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I was considering the role that Central Banks play in the context of market stability and market efficiency. It is indeed true that Central Banks can help with both, for example, by matching tweaking interest rates in a way that matches the expectations of all market participants and thus reducing uncertainty.
However, it is also true that Central Banks could also hurt stability long-term too since very cheap interest rates and a plentiful supply of money can encourage risk taking. For example, if it costs you 0.01% annually to borrow, you’d want to borrow as much as you can even if you can get a low-ish return of 1% on it. But if it costs you 20% to borrow , you’re going to get eaten alive by the interest rate unless you have a very good reason to put that capital into use.
Anyways, there’s an entire field of study here with many complexities and nuances, each worth of their own thread.
What I was thinking about was the idea of trading strategies that are based on black box algorithms. Usually there’s an economic rationale (expectation of interest rate increase, over- or under-valuation of a stock, and so on) for various trading strategies, but what’s wild is that many of these quant hedge funds are starting to delve into AI and thereby relinquish control of many aspects of the model building that intakes and generates…
