Should stock markets be predictable?

By | February 16, 2012
Interfering with normal market interactions means we're doing something that computer gamers have been doing for ages: trying to create AI bots that can outsmart each other. And yes, AI bots do tend to do some rather unusual things at times. But so do people.

Adding measures to limit the influence bots have on market raises the question of how you know whether a trade was prepared by a bot or by a person. Without this distinction, you can't filter out bots in the fast-paced transactional world. But on the other hand, if you add rules (e.g. maximum rate of change) across all transactions, you are subjecting natural people traders to the same rules, and thus making the market prices more stable and predictable by guaranteeing certain conditions. It changes the rules of gameplay, and more to the favor of AI as emulating limits is easier for a bot to analyze than a person. Is that a good thing? Probably not.

To draw the analogy: You don't even out the Starcraft battlefield by putting limits on what each player can kill (i.e. adding a maximum kill rate); you even it out by adjusting the abilities that the units have (in network terms, adjusting the weights). Likewise, to tackle the black swan financial problem, we shouldn't be looking at policy that can be applied across the board, but rather at adjusting these 'unit abilities' – e.g. minimum trade 'reload' interval before firing for each account. These weights can even be dynamic / random, just to baffle AIs even more.

I'd also expect humans to adapt to 'learn' AI influence. Gamers do by practicing against computer AIs, so why not in finance too?

Reshared post from +Jon Mallin

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3 thoughts on “Should stock markets be predictable?

  1. Sai

    +Sophie Wrobel Well of course it'd be easy to account for. The point is only that it'd screw up the profit model of ultrafast trading, just like eliminating bulk registration discounts would screw up the profit model of domain squatters. 😉

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  2. Sophie Wrobel

    +Sai I was thinking about that too – I believe you had proposed this some days ago. 🙂

    The problem is that a small transactional cost is something that AI can relatively easily account for – once the AIs are done retraining on each other, I'd suspect that we'd only end up with larger black swans as prediction models scale up price changes to continue nanotrading with the transactional cost as part of the high/low trendline fluctuation weight.

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