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Portfolio VaR Jorion, chapter 7. Goals Portfolio VaR definitions Portfolio VaR global equity example –Delta normal –Historical –Bootstrap Incremental.

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Presentation on theme: "Portfolio VaR Jorion, chapter 7. Goals Portfolio VaR definitions Portfolio VaR global equity example –Delta normal –Historical –Bootstrap Incremental."— Presentation transcript:

1 Portfolio VaR Jorion, chapter 7

2 Goals Portfolio VaR definitions Portfolio VaR global equity example –Delta normal –Historical –Bootstrap Incremental VaR

3 Portfolio VaR VaR on portfolio of assets Similar to standard VaR with new complications –Covariance –Dependence –Portfolio weights

4 Global Portfolio Example Data – wldeqp.dat, wldeqp.info –Column 1: date (mm/dd/yy) 92-2002 –Column 2-6, MSCI equity indices (US $) World Japan US Germany UK

5 Historical VaR Matlab – gport.m Notes: –Portfolio weights: Equal weighted over US, Japan, Germany, UK –Compares delta normal with historical

6 Monte-Carlo VaR Matlab – mcgport.m Critical issue: –Variance covariance matrix –See revised normal.m Similar patterns to univariate VaR

7 Bootstrap VaR Matlab: – bgport.m Note: –Bootstrap modeling of dependence – Importance of getting this right

8 Correlations and Portfolio VaR

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11 Extremes VaR on portfolio is max for correlation of 1 Portfolio VaR is the sum of VaR’s

12 Component Issues Sensitivity to portfolio changes –Analytic tools (in Jorion) Bootstrap and monte-carlo methods –Try sweeping through different portfolios –Applications – US to Global change bsensgport.m – US to Japan change bsensgport2.m

13 Adding Options to Equity Portfolios Problem: –50/50 US/UK equity portfolio –Cover the US position only by purchasing a put Do this at the money first 20 day (1 month European option) –First, what does the eventual portfolio distribution look like?

14 Part 1 What does an option do to the distribution? optdist.m

15 Part 2 Evaluating option purchases – usoptchoice.m

16 Summary Portfolio choice adds different dimensions –Covariances –Joint bootstrapping Often critical May be most important part of modeling risk factors


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