Investors who trade based on good research are said to be the backbone of stock markets: They conduct research to discover the value of stocks and, through their trading, guide financial prices to reflect true value. What can make their job difficult is that high-speed, short-term traders could use machine learning and other technologies to infer when informed investors are trading. These short-term traders can then buy when informed investors are buying or sell when they are selling, and (in a sense) steal some of their profits. This behaviour could discourage informed investors from trading, thus making prices less informative-which could have wider ramifications for the economy.
To assess this possibility, we investigate an 11-year sample of stock trading and study investors we identify as informed in the long term. We ask whether informed investors are healthy and whether they are affected by shorter-term traders. We find, in contrast to some empirical studies, that informed investors have roughly constant trading and profits in the sample. Also, our findings show no sign prices are getting worse, as our metrics of price informativeness are flat. This is despite a slow growth (though later, a fall) in the presence of shorter-term trading. Moreover, informed investors are sophisticated in how they trade, which might disguise their presence in markets from a detection algorithm.
In general, rather than being the 'prey' in financial markets, informed traders appear to be the 'apex predators.' They seem to be so good at their trading that (as far as we can measure) relatively little of what they know makes it into prices. Thus, it is unclear that efforts to protect informed investors from high-speed traders are really needed. Instead, regulators might think of ways to increase competition in the financial sector among informed investors themselves.
Bank of Canada published this content on 05 June 2020 and is solely responsible for the information contained therein. Distributed by Public, unedited and unaltered, on 05 June 2020 18:40:01 UTC