Skip to content

This repository provides an approach towards data analysis and visualization of financial dataset which is used to gauge the impact of COVID-19 on Indian Stock Market mainly on benchmark indices i.e. NSE NIFTY-50 and S&P BSE SENSEX.

License

strikersps/COVID-19-Impact-On-Indian-Stock-Market

Repository files navigation

Impact of COVID-19 On Indian Economy from The Perspective of Indian Stock Market.

forthebadge made-with-python Made withJupyter Repo-Size-Badge Binder

GitHub contributors GitHub Issues GitHub Stars GitHub Forks Dalal Street Image

NOTE: Run the jupyter notebook name Impact-of-COVID-19-On-Indian-Economy.ipynb from the file explorer in the Jupyter Lab after clicking on the badge: Binder

1. Objective

This project is an analysis based on the publicly available datasets related to COVID-19, Indian Stock Market Indices Dataset, Volatility Prices and Oil Prices. The goal is to examine the behaviour of Indian Stock Market from Jan 2020 to Dec 2020 and how it was impacted due to COVID-19, Oil Price War between Russia and Saudi Arabia, Lockdowns due to COVID-19 and other major events happened during the period.

2. Introduction

  • Indian stock market saw one of the biggest falls in its history i.e. BSE SENSEX and NIFTY-50 corrected sharply by 38% in March 2020, more specifically this crash was another major crash after the Global Financial Crisis of 2008 which was due to fall in the Housing Price in the USA.
  • COVID-19 had a brutal and dramatic impact on financial markets all over the world. It has exposed investors to unprecedented levels of risks causing investors all over the world to suffer significant losses in a very short period of time.
  • The idea was that if you want to measure/gauge the behaviour of the stock market then you look at the different indices listed in the exchanges as indices are the best way to measure how the whole market or a section/sector of the market is performing. Market indices are classified on the basis of broader/benchmark market indices and sector indices majorly and every exchange has its own set of indices.

  • Indian Stock Market has two major exchanges namely National Stock Exchange and Bombay Stock Exchange and there are more than 5000 companies listed on both the exchanges and monitored by the market regulator SEBI. So to gauge the market we need to look at the price action of benchmark indices and sector indices. There are various indices but the most famous and concise indices are SENSEX of Bombay Stock Exchange(BSE) and NIFTY-50 of National Stock Exchange(NSE). There is another index known as INDIA VIX which is a way to gauge the volatility in the Indian market. Volatility is a very important variable in order to understand whether on a given market session or time period the investors are afraid or greedy when buying securities in the market.

  • The stock market in the short term can be considered as a sentiment index of an economy and it's a way to measure the emotions of an economy. If you look at the stock market benchmark indices after March 2020, you will see a very quick recovery in the market and selected sectors like IT, Pharmaceuticals due to which it is hard to answer the question whether COVID-19 has impacted the market or not just on the basis of data?

  • The main goal of the project is to identify/quantify the relationship between the COVID-19 and other major events which are a direct or indirect consequence of COVID-19 and its impact on the Indian Economy by studying, visualising, and establishing relationships between the Indian Stock Market Indices (NIFTY-50 and SENSEX), COVID-19 cases and deaths around the world, lockdowns imposed by the governments and various other events.

  • This report stays away from making prediction on Indian financial markets because a huge proportion of Indian economy is unorganized. With limited time and infrastructure, it is really hard to make any short term predictions of the stock market because upside and downside in a short term or long term depends upon various factors like economic, social, technology, climate, businesess etc.

  • The efficient-market hypothesis (EMH) is a hypothesis in financial economics that states that asset prices reflect all available information. A direct implication is that it is impossible to "beat the market" consistently on a risk-adjusted basis since market prices should only react to new information. The idea that financial market returns are difficult to predict goes back to Bachelier (1900), Mandelbrot (1963), and Samuelson (1965), but is closely associated with Eugene Fama, in part due to his influential 1970 review of the theoretical and empirical research.

