Reflexivity in Credit Markets

Abstract

At least one co-author has disclosed a financial relationship of potential relevance for this research. Further information is available online at http://www.nber.org/papers/w25747.ack NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

The Profit-Credit Cycle

“…This finding connects well with older ideas of "displacements" in the credit market triggering waves of optimism (Kindleberger, 1978;Minsky, 1977). It reinforces the importance of funding supply shocks for credit and business cycles (Krishnamurthy and Muir, 2017;Mian et al, 2017b) and meshes nicely with new modelling approaches of the credit cycle using diagnostic or extrapolative expectations (Bordalo et al, 2018;Greenwood et al, 2018). Our results suggest that such biases in expectation formation have important macroeconomic consequences.…”

“…3 We furthermore assume that R is uniformally distributed over (1, 1 + ρ) with meanR, which ensures that projects have a positive NPV, while it is not possible to finance projects with debt only. Furthermore, for ease of exposition, assume that there is no persistence in R. Similar to Greenwood et al (2018) we assume that expectations R E t are a mixture of (i) a rational forward looking component and (ii) a backward looking extrapolative component.…”

“…A novel theoretical literature links the credit cycle to behavioral biases in the expectation formation process. In these models agents extrapolate from current default rates when building their expectations about future credit market outcomes (Bordalo et al, 2018;Greenwood et al, 2018). As a result, creditors are too optimistic when default rates are low and too pessimistic when default rates are high.…”

“…In their model creditors assign higher probabilities to states of the world that have become more likely in light of recent data, leading to excessive credit growth after a number of good realizations and to predictable reversals. In Greenwood et al (2018) creditors extrapolate default risk.…”

Handling the COVID‐19 crisis: Toward an agile model‐based systems approach

“…To conclude this initial discussion on the crisis of models, we point out that if the scenario that we highlighted in Figure 2 comes true, we may also eventually be forced to deal with another crisis of models, namely, the crisis of mathematical models used in finance. These other “models” are not necessarily models in the observational sense that we are using in this paper since they suffer from many well‐known issues such as reflexivity , 47 which refers to the fact that mathematical financial models are essentially observing other mathematical financial models, or more deeply the lack of evidence for the market equilibrium hypothesis, 48 which is at the heart of the probabilistic framework used in mathematical finance, but which is in fact rarely observed in practice (see, for instance, Ref. 48 or 49), especially in a financial crisis situation where the market is of course highly unbalanced and volatile and therefore out of equilibrium, as pointed out by several researchers.…”