Starting with Chamberlin in the 40s, experiments with markets have made economists pessimistic about the merits of decentralized markets, in sharp contrast with centralized markets. The centralized continuous double auction has emerged as the mechanism most advocated by economists to generate the beneficial outcomes associated with competitive equilibrium. Buttressed by recent advances in theoretical modeling of decentralized markets, our experiments have started to paint a different picture, with decentralized markets generating outcomes that are not much different from those of centralized markets. Here, we propose to investigate the very dimension in which decentralized markets have been proposed to improve upon centralized markets, namely, in providing sustained incentives to pay for (inside) information (within the right economic setting, of course) the theory does not claim that decentralized markets will always be better). This contrasts with centralized markets, which theory and experiments have argued lead to the Grossman-Stiglitz paradox (if information is costly, prices cannot be informative). The negativity with which economists generally depict the workings of decentralized markets has affected policy making, certainly since the Great Financial Crisis, to the extent that such markets are now generally shunned, or even, as in the recent European directive MiFID 2, disallowed. Our experiments are meant to bring hard evidence to the table. They should illustrate the possibility of evidence-based policy making in finance.
Decentralized financial markets have been deemed detrimental to efficient and fair pricing because of their lack of transparency (whence the synonym "dark markets"). Recent legislation in both the U.S. and in the E.U. is gradually forcing all trading onto centralized markets, or multilateral trading platforms, where everyone can see, in a timely fashion, pretty much everything that is going on (order submission, executed trades, etc.). However, controlled experiments with financial markets have confirmed a theoretical prediction from the 70s, which is that centralized markets fail to provide incentives to collect information (when this is costly) and hence, centralized markets can at best generate only noisy prices. In contrast, more recent theoretical modeling argues that in certain settings, decentralized markets would actually generate the right incentives, and as a result, prices would be more accurate than in centralized markets. If this is true, the gradual elimination of "dark markets" might not have been a good policy. We propose to study price discovery with costly information acquisition in decentralized markets through controlled experimentation. Our experiments would advise whether recent financial markets regulation may have to be re-examined. While inspired by theoretical reasoning, our recommendation will be evidence-based, and as such, would break with the tradition in rule making in finance, which has been almost entirely model-based.