My team and I are busy coding up a python implementation of the information driven bars (imbalance and run bars) mentioned in Chapter 2 of the text book Advances in Financial Machine Learning.

There really isn't a lot of information published on this technique. I have read the papers in the bib, mainly:

  • The volume clock: Insights into the high frequency paradigm
  • Flow toxicity and liquidity in a high frequency world.

The two papers really highlight the importance of volume sampling and how market micro-structure features like VPIN can be used as an important features but neither provide deeper insight into the imbalance or run bars.

I then turned to chapter 19 which has a very nice explanation on the tick rule and the various micro-structure models and their generations.

However I still don't have a firm grasp on the implementation or details for the information driven bars.

The following blog post has helped us with the implementation Maks Ivanov.

Main question: Is there a piece of literature that I have missed? Where can we learn more about this technique. Is it mentioned somewhere in another journal or a slide show?

  • $\begingroup$ Asking what you have missed I suspect is too hard and too broad to answer (not that I have good knowledge in this area). This technique seems particularly broad enough to be subjective and speculative. Whilst the consideration of various different techniques seems admirable I suspect one method will not be universally optimal for a given contract or trading model. $\endgroup$ – Attack68 Apr 5 at 16:37
  • $\begingroup$ It's not a question of what I missed but rather that I can't find any other literature out there on the topic. There is lots written on the importance of volume sampling but an implementation / algorithm / discussion on information driven bars is sparse. $\endgroup$ – Jacques Joubert Apr 7 at 17:01
  • $\begingroup$ @JacquesJoubert, I wouldn't imagine posting here will yield many useful responses. you'll probably have better luck posting on Nuclear Phynance or Willmott (if it's still around?). that said, as much as NP would likely be a better resource, I'd be surprised if you received helpful responses there as most consider TA or TA-variants a bit loosey goosey. esoteric rarely means insightful. best of luck all the same. $\endgroup$ – Chris Apr 11 at 19:27

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