Research

Persistent noise, investors’ expectations, and market meltdowns

The recent financial crisis has revived interest in the question of what triggers crashes and meltdowns in financial markets. An important reason for abrupt and large price dislocations is the lack or 'slow motion' of arbitrage capital (Duffie 2010) that weakens the risk-bearing capacity of liquidity providers. In a recent paper the authors propose an alternative explanation that relies on expectations dynamics in the presence of persistent noise trading. Their idea relies on a particular, backward-looking expectation revision mechanism that arises when asset prices reflect fundamentals and persistent noise trading, dubbed "retrospective inference." They show that because of retrospective inference, the market can hover in a high-liquidity, high-informational-efficiency state, or be mired in a low- liquidity, poor-informational-efficiency trap.

Examples of persistent noise trading abound. Indeed, there is strong evidence that capital flows to and from investment funds are strongly related to past performance, implying that an exogenous liquidity shock can trigger a vicious cycle of outflows and declining performance. A vivid example of this dynamic is offered by the 'Quant Meltdown' episode, when some of the most profitable hedge funds steadily unwound their positions during the second week of August 2007. The authors argue that retrospective inference offers an explanation of this type of events that abstracts from the role of slow moving arbitrage capital, and highlights instead the importance of equilibrium transitions.

The full research article can be read at Vox EU