# Tag Info

3

As @babelproofreader mentioned, I recently blogged about the Roll model (see the original paper), which provides a very simple method for inferring the bid/ask spread based on trade prices. In short, you can estimate the cost using using the covariance: $c = \sqrt{\gamma_1}$. Where $\gamma_1$ is the $Cov(r_t, r_{t-1})$. (The R code is provided in my post). ...

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To construct best bid/ask from ITCH you must build a book incrementally from the messages in the data. Every message, except for system oriented messages, and non-displayed Trades, represent an order or an action on an order. Process the data, build a book, and you will naturally be left with the best bid/ask at the top of each side.

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I was able to identify significant participants by order size on CME exchange. I think ITCH is even more informative that CME's data format. The trick is to learn very closely the incremental data and the order in which this data arrives. We can assume that exchange's Matching Engine and its market data distribution algorithm are programmed machines, ...

1

The cross-validation procedure does not turn on the choice of algorithm. Yes - calculate the prediction error of the fitted models when predicting the V'th part of the data. Combine the V estimates of prediction average using a simple average. Subsets should be randomly sampled (roughly equally sized). 2a. Subsets should not overlap. No. As long as the ...

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