2
$\begingroup$

I am trying to predict the realised daily close to close variance of an equity index.

I checked the literature on volatility forecasting and tried a bunch of things on a dataset for the S&P 500. The most promising approached were an EWMA, GARCH and just using the squared VIX. I measured the performance of my predictions by looking at average absolute error, mean squared error and also doing a regression between my predictor and the actual squared returns. I am aware that squared returns are very noisy, so I also took longer term averages of them and checked how well my predictors forecasts these averages.

EWMA and GARCH showed a similar performance. I was surprised to see that the VIX did much better. I can clearly see that VIX is biased, since there is the volatility risk premium. Implied vol is on average higher than realised vol, since option sellers want to be compensated, but of course there are exceptions. I tried to remove the volatility risk premium from the VIX by subtracting some rolling averages of the realised risk premium, hoping that this would remove the bias, but my estimation got much worse afterwards.

Does anyone have some experience on this type of problem? Can you confirm my observations? Are there other methods I could try?

Improve this question
$\endgroup$
1
  • $\begingroup$ There is the realized GARCH model that may be useful. Here is a nice presentation of the model by its author. $\endgroup$
    – Richard Hardy
    Jun 7, 2020 at 18:29

2 Answers 2

Reset to default
1
$\begingroup$

EWMA and GARCH are good methods. If you can do better than using the VIX then you should not post online about it and instead just trade that yourself and make a ton of money! Seriously.

I don't love the sound of subtracting some rolling averages of the realized risk premium. While I could see that working because the risk premium does change over time, it also relies heavily on your specific implementation and could result in something quite poor.

Years ago when I looked at this I saw something like 1.07x for the ex-ante implied/ex-post realized premium over a decade plus. You can find that easily from your data.

Improve this answer
$\endgroup$
0
$\begingroup$

You can use blackscholes, use option price and current price and solve for implied vol.

Improve this answer
$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge that you have read and understand our privacy policy and code of conduct.

Not the answer you're looking for? Browse other questions tagged or ask your own question.