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I apologize if this is a stupid question, I'm a complete neophyte in academic finance but I am trying to learn.

I am trying to create an estimate of how likely indexes are to rise/fall by x% by the end of the trading day at the New York Stock Exchange in real time.

Currently what I have been trying to do is analyze historical data for the given asset and compute what percentage of the time that asset has risen/fallen x% between a given time and the end of the trading day. This method is okay but I was thinking the very smart people in quantitative finance might be able to help me out?

Doing some digging on the topic, it appears that indexes often have corresponding implied volatility indexes. That kind of thing seems perfect for what I'm trying to do. But the issue is that these indexes predict volatility over the next 12 months. That seems totally inappropriate for deriving estimates at the level of hours or minutes.

That said, volatility indexes like the VIX take into account supply and demand for options which seems like exactly the sort of thing that would be perfect for improving my model because options are a great way of estimating probability and volatility. Is there a better index, or better method, more suited to my purposes?

I have also considered taking into account recent historical volatility data, but I'm not sure that's truly predictive as volatility could change at any moment.

I would greatly appreciate if anyone could give me any tips or point me in the right direction. Thanks so much!

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    $\begingroup$ The VIX predicts volatility over 1 month (not 12 months). It would be a good starting point for what you are trying to do. I agree that historical vol is probably already taken into account in the VIX, would not add anything. Recently they also added VIX1D with a span of one day, though I don't know much about it. It is worth looking at. $\endgroup$
    – nbbo2
    Aug 2, 2023 at 8:01

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