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I have a task to calculate VaR for a portfolio of stocks and bonds. The main problem is that there is 1 stock which IPO was in November 2023 so there is few data points. To cope with that I came up with 2 ideas:

  • Bootstrapping stock's returns until I get 500 data points
  • Take as a proxy some industry index and use its returns

I think that 2nd option is more preferable as it takes into account specific risks of the industry. Can somebody approve my idea or there can be any better consideration?

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You may be able to use a multi-factor model for the VaR, if allowed by whoever needs to approve/validate your VaR methodology.

In summary, assume that there are a only few indices, and that every stock has betas to the indices and some idiosyncratic volatility not explained by the indices.

You might even use just one general market index, and one beta for each stock, that is, CAPM.

This takes a lot of work with historical data, so you may want to use vendor products for some of it, e.g. BARRA.

One advantage is that when you encounter a stock with not enough history to calculate pairwise historical correlations, it's easier to predict the betas and idiosyncratic volatilities. If you use a vendor, just use the vendor's predicted betas.

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