Efficiency And Credit Ratings: A Permutation-Information-Theory Analysis
Aurelio Fernandez Bariviera
Universitat Rovira i Virgili – Department of Business
Luciano Zunino
Centro de Investigaciones Opticas (CONICET La Plata – CIC)
Belén Guercio
Lisana B. Martinez
National University of the South – Instituto de Investigaciones Económicas y Sociales del Sur (IIESS)
Osvaldo A. Rosso
Universidade Federal de Alagoas
August 14, 2013
Journal of Statistical Mechanics: Theory and Experiment, No. 8, 2013, DOI: 10.1088/1742-5468/2013/08/P08007
Abstract:
The role of credit rating agencies has been under severe scrutiny after the subprime crisis. In this paper we explore the relationship between credit ratings and informational efficiency of a sample of thirty nine corporate bonds of US oil and energy companies from April 2008 to November 2012. For that purpose, we use a powerful statistical tool relatively new in the financial literature: the complexity-entropy causality plane. This representation space allows to graphically classify the different bonds according to their degree of informational efficiency. We find that this classification agrees with the credit ratings assigned by Moody’s. Particularly, we detect the formation of two clusters, that correspond to the global categories of investment and speculative grades. Regarding to the latter cluster, two subgroups reflect distinct levels of efficiency. Additionally, we also find an intriguing absence of correlation between informational efficiency and firm characteristics. This allows us to conclude that the proposed permutation-information-theory approach provides an alternative practical way to justify bond classification.
Efficiency And Credit Ratings: A Permutation-Information-Theory Analysis – Introduction
In his classical definition, [19] establishes that a market is informationally efficient if prices reflect all available information and classifies efficiency into three broad categories: (i) weak efficiency if today price reflects the information embedded in the series of past prices, (ii) semi-strong efficiency if prices reflect all public information, beyond past prices, and (iii) strong efficiency if prices reflect
all public and private information. We will center our study in the weak form of the informational efficiency. Prices are in fact a mechanism of signaling. [26] says that the price system can be regarded as a platform for communicating information and its functioning is based on the economy of knowledge where “by a kind of symbol, only the most essential information is passed on, and passed on only to those concerned”. In fact such a definition was anticipated in [24], who wrote “when shares become publicly known in an open market, the value which they acquire there may be regarded as the judgment of the best intelligence concerning them”. Later, [7] formalized the first mathematical model of security prices, considering an stochastic process without memory. In fact, as recognized by [28], the Efficient Market Hypothesis (EMH) is the theory of competitive equilibrium applied to securities markets. There is a vast literature on empirical research related to weak informational efficiency. It is worth mentioning here that deviations from the EMH have been confirmed for oil and energy markets – see, for instance, results obtained by [51], [58], [2], [11], [3], [4] and [6].
Since the subprime crisis credit rating agencies (CRAs) activities are under scrutiny, due to their difficulty to rank financial securities, specially Collateralized Debt Obligations (CDOs). There are some paradigmatic examples of slow reaction of CRAs to market movements: Enron was rated investment grade by both, Moody’s and Standard & Poor’s, four days prior to its bankruptcy on December 2nd 2001, and more recently, Lehman Brother was still rated investment grade by both agencies on the day of its bankruptcy filing on September 15th 2008.
The aim of this paper is to build a bridge between credit ratings and a market derived measure, i.e. informational efficiency. Specifically, we explore the link between the correlated stochastic behavior of the bond yield time series (quantified by a combination of entropy and complexity measures) and bond ratings. We want to: (i) classify corporate bonds by means of the complexityentropy causality plane, (ii) establish a correspondence between credit ratings and levels of informational efficiency, and (iii) analyze the potential link between market efficiency and firm ratios. It is worth remarking that we are not trying to analyze causality between credit rating and informational efficiency. Probably, a better rating induces market participants to trade more actively this bond, increasing the informative flow to the market and, consequently, the associated informational efficiency. On the contrary, it could be thought that better informational efficiency reflects an intrinsic quality of the firm that is captured by CRAs.
This paper is organized as follows. Section 2 presents a review about credit ratings. Section 3 describes the study of informational efficiency by using tools derived from Information Theory. Section 4 details the data analyzed and the results obtained. Section 5 draws the main findings of our work. Finally, A includes a thorough explanation of the permutation-information-theory based quantifiers applied in this paper.
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