# Measuring Volatility from Execution Prices

I was told of a way of measuring the volatility of a stock by looking at the reported execution prices (from Level III or Level II data.) I'm well aware of how to measure volatility by looking at the mid-quote or similar but I have never heard of a way that would use solely the prices of the executions. Unfortunately, I cannot find any paper that would either use such method or define it. Can anyone point me in the right direction?

Possibly you might be able to first estimate the bid-ask spread from execution prices, using the method of Roll (1984), and then adjust the volatility for this.

Essentially the bid-ask bounce adds to the underlying volatility, so knowing an estimate of the b/a and the apparent volatility, the underlying volatility could be recovered by subtraction.

Roll(1984)

• I already know the bid and ask spread since I can rebuild the book from Level III data. Moreover, there is no such thing as bid-ask bounce since each execution is linked to a specific limit order. Commented Jun 18, 2015 at 16:53

Do you mean the "realize measure" of volatility using the intraday Transaction-and-Quote data? If that's the case, just trade data, or mid-quote would be sufficient.

Looking at Level II and level III data really introduces a lot of noises (hudge cancellation rates, orders placed by HFT blindly to gain time-priority advantage). Using those data to calculate some weighted-average of price is not a sound approach to me.

• Thank you for you feedback but I'm a little confused by your answer. I'm not sure what do you mean when you talk about "... some weighted-average of price...": can you clarify? Also, what is a "hudge" cancellation? Is it just a typo? Moreover, If I'm looking at the execution prices in Level III data what does the cancellation rate of limit orders or the HFT submission strategies have to do with the reported execution prices? Finally, when you talk about TAQ data, are you suggesting to use transaction prices sampled at some interval to compute the returns? Commented Jun 18, 2015 at 17:34