Overcoming the Impasse in Modern Economics

This document is the Accepted Manuscript version of the following article: Francesca Gagliardi, and David Gindis, 'Overcoming the Impasse in Modern Economics', Competition and Change, Vol. 15 (4): 336-42, November 2011, doi: 10.1179/102452911X13135903675732. Published by SAGE.Peer reviewe

Crises and collective socio-economic phenomena: simple models and challenges

Financial and economic history is strewn with bubbles and crashes, booms and busts, crises and upheavals of all sorts. Understanding the origin of these events is arguably one of the most important problems in economic theory. In this paper, we review recent efforts to include heterogeneities and interactions in models of decision. We argue that the Random Field Ising model (RFIM) indeed provides a unifying framework to account for many collective socio-economic phenomena that lead to sudden ruptures and crises. We discuss different models that can capture potentially destabilising self-referential feedback loops, induced either by herding, i.e. reference to peers, or trending, i.e. reference to the past, and account for some of the phenomenology missing in the standard models. We discuss some empirically testable predictions of these models, for example robust signatures of RFIM-like herding effects, or the logarithmic decay of spatial correlations of voting patterns. One of the most striking result, inspired by statistical physics methods, is that Adam Smith's invisible hand can badly fail at solving simple coordination problems. We also insist on the issue of time-scales, that can be extremely long in some cases, and prevent socially optimal equilibria to be reached. As a theoretical challenge, the study of so-called "detailed-balance" violating decision rules is needed to decide whether conclusions based on current models (that all assume detailed-balance) are indeed robust and generic.Comment: Review paper accepted for a special issue of J Stat Phys; several minor improvements along reviewers' comment

Tools for Financial Innovation: Neoclassical versus Behavioral Finance

The behavioral finance revolution in academic finance in the last several decades is best described as a return to a more eclectic approach to financial modeling. The earlier neoclassical finance revolution that had swept the finance profession in the 1960s and 1970s represented the overly-enthusiastic pursuit of only one model. Freed from the tyranny of just one model, financial research is now making faster progress, and that progress can be expected to show material benefits. An example of the application of both behavioral finance and neoclassical finance is discussed: the reform of Social Security and the introduction of personal accounts. Copyright 2006 by the Eastern Finance Association.

Stock market returns and the content of annual report narratives

This paper uses the tools of computational linguistics to analyze the qualitative part of annual reports of UK listed companies. More specifically, the frequency of words associated with different language indicators is used to forecast future stock returns. We find that two of these indicators, capturing ‘activity’ and ‘realism’, predict subsequent price increases, even after controlling for a wide range of factors. Elevated values of these two linguistic variables, however, are not symptomatic of exacerbated risk. Consequently, investors are advised to peruse annual report narratives, as they contain valuable information that may not yet have been discounted in the prices