Estimating Portfolio VaR for a Recent IPO with a Factor Model

Summary

This note considers how to estimate value-at-risk for a stock-and-bond portfolio when one stock has only a short post-IPO return history. It raises two possible workarounds: bootstrap the stock's observed returns to create a longer series, or substitute returns from an industry index. The response instead suggests a multi-factor model, in which stocks have sensitivities to a small set of indices and residual volatility not explained by those factors.

A simpler version could use a broad market index and a single beta per stock, as in CAPM. The response notes that estimating factor sensitivities and idiosyncratic volatility requires substantial historical data, and mentions vendor estimates as an option. It argues that betas and residual volatilities may be easier to estimate than pairwise historical correlations for stocks with limited records. The suggestion depends on approval of the VaR methodology and does not provide a worked calculation or validate a particular model.

Key ideas

• A short return history after an IPO makes historical correlation estimates difficult.
• A multi-factor model can represent stock returns through index exposures and residual volatility.
• A broad-market index with one beta per stock is a simpler CAPM-style alternative.
• Vendor estimates may supply factor betas and idiosyncratic volatility when internal data is limited.
• The proposed approach requires methodology approval and is not demonstrated with a worked VaR example.

Tags

# Value-at-Risk of a portfolio with a stock after recent IPO


# Value-at-Risk of a portfolio with a stock after recent IPO












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?

## Answer by Dimitri Vulis (score 1, accepted)

https://quant.stackexchange.com/a/78769

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.

Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.