NSEpy DocumentationRelease 1.0

Swapnil Jariwala

Mar 10, 2018

Contents

1 Quick Start 31.1 Installation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.2 Quick Hand-On . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

2 Fetching Price History 52.1 Stock price history . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52.2 Stock futures price history . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62.3 Stock options price history . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72.4 Index price history . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72.5 Index futures price history . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72.6 Index options price history . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82.7 India VIX price history . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82.8 Missing or zero values in derivative data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

3 Fetching Expiry Dates 9

4 Index P/E Ratio History 11

5 RBI Reference Rates 13

6 Daily Bhav Copy 15

7 Command Line Interface 17

8 Indices and tables 19

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NSEpy Documentation, Release 1.0

NSEpy is a library to extract historical and realtime data from NSE’s website. This Library aims to keep the API verysimple.

Python is a great tool for data analysis along with the scipy stack and the main objective of NSEpy is to provideanalysis ready data-series for use with scipy stack. NSEpy can seamlessly integrate with Technical Analysis library(Acronymed TA-Lib, includes 200 indicators like MACD, RSI). This library would serve as a basic building block forautomatic/semi-automatic algorithm trading systems or backtesting systems for Indian markets.

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2 Contents

CHAPTER 1

Quick Start

1.1 Installation

$ pip install nsepy

1.2 Quick Hand-On

Here’s a simple example to get historical stock data for the month of January 2015.

>>> from nsepy import get_history>>> from datetime import date>>> data = get_history(symbol="SBIN", start=date(2015,1,1), end=date(2015,1,31))>>> data[['Close']].plot()

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CHAPTER 2

Fetching Price History

Function get_history fetches the price history of stocks/indices/derivatives and returns a pandas dataframe.

2.1 Stock price history

from datetime import datefrom nsepy import get_historysbin = get_history(symbol='SBIN',

start=date(2015,1,1),end=date(2015,1,10))

Executed on ipython console:

In [1]: sbinOut[1]: Symbol Series Prev Close Open High Low Last Close \Date2015-01-01 SBIN EQ 311.85 312.45 315.00 310.70 314.0 314.002015-01-02 SBIN EQ 314.00 314.35 318.30 314.35 315.6 315.252015-01-05 SBIN EQ 315.25 316.25 316.80 312.10 312.8 312.752015-01-06 SBIN EQ 312.75 310.00 311.10 298.70 299.9 299.902015-01-07 SBIN EQ 299.90 300.00 302.55 295.15 301.4 300.15

VWAP Volume Turnover Trades Deliverable Volume \Date2015-01-01 313.67 6138488 1.925489e+14 58688 18776772015-01-02 316.80 9935094 3.147389e+14 79553 42216852015-01-05 313.84 9136716 2.867432e+14 88236 38451732015-01-06 305.14 15329257 4.677601e+14 169268 74248472015-01-07 299.95 15046745 4.513243e+14 147185 5631400

%DeliverbleDate2015-01-01 0.3059

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2015-01-02 0.42492015-01-05 0.42082015-01-06 0.48442015-01-07 0.3743

2.2 Stock futures price history

Set futures=True and provide expiry_date of the contract (Refer Fetching Expiry Dates)

from datetime import datefrom nsepy import get_history# Stock options (Similarly for index options, set index = True)stock_fut = get_history(symbol="SBIN",

start=date(2015,1,1),end=date(2015,1,10),futures=True,expiry_date=date(2015,1,29))

Please refer to Note on Missing or zero values in derivative data.

When executed the above code on ipython console:

In [38]: stock_optOut[38]:

Symbol Expiry Open High Low Close Last \Date2015-01-01 SBIN 2015-01-29 315.10 317.95 313.40 316.65 317.002015-01-02 SBIN 2015-01-29 317.50 320.95 317.10 317.75 318.302015-01-05 SBIN 2015-01-29 318.00 318.75 314.10 315.00 315.052015-01-06 SBIN 2015-01-29 312.95 312.95 300.10 301.30 301.102015-01-07 SBIN 2015-01-29 301.95 304.55 297.35 302.25 303.502015-01-08 SBIN 2015-01-29 306.50 308.40 303.70 306.65 307.002015-01-09 SBIN 2015-01-29 306.75 309.25 301.05 304.75 304.15

Settle Price Number of Contracts Turnover Open Interest \Date2015-01-01 316.65 14720 5.821172e+09 554800002015-01-02 317.75 22525 8.988242e+09 550875002015-01-05 315.00 17455 6.898723e+09 557187502015-01-06 301.30 29338 1.126715e+10 567012502015-01-07 302.25 28489 1.074823e+10 580362502015-01-08 306.65 20120 7.702653e+09 572875002015-01-09 304.75 18961 7.247211e+09 57035000

Change in OI UnderlyingDate2015-01-01 358750 314.002015-01-02 -392500 315.252015-01-05 631250 312.752015-01-06 982500 299.902015-01-07 1335000 300.152015-01-08 -748750 304.852015-01-09 -252500 303.20

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2.3 Stock options price history

For stock options, specify-

• option_type as “CE” for call and as “PE” for put option

• strike_price - the strike price of the contract

• expiry_date - expiry date of the contract, refer:ref:get_expiry_date.

