Using Behavioral Economics to Analyze Credit Policies in the Banking Industry

Abstract

1. Introduction Are private banks efficient when providing credit to the real economy? Probably, in the last decades there has not been such a bitter debate in academic research as the one related to efficiency in financial markets. Hence, we will not find a unanimous answer to that question, but in the midst of the worst financial crisis since the Great Depression, it seems unavoidable to wonder how did all go wrong? Kindleberger (1978) provided what Shleifer (2000) named the 'anatomy of a price bubble': a process that starts with some good news that generate a profit in an asset, followed by a 'smart-money response' where both the supply and the demand of such asset are encouraged by initial investors. The bubble is then sustained by the same investors, who stimulate positive feedback trading by (...) facilitating noise trader speculation (Shleifer, 2000, p.172). That is, the same agents who are benefited in the early stages of the bubble generate a greater supply of the asset and encourage other actors to participate, increasing the demand and sustaining asset prices until the market, eventually, collapses. Hens and Bachmann (2008) explain the anatomy of the financial bubble that led to our present crisis. They interpret the initial good news that rose prices on the real estate market as the speculative money coming into the house market after the dot-com bubble burst. Then, smart-money investors started the packaging of mortgage risks in new securities (MBS) that are sold outsourced in special investment vehicles (SIV) and sold worldwide (p.94). This approach is focused on the role that subprime mortgages had in the process that led to the crisis, but in this paper we want to delve a little deeper into the study of how the 'smart-money response' promoted the credit growth in order to sustain the bubble. The financial meltdown highlighted significant shortcomings on procedures used by the banking sector when providing credit to the real economy for two reasons. First, a long period of indulgence granting personal loans and mortgages boosted the credit bubble all over the world, and second, after the collapse of Lehman Brothers, an era of suspicion within the banking sector precipitated the liquidity crunch and the credit squeeze to private agents. A traditional approach to analyze market efficiency is the efficient market hypothesis (EMH) by Fama (1970) applied to capital markets. In this paper we will first provide a brief outlook on several ideas that behavioral economics has presented when analyzing the EMH in the context of capital markets, and then, in the bulk of this paper, we shall apply that analysis to the study of retail banking sector -both from a macro and a micro perspective- when granting credit to businesses and households. 2. Behavioral Finance and the EMH on Capital Markets The efficient market hypothesis (EMH) postulates market prices reflect the 'true value' of capital stock, given information available. Fama (1970) sees three categories in the EMH. Under the weak-form EMH, current stock prices fully reflect all currently available market information. Hence, past price and volume information would have no relationship with the future direction of security prices. The semistrong-form EMH assumes current stock prices adjust rapidly to the release of any market and non-market information available to the agents. Finally, the strong-form EMH version implies that prices fully reflect all public and private information. The strong-form assumes perfect markets where information is cost-free and available to all market participants at the same time. (3) Empirical data has challenged the EMH. Relevant examples are Shiller (1981), De Bondt and Thaler (1985), Jegadeesh and Titman (1993), Siegel (1998) or even Fama (1991) and Fama and French (1992), which evidence market anomalies inconsistent with market rationality. Empirical evidence against the weak form EMH include stock market volatility much higher than justified by the expected net present value of future dividends, extreme losers (the worst performing stocks over a long period in the past) outperforming extreme winners in the short future -a sign of overreaction and return to the mean- or, on the contrary, for short term periods price movements over six to twelve months tend to predict future movements in the same direction (which is called 'momentum'). …