotting horizon and plot
new=new[slicer:]
plot(new,ticker)
#how to calculate stats could be found from my other code called Heikin-Ashi
# https://github.com/je-suis-tm/quant-trading/blob/master/heikin%20ashi%20backtest.py
# In[6]:
if __name__ == '__main__':
main()