Here is a simple example to compute Cointegration between two stock pairs using python libraries like NSEpy, Pandas, statmodels, matplotlib
Cointegration is used in Statistical Arbitrage to find best Pair of Stocks (Pair Trading) to go long in one stock and short(Competitive peers) another to generate returns. Statistical Arbitrage(StatArb) is all about mean reversion, looking for deviation in the spreads and expecting mean reversion from the spread.
NSEpy – fetches historical data from nseindia.com
Pandas – Python library to handle time series data
Statmodels – Python library to handle statistical operations like cointegration
Matplotlib – Python library to handle 2D chart plotting
We will be using get_history NSEpy function to fetch the index data from nseindia. However to fetch stock data you need to use get_price_history. Exploring the NSEpy library would give you a broader idea about how to replicate the same for stocks. But the problem with NSEIndia data is that stock data is not adjusted to split/bonus. Will handle that in a different post about how to process the data for split/bonus before analyzing the time series data.
Sample IPython Notebook to compute Cointegration below :
References
Quantopian Lecture on Pair Trading
Python Library to get publicly available data on NSE website – NSEpy
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Great post Rajandran
Is there any specific version of python that would you recommend. Else may i know the python version that you are trying this on.
Regards,
Surya
We are using Python 2.7
hello Rajandran
i want your support will u please give your email.id or phone no
do send a mail to rajandran@marketcalls.in
Happy to see my work in action, Thanks for using the library!!
Do let me know if any feedbacks!!
Please do try https://github.com/swapniljariwala/zerodha as well and let me know feedback
I am using nsepy but it is not working to fetch indices data to manipulate for our reqirement.
what i have to do.
What error you are facing?
now due to chane in indices symbol free downloaders(eod nse) can not download indices. data
how to download or extract some main indices data from indices snapshot csv data file quickly.
i need nifty, ,banknifty, nse it, nifty junior, midcap50, nse 100 etc
I’ve updated the API, The updated API will solve your problem
https://github.com/swapniljariwala/nsepy
Simple few lines of code and you are done
from nsepy import get_history, get_index_pe_history
from datetime import date
#Index price history
nifty = get_history(symbol=”NIFTY”,
start=date(2015,1,1),
end=date(2015,1,10),
index=True)
nifty[[‘Close’, ‘Turnover’]].plot(secondary_y=’Turnover’)
Hello all,
Please check out the latest version of NSEpy, I’ve added the support for
Derivative data. (Probably only API for indian derivative and India VIX data as Yahoo API has no support for derivatives), Index data
Unified and simplified API for all (Equity, Index, Derivative, Volatility Indexes-INDIAVIX)
Compatible and Tested with Python 2.7 and 3.4
Examples on git-hub page-
https://github.com/swapniljariwala/nsepy
Please report any bugs or issues on --
https://github.com/swapniljariwala/nsepy/issues
Sir, I beginner in Algo Trading trying to use my quant knowlegde. I am using NSEpy though getting error like “ValueError: negative dimensions are not allowed” and “AttributeError: ‘ThreadReturns’ object has no attribute ‘result’. Could you please help me. I would thankful to you. My code is mentioned below:
#importing modules
import pandas as pd
import numpy as np
import statsmodels
from statsmodels.tsa.stattools import coint
import matplotlib.pyplot as plt
import datetime as date
import nsepy
from nsepy.archives import get_price_history
import seaborn
#Defining Cointegrated pairs formula
def find_cointegrated_pairs(stockdata):
n = len(stockdata.minor_axis)
score_matrix = np.zeros((n, n))
pvalue_matrix = np.ones((n, n))
keys = stockdata.keys
pairs = []
for i in range(n):
for j in range(i+1, n):
S1 = stockdata.minor_xs(stockdata.minor_axis[i])
S2 = stockdata.minor_xs(stockdata.minor_axis[j])
result = coint(S1, S2)
score = result[0]
pvalue = result[1]
score_matrix[i, j] = score
pvalue_matrix[i, j] = pvalue
if pvalue = 0.99))
print (pairs)
I am getting same error, did you find the solution ?
if pvalue < 0.05:
pairs.append((stockdata.minor_axis[i], stockdata.minor_axis[j]))
return score_matrix, pvalue_matrix, pairs
#time period of testing
histdata = {}
startdate = date.datetime(2016,5,20)
enddate = date.datetime.today()
#Dowloading NSE Symbols
url = "https://www.nseindia.com/content/indices/ind_nifty50list.csv"
csvfromurl = req.get(url).content
csvfordf = pd.read_csv(strio.StringIO(csvfromurl.decode('utf-8')))
nifty50df = pd.DataFrame(csvfordf)
#fetching data
for eachscrip in nifty50df[‘Symbol’]:
try:
stockdata = get_price_history(stock = eachscrip, start = startdate, end = enddate)
except (ValueError,IOError) as err:
print(err)
#Arranging pairs combination
stockdata.minor_axis = map(lambda x: x.Symbol, stockdata.minor_axis)
Getting above two errors when fetching data
Is there anyone who is still using NSEpy ?
I m newbie with python but willing to learn.
Hi
How do i get live data using nsepy?
Hey hi. Can you help with adjusting historical prices with splits and bonuses
how to get live data using nsepy