# Stock options (Similarly for index options, set index = True)stock_opt = get_history(symbol="SBIN",

start=date(2015,1,1),end=date(2015,1,10),option_type="CE",strike_price=300,expiry_date=date(2015,1,29))

2.4 Index price history

There are currently 50+ indices maintained by NSE. You can get historical data for all of them.:: Usage-

• symbol - Name of the index in capital (Refer this page for list of indices)

• index - Set this True for all index related operations

# NIFTY Next 50 indexnifty_next50 = get_history(symbol="NIFTY NEXT 50",

start=date(2015,1,1),end=date(2015,1,10),index=True)

# NIFTY50 Equal wight index (random index from the list)nifty_eq_wt = get_history(symbol="NIFTY50 EQUAL WEIGHT",

start=date(2017,6,1),end=date(2017,6,10),index=True)

You will observe a lot of NaN values for many indeces like ‘NIFTY50 Equal wight index’, In those cases just use‘Close’ values

2.5 Index futures price history

Out of the 60+ indices, only 7 indeces are available for derivative. (List available here.) Usage-

• index - Set True

• futures - Set True

• expiry_date - Expiry date of the contract. refer:ref:get_expiry_date.

nifty_fut = get_history(symbol="NIFTY",start=date(2015,1,1),end=date(2015,1,10),index=True,futures=True,expiry_date=date(2015,1,29))

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2.6 Index options price history

Usage-

• index - Set True

• option_type as “CE” for call and as “PE” for put option

• strike_price - the strike price of the contract

• expiry_date - expiry date of the contract, refer:ref:get_expiry_date.

nifty_opt = get_history(symbol="NIFTY",start=date(2015,1,1),end=date(2015,1,10),index=True,option_type='CE',strike_price=8200,expiry_date=date(2015,1,29))

2.7 India VIX price history

India VIX is a volatility index which gives a measurement of market volatility based on NIFTY options contract. Thisservers as important parameter in option pricing.

vix = get_history(symbol="INDIAVIX",start=date(2015,1,1),end=date(2015,1,10),index=True)

2.8 Missing or zero values in derivative data

Although NSE specifies a trading cycle of three months, most stock futures will not be traded for wholethree months, rather they will be active only in the month of expiry, So you may get 0 values for dayswhen no contracts were traded. Please deal with this situation carefully in your logic.

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CHAPTER 3

Fetching Expiry Dates

Fetch expiry date of all derivative contracts for a perticular month and year. Usage-

• month - Month of contract expiry starting from 1 for January and 12 for December

• year - Year of the contract expiry

from nsepy.derivatives import get_expiry_dateexpiry = get_expiry_date(year=2015, month=1)

Use this function with get_history:

stock_opt = get_history(symbol="SBIN",start=date(2015,1,1),end=date(2015,1,10),futures=True,expiry_date=get_expiry_date(2015,1))

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CHAPTER 4

Index P/E Ratio History

P/E ratio of a security helps to estimate if the security is over-priced or under-priced. NSE offers historical P/E ratiofor 30+ thematic and sectoral indices, we can use this data to determine which sectors are over-priced or under-pricedand further make investment decisions.

# Index P/E ratio historyfrom nsepy import get_index_pe_historynifty_pe = get_index_pe_history(symbol="NIFTY",

start=date(2015,1,1),end=date(2015,1,10))

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CHAPTER 5

RBI Reference Rates

USD, GBP, EURO, YEN to INR rbi reference rates:

from nsepy import get_rbi_ref_historyrbi_ref = get_rbi_ref_history(date(2015,1,1), date(2015,1,10))

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CHAPTER 6

Daily Bhav Copy

Download daily bhav copy, which is nothing but OHLC prices of all the traded stocks on a particular day:

from nsepy.history import get_price_listprices = get_price_list(dt=date(2015,1,1))

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CHAPTER 7

Command Line Interface

NSEpy offers a simple to use, easy to remember command line interface, This method is useful when you just wantthe data for further processed in Excel, R or any other tool which supports CSV format. Basic Use, Fetch stock pricehistory

$ nsecli history --symbol SBIN -s 2017-01-01 -e 2017-01-31 -o output.csv

This will save price history of State Bank of India for the month of January 2017 as csv file with name output.csv.Lets see the complete functionality using –help option.:

$ nsecli --helpUsage: nsecli history [OPTIONS]

Options:

-S, --symbol TEXT Security code

-s, --start TEXT Start date in yyyy-mm-dd format

-e, --end TEXT End date in yyyy-mm-dd format

-o, --file TEXT Output file name

--series TEXT Default series - EQ

--index / --no-index --index if security is index else --no-index

--help Show this message and exit.

Similar to stocks you can get Index data, just by adding –index flag -

$ nsecli history --symbol "NIFTY 100" -s 2017-07-01 -e 2017-07-27 -o output.csv --→˓index

Contents:

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CHAPTER 8

Indices and tables

• genindex

• modindex

• search

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