Peso Problem Research Articles

Hunting the Living Dead: A 'Peso Problem' in Corporate Liabilities Data

Recent literature has pointed out that information asymmetries may be the reason for the poor performance of structural credit risk models to fit corporate bond data. It is well known in fact that these models lead to a strong understatement of the credit spread terms structure, particularly on the short maturity end. Possible explanations stem from strategic debt service behavior and, as discovered more recently, the problem of accounting transparency. This raises the possibility that some of these flaws could be reconducted to a sort of peso problem, i.e. that the market may ask for a premium in order to allow for a small probability that accounting data may actually be biased (Baglioni and Cherubini, 2005). In this paper we propose a modified version of the Duan (1994,2000) MLE approach to structural models estimation in order to allow for this peso problem effect. The model is estimated for the Parmalat case, one of the most famous cases of accounting opacity, using both equity and CDS data.

Is IPO Underperformance a Peso Problem?

Recent studies suggest that the underperformance of IPO's in the post-1970 sample may be a small sample effect or Peso problem. That is, IPO underperformance may be due to observing too few star performers ex-post than were expected ex-ante. We develop a model of IPO performance that captures this intuition, by allowing returns to be drawn from mixtures of outstanding, benchmark, or poor performance. We estimate the model under the null of no ex-ante average IPO underperformance to construct small sample distributions of various statistics measuring IPO relative performance. We find that small sample biases are extremely unlikely to account for the magnitude of the post-1970 IPO underperformance observed in data.

Modelling Probabilities of Devaluations

I show why, when the realized rates of depreciation within the exchange rate band are regressed on a given information set and conditioned on (ex post) actual no realignment (à la drift adjustment), a ‘peso problem’ is still encountered. The reason is that the frequency of realignments in the data need not be the same as the frequency of the (even small) subjective probabilities that a realignment may take place. I suggest an alternative approach to solve the peso problem and provide consistent estimates. My estimates of the expected realignment rates are greater than the ones obtained using the drift adjustment method.

Filtering Returns for Unspecified Biases in Priors when Testing Asset Pricing Theory

Procedures are presented that allow the empiricist to estimate and test asset pricing models on limited-liability securities without the assumption that the historical payoff distribution provides a consistent estimate of the market's prior beliefs. The procedures effectively filter return data for unspecified historical biases in the market's priors. They do not involve explicit estimation of the market's priors, and hence, economize on parameters. The procedures derive from a new but simple property of Bayesian learning, namely: if the correct likelihood is used, the inverse posterior at the true parameter value forms a martingale process relative to the learner's information filtration augmented with the true parameter value. Application of this central result to tests of asset pricing models requires a deliberate selection bias. Hence, as a by-product, the article establishes that biased samples contain information with which to falsify an asset pricing model or estimate its parameters. These include samples subject to, e.g. survivorship bias or Peso problems.

Why Do Investors Still Hope? The Soviet Repudiation Puzzle (1918-1919)

This paper provides an empirical study of bond prices reactions following a repudiation. Based on an original database, it analyses the repudiation by the Soviets of bonds issued under the Tsarist regime. For the two years following the repudiation two striking feature of a representative Tsarist bond traded in Paris must be highlighted: first, the price decline following the repudiation announcement is limited; second the price remains relatively high, and even increases, during the two following years. This is the so-called Soviet Repudiation Puzzle. We argue that the bonds' persistent high relative value can be approached via the Peso problem hypothesis: prices are affected by expected events that never took place and thus remained unobservable. In the Russian case, several unusual events could be expected: a dramatic change in the Russian attitude, due for instance to the Soviet overthrow or a takeover of part of the debt either by the French or by another government (most likely countries created from the former Russian Empire). In this respect, the Soviet Repudiation Puzzle appears as a multidimensional peso problem.

A Portfolio Perspective on Option Pricing Anomalies

We empirically study the economic benefits of giving investors access to index options in the context of the standard asset allocation problem. We analyze both expected-utility and non-expected-utility investors in order to understand who optimally buys and sells in option markets. We solve the portfolio problem with a flexible empirical methodology that does not rely on specific assumptions about the process of the underlying equity index. Using data on S&P 500 index options (1987-2001) we consider returns on OTM put options and ATM straddles. CRRA investors find it always optimal to short put options and straddles, regardless of their risk aversion. The option positions are economically and statistically significant and robust to corrections for transaction costs, margin requirements, and Peso problems. Surprisingly, loss-averse and disappointment-averse investors also optimally hold short positions in puts and straddles. Because derivatives are in zero net supply, this suggests that generating empirically relevant option prices in an equilibrium model is a challenging task, even with investor heterogeneity and even with commonly-studied behavioral preferences. Only when loss aversion is combined with highly distorted probability assessments, can we obtain positive portfolio weights for puts and straddles.