3. Datasets

  • Extracted dataset's are of price actions of SENSEX, NIFTY-50, INDIA VIX, COVID-19 Total Deaths and Cases Worldwide, and also the price actions of some of the sector indices which are heavily impacted due to COVID-19 i.e. NIFTY-AUTO, NIFTY-IT, NIFTY-PHARMA, NIFTY-BANK, NIFTY-MEDIA, NIFTY-REALTY, NIFTY-FMCG.

  • As the Oil Price War between Saudi Arabia and Russia has also impacted the market, the dataset's related to Crude Oil WTI, BRENT Europe and CBOE-Crude-Oil Volatility are also used.

  • For some of the dataset's, the python library Quandl which provides access to data about various economic variables or price data of financial securities/instruments.
  • Following table shows a summary of all the datsets with their source:
Sr. No Name of Dataset Source
1 COVID-19-Dataset Our World In Data COVID-19 Dataset
2 Crude Oil WTI Price Index Fetched through quandl
3 BRENT Europe Crude Oil Price Index Fetched through quandl
4 VIX index of OVX (ETF on Crude Oil) CBOE Crude Oil Volatility Index (^OVX)
5 INDIA-VIX INDIA-Volatility Index (INDIA VIX)
6 NIFTY-50 NIFTY-50-Index-Data
7 BSE-SENSEX Fetched through quandl
8 NIFTY-IT NIFTY-IT-Index-Data
9 NIFTY-PHARMA NIFY-Pharma-Index-Data
10 NIFTY-FMCG NIFTY-FMCG-Index-Data
11 NIFTY-Auto NIFTY-Auto-Index-Data
12 NIFTY-Media NIFTY-Media-Index-Data
13 NIFTY-Bank NIFTY-Bank-Index-Data
14 NIFTY-Realty NIFTY-Realty-Index-Data
15 Google Trends Fetched using pytrends

4. Conclusions

  • The main conclusions drawn from the above work are:
    • Market was reacting to the anticipation and the consequences of globalization. The market downturn/sharp correction in the global markets was influenced by several non-economic factors due to an unpredicted event i.e. COVID-19 Pandemic and it has affected almost all of the major sectors of the global economy. But one more question arises at the same time that how only COVID-19 pandemic has made the market fall by that much, more clearly Does COVID-19 is the only reason for the fall happened in March-2020? and the answer is Yes but not just COVID-19 rather the sequence of events or the ripple affect caused by COVID-19 like countries imposing strict lockdown policies, businesses are shutting down their daily operations except the pharmaceutical and consumer discretionary sectors, MSMEs (Micro, Small & Medium Enterprises) are severely affected due to lockdowns, people all around the world especially investors were panicking under the impression of Global Recession and at the same time there was an Oil Price War which had happened between Saudi-Arabia and Russia which made the market fall further in the March and April of 2020.

    • COVID-19 is still present and it is affecting people at a pace but markets all around the world are at all time highs just after the fall of March, 2020 which is a contradiction to my initial hyphothesis which was based upon previous financial crisis i.e. "It will take atleast 2 years for the market to recover its losses and reach its all-time highs again" but the opposite has happened with markets globally recovered its losses in just 8-9 months.
      NIFTY-50 Record-Pace to Reach 13K

    • The above snapshot shows that it just took 170 trading days for NIFTY-50 to reach 13K (All Time Highs) from 8,318 point recorded on March 25, 2020 when benchmark indices i.e. SENSEX and NIFTY-50 of indian stock market crashed by approximately 13% due to Coronavirus Pandemic!

NOTE: If you want to cite this repository, then please copy the respective style information (APA or BibTex) provided under cite this repository option as shown in the tutorial: https://github.blog/wp-content/uploads/2021/08/GitHub-citation-demo.gif
GNU General Public License v3.0

GPL-V3 license

About

This repository provides an approach towards data analysis and visualization of financial dataset which is used to gauge the impact of COVID-19 on Indian Stock Market mainly on benchmark indices i.e. NSE NIFTY-50 and S&P BSE SENSEX.

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published