I agree it’s all quite understandable if people had the resources available. I would argue part of the reason it is opaque is the fears of operators that too much public attention can bring a lynch mob. This business can literally be one of the most profitable activities on the planet, but contrary to populist sentiment this is not evidence of wrong doing, it’s simply because it’s so automated and scalable and all electronic.
Back to ATS and dark liquidity, this isn’t as trivial to explain as you suggest, it requires understanding of flow toxicity and information theory to be understood completely. You must know that in markets, transactions can be beneficial to both parties as they have different objective functions and timescales.
What evidence can be presented that supports the idea HFT operators are extracting increasing costs on the system? I’m not aware of any.
What you’re failing to disclose is that there is an easy way out of solving the adverse selection problem. For example you could buy “uninformed flow”. I think that you could agree that for the touted sophistication of the field you would expect something … more sophisticated?
Again, don’t get me wrong. I love the field but I think it’s stagnant in certain aspects and I like to have a sober view of it.
It’s too late in the day for me today to attempt to write a coherent and accurate explanation of exactly why I say that. However I will say you don’t understand this isn’t a zero sum game and it’s an incorrect argument to claim HFT is an arms race in a game like a war, which is a negative sum game.
Your risk argument doesn’t hold water because liquidity is not the only risk. There are at least 20+ I can think of from the top of my head without even trying.
I’ll rest my case here.
HN isn’t the best forum for this type of ongoing discussion. Engage me on reddit if you like. u/alchemist1e9
What I am saying is that the thesis that the costs are dropping due to HFT style strategies has not been proven. Majority of the HFT tend to be market makers which tend to help with liquidity but not all are. I agree that liquidity helps offload or acquire large stakes.
As for NBBO and the effect a regulation has on markets you seem to be extremely US centric but if you go across the ocean and find out that Europe has no concept of NBBO at all, and that a retail person trading experience is equivalent for getting a different price on Amazon depending on which web browser they use you could imagine how that would make an average retail person feel.
Another example of the regulation is trying to move a large stake outside regular hours when NMS is suspended. Why do you think OTC block trades are pre-arranged at a fixed price? You can even look them up in relevant reporting facilities.
As for dark pools, ATS and internalizers there’s nothing difficult about them. I don’t think you’re doing anyone any favors by obfuscating an extremely simple concepts. Those market participants with their specific mechanics that are learnable. What’s complex is how to devise strategies and how to rely on the liquidity sources to get your desired fills and desired rates. You’re describing bread and butter of trading at an institutional level and the fact it seems difficult can maybe be attributed to the fact that it is opaque, doesn’t enjoy public communities, e.g. very little blog posts exist on the subject and the knowledge is sort of centralized to a specialized corners of the industry. But it is learnable without great difficulty if you have access to the resources.
What’s surprising to me is that a lot of people can talk about abstract concepts in computer science and then don’t connect facts that bridge into a separate discipline. As an example I could refer to consistency that people love to rave about but somehow forget the concept the moment capital market is introduced.
And yes, I’m familiar with the no trade theorem and relevant academic concepts but they are all models that often don’t translate to real life due to extremely limiting assumptions that don’t enjoy any connection to reality. I think it’s a problem with the community in this particular industry to take academic market models at face value. Often you will find that looking at a model carefully with assumptions that mirror real world, your performance gets better.