Statistical Arbitrage and Securities Prices

This article introduces the concept of a statistical arbitrage opportunity (SAO). In a finite-horizon economy, a SAO is a zero-cost trading strategy for which (i) the expected payoff is positive, and (ii) the conditional expected payoff in each final state of the economy is nonnegative. Unlike a pure arbitrage opportunity, a SAO can have negative payoffs provided that the average payoff in each final state is nonnegative. If the pricing kernel in the economy is path independent, then no SAOs can exist. Furthermore, ruling out SAOs imposes a novel martingale-type restriction on the dynamics of securities prices. The important properties of the restriction are that it (1) is model-free, in the sense that it requires no parametric assumptions about the true equilibrium model, (2) can be tested in samples affected by selection biases, such as the peso problem, and (3) continues to hold when investors’ beliefs are mistaken. The article argues that one can use the new restriction to empirically resolve the joint hypothesis problem present in the traditional tests of the efficient market hypothesis. In a fairly general environment, this article proposes a novel martingaletype restriction on the dynamics of securities prices. This restriction has a number of important properties. Most notably, the restriction may be viewed as model-free because it requires no parametric assumptions about the true equilibrium model. To derive the restriction, we rely on the concept of statistical arbitrage, a generalization of pure arbitrage. A pure arbitrage opportunity (PAO) is a zero-cost trading strategy that offers the possibility of a gain with no possibility of a loss. As is well known, the existence of PAOs is incompatible with a competitive equilibrium in asset markets. The fundamental theorem of the financial theory establishes a link between the absence of PAOs and the existence of a positive pricing kernel which supports securities prices. While the absence of PAOs is a necessary condition for any equilibrium model, this condition alone often yields pricing implications that are too weak to be practically useful. For example, when valuing options in incomplete markets, the no-arbitrage bounds on option prices are typically very wide. To strengthen pricing implications, several recent articles

Why are Put Options So Expensive?

This paper studies the overpriced puts puzzle'' -- the finding that historical prices of the S&P 500 put options have been too high and incompatible with the canonical asset-pricing models, such as CAPM and Rubinstein (1976) model. To investigate whether put returns could be rationalized by another, possibly nonstandard equilibrium model, we implement the model-free methodology of Bondarenko (2003a). The methodology requires no parametric assumptions on investors' preferences. Furthermore, it can be applied even when the sample is affected by certain selection biases (such as the Peso problem) and when investors' beliefs are incorrect. The main finding of the paper is that no model within a studied class of models can possibly explain the put anomaly.

The Peso problem hypothesis and stock market returns

The Peso problem hypothesis has often been advocated in the financial literature to explain the historically puzzlingly high risk premium of stock returns. Using a dynamic model of learning, this paper shows that the implications of the Peso problem hypothesis are much more far reaching than the ones commonly advocated, implying most of the stylized facts about stock returns. These include high risk premia, time-varying volatility, asymmetric volatility reaction to good and bad news, excess sensitivity of price reaction to dividend changes and thus excess return volatility.

External shocks and debt accumulation in a small open economy

This paper analyzes the borrowing behavior of a small open economy of a Less Developed Country (LDC) that relies heavily on imports for its capital formation and faces an upward sloping supply function of foreign loans, in an environment where decision makers face uncertainty about the longevity of external shocks. First, a dynamic general equilibrium model is developed which replicates fairly well the business cycle properties of the LDC data. Second, it is shown that uncertainty concerning the longevity of shocks (a relevant type of uncertainty, especially for LDCs) generates forecast errors that are autocorrelated in a way that is similar to Bayesian learning in the “peso problem.” This autocorrelated forecast errors can generate substantial debt accumulation. Third, it is shown that the assumption of an upward sloping supply function of foreign loans, which is a more realistic assumption for LDCs than the usual perfectly elastic one, offers an alternative to the Uzawa-type utility function for the analysis of asset accumulation in the small open economy framework.

Statistical Arbitrage and Securities Prices

This paper introduces the concept of a statistical arbitrage opportunity (SAO). In a finite-horizon economy, an SAO is a zero-cost trading strategy for which i) the expected payoff is positive, and ii) the conditional expected payoff in each final state of the economy is nonnegative. Unlike a pure arbitrage opportunity, an SAO can have negative payoffs provided that the average payoff in each final state is nonnegative. If the pricing kernel in the economy is path-independent then no SAOs can exist. Furthermore, ruling out SAOs imposes a novel martingale-type restriction on the dynamics of securities prices. The important properties of the restriction are that it 1) is model-free, in the sense that it requires no parametric assumptions about the true equilibrium model, 2) can be tested in samples affected by selection biases, such as the Peso problem, and 3) continues to hold when investors' beliefs are mistaken. The paper argues that one can use the new restriction to empirically resolve the joint hypothesis problem present in the traditional tests of the Efficient Market Hypothesis.

Peso problem explanations for term structure anomalies

We investigate whether term structure anomalies in U.S. data may be due to a generalized peso problem, in which a high-interest-rate regime occurred less frequently in the U.S. sample than was rationally anticipated. We formalize this idea by estimating a regime-switching model of short-term interest rates with data from seven countries. Under the small-sample distributions generated by the model, the expectations hypothesis is rejected. When we allow moderate time variation in term premiums, the term-premium dynamics interact with peso-problem effects to generate small-sample distributions more consistent with the data. Nonetheless, our model cannot fully account for U.S. term structure anomalies.

Scandinavian forward discount bias risk premia

In this article, we investigate expectations concerning Scandinavian exchange rates with the aid of a survey dataset containing market participants’ forecasts of the exchange rates. Our findings indicate that formal tests of forward discount bias do not always result in statistically significant rejections. This contrasts with most of the results reported in the literature, which typically demonstrate sound rejections of unbiasedness. Our tests of rational expectations demonstrate significant irrationality in many, but not all, cases. Alternative explanations of the rejections focus on peso problems and learning about policy changes. Tests of perfect substitutability indicate the significant presence of time-varying risk premia for all pairs of currencies studied, and almost all horizons.

Understanding Asset Values: Stock Prices, Exchange Rates, and the ‘Peso Problem,’

Understanding Asset Values: Stock Prices, Exchange Rates, and the ‘Peso Problem,’

On the Estimation of Euler Equations in the Presence of a Potential Regime Shift

The concept of a peso problem is formalized in terms of a linear Euler equation and a nonlinear marginal model describing the dynamics of the exogenous driving process. It is shown that, using a threshold autoregressive model as a marginal model, it is possible to produce time-varying peso premia. A Monte Carlo method and a method based on the numerical solution of integral equations are considered as tools for computing conditional future expectations in the marginal model. A Monte Carlo study illustrates the poor performance of the generalized method of moment (GMM) estimator in small and even relatively large samples. The poor performance is particularly acute in the presence of a peso problem but is also serious in the simple linear case.

Uncovered interest parity and the peso problem: the Brazilian case

The uncovered interest parity (UIP) test for Brazil is presented from the standpoint of rational expectations hypothesis. The period is January 1984 to October 1998. The econometric tests validate the UIP just for the sub-period January 1990 to June 1994. The result suggests fail with the UIP in the Real Plan, validating the theoretical point proposed by Krasker.

Pouvoir prédictif de la volatilité implicite dans le prix des options de change

La volatilité implicite dans le prix des options est souvent considérée comme la meilleure prévision de la volatilité future. Le pouvoir prédictif de la volatilité implicite « à-la-monnaie » du dollar/ yen, mark/ franc, mark/ peseta et mark/ lire est comparé à celui de volatilités historiques et conditionnelles issues de différentes spécifications garch. Les estimations, sur la période juillet 1995 – avril 1997, montrent que la volatilité implicite des monnaies du Mécanisme de Change Européen n’est pas une prévision sans biais et efficiente de la volatilité future, résultat confirmé par les tests hors échantillon (mai 1997 – mars 1998). Un « problème du peso » semble être à l’origine des biais observés. La volatilité du dollar/ yen au contraire est une prévision sans biais et proche des conditions d’efficience.

The effect of interventions on realignment probabilities

Abstract The expected future change of the exchange rate within its currency band and the expected realignment rate are estimated using the Regime–Switching Model. There exists an unobserved variable st, which characterises the equilibrium state of the expected future change of the exchange rate within its currency band at any time t with certain probabilities. Different values of st correspond to states with high and low risk of realignment, respectively. The probabilities of switching between one regime and another depend on central bank intervention in the foreign exchange market. Daily data on intervention by Norges Bank are used. The data contain relatively few actual realignments, and the sample distribution of realignments may not be representative enough to capture the discrete changes in the exchange rate caused by a non-zero subjective probability of realignment (even when no realignment has in fact taken place). This causes the very well known peso problem in the estimation.

Realignment expectations and the US dollar, 1890–1897: Was there a ‘Peso problem’?

We investigate dollar–sterling exchange rate expectations during the period 1890–1908. We show that the dollar faced a ‘Peso problem’ in that for much of the period financial markets expected it to depreciate against sterling, but this never in fact happened – i.e. expectations were persistently biased. Drawing on the economic history of the period we identify 11 ‘events’ which probably gave rise to realignment expectations. Once the dollar's adherence to the gold standard was settled as a political matter in the 1896 Presidential Election expectations of dollar realignment abruptly subsided and United States interest rates fell relative to British rates.

Technology-Risk-Related Peso Problems in Stock Returns

In the empirical testing of many asset pricing models it is assumed that realised returns are an unbiased estimate of expