Value at Risk: A Comparative Analysis. Filip Iorgulescu. Introduction. Why is VaR a challenging subject for me?. - scientific but also practical - easy to understood, difficult to determine - a benchmark with certain shortcomings.
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Why is VaR a challenging subject for me?
- scientific but also practical
- easy to understood, difficult to determine
- a benchmark with certain shortcomings
VaR - the number that measures risk, so popular it may not need an introduction
The objective: to develop a comparison between different approaches to VaR by the means of a portfolio consisting of three stocks traded at BSE
- the volatility models
- the distributional approaches
It was considered that T = 1 day and p = 1%
Mainly based on Christoffersen (2002) and Codirlasu (2007)
Therefore, I set out from 1-day, 1% VaR formula
VaR1% = - (Q1%σ + μ)S
The following approaches were considered:
The pitch is ready… all the tickets are sold…
The computed VaR measures were examined according to the following criteria:
- level of capital coverage
- calculation requirements
Period: 5 Jan 2001 – 9 May 2008
- Volatility clustering => conditional volatility models are recommended
- Non-normality => other distributional approaches are needed
- No unit roots
A portfolio consisting of three stocks with equal weights: ATB, AZO and TLV. Arguments:
quoted at Category 1 at BSE
diversification across industries
Historical volatility approach
VaR GHD seems to be the most appropriate choice under historical volatility approach.
ES EVT seems to be the most appropriate choice under EWMA volatility approach.
VaR GHD seems to be the most appropriate choice under GARCH (portfolio) volatility approach.
VaR NIG seems to be the most appropriate choice under GARCH (stocks) volatility approach.
VaR GHD seems to be the most appropriate choice under GARCH DCC volatility approach.