Assessing the Value Risk (VAR) for BSE Index consisting of 30 stocks by using various parametric, nonparametric and semiparametric models for estimating Value-at-Risk (VAR)

The objective of this report is to estimate Value-at-Risk (VAR) for Bombay Stock Exchange (BSE) Index consisting of 30 stocks for a single day and 5-day period using various methods of assessment and comment on the best estimate for VAR. In this report VAR theory and various models used to estimate...

Full description

Bibliographic Details
Main Author:	Gupta, Ruchir
Format:	Dissertation (University of Nottingham only)
Language:	English
Published:	2008
Online Access:	https://eprints.nottingham.ac.uk/22164/

_version_	1848792368181936128
author	Gupta, Ruchir
author_facet	Gupta, Ruchir
author_sort	Gupta, Ruchir
building	Nottingham Research Data Repository
collection	Online Access
description	The objective of this report is to estimate Value-at-Risk (VAR) for Bombay Stock Exchange (BSE) Index consisting of 30 stocks for a single day and 5-day period using various methods of assessment and comment on the best estimate for VAR. In this report VAR theory and various models used to estimate VAR like Parametric models (GARCH, EWMA) and Semi-parametric model (Historical simulation methods and its variants) has been studied and explained. The report also explains the backtesting models to check the accuracy of results. Finally, the models have been applied to BSE Sensitive Index (SENSEX) which consists of 30 stocks in different sectors of Indian economy. The key findings of this report is that Volatility Clustering is one of the most prominent stylized fact for the index due to which there is no single value for VaR which could explain the risk in the market for all times. Rather, investors should base their decision on a range of VaR values based on the state of economy of the country (i.e. inflation, business cycle etc).
first_indexed	2025-11-14T18:43:17Z
format	Dissertation (University of Nottingham only)
id	nottingham-22164
institution	University of Nottingham Malaysia Campus
institution_category	Local University
language	English
last_indexed	2025-11-14T18:43:17Z
publishDate	2008
recordtype	eprints
repository_type	Digital Repository
spelling	nottingham-221642018-01-30T22:37:44Z https://eprints.nottingham.ac.uk/22164/ Assessing the Value Risk (VAR) for BSE Index consisting of 30 stocks by using various parametric, nonparametric and semiparametric models for estimating Value-at-Risk (VAR) Gupta, Ruchir The objective of this report is to estimate Value-at-Risk (VAR) for Bombay Stock Exchange (BSE) Index consisting of 30 stocks for a single day and 5-day period using various methods of assessment and comment on the best estimate for VAR. In this report VAR theory and various models used to estimate VAR like Parametric models (GARCH, EWMA) and Semi-parametric model (Historical simulation methods and its variants) has been studied and explained. The report also explains the backtesting models to check the accuracy of results. Finally, the models have been applied to BSE Sensitive Index (SENSEX) which consists of 30 stocks in different sectors of Indian economy. The key findings of this report is that Volatility Clustering is one of the most prominent stylized fact for the index due to which there is no single value for VaR which could explain the risk in the market for all times. Rather, investors should base their decision on a range of VaR values based on the state of economy of the country (i.e. inflation, business cycle etc). 2008 Dissertation (University of Nottingham only) NonPeerReviewed application/pdf en https://eprints.nottingham.ac.uk/22164/1/07MBAlixrg5.pdf Gupta, Ruchir (2008) Assessing the Value Risk (VAR) for BSE Index consisting of 30 stocks by using various parametric, nonparametric and semiparametric models for estimating Value-at-Risk (VAR). [Dissertation (University of Nottingham only)] (Unpublished)
spellingShingle	Gupta, Ruchir Assessing the Value Risk (VAR) for BSE Index consisting of 30 stocks by using various parametric, nonparametric and semiparametric models for estimating Value-at-Risk (VAR)
title	Assessing the Value Risk (VAR) for BSE Index consisting of 30 stocks by using various parametric, nonparametric and semiparametric models for estimating Value-at-Risk (VAR)
title_full	Assessing the Value Risk (VAR) for BSE Index consisting of 30 stocks by using various parametric, nonparametric and semiparametric models for estimating Value-at-Risk (VAR)
title_fullStr	Assessing the Value Risk (VAR) for BSE Index consisting of 30 stocks by using various parametric, nonparametric and semiparametric models for estimating Value-at-Risk (VAR)
title_full_unstemmed	Assessing the Value Risk (VAR) for BSE Index consisting of 30 stocks by using various parametric, nonparametric and semiparametric models for estimating Value-at-Risk (VAR)
title_short	Assessing the Value Risk (VAR) for BSE Index consisting of 30 stocks by using various parametric, nonparametric and semiparametric models for estimating Value-at-Risk (VAR)
title_sort	assessing the value risk (var) for bse index consisting of 30 stocks by using various parametric, nonparametric and semiparametric models for estimating value-at-risk (var)
url	https://eprints.nottingham.ac.uk/22164/

Assessing the Value Risk (VAR) for BSE Index consisting of 30 stocks by using various parametric, nonparametric and semiparametric models for estimating Value-at-Risk (VAR)

Similar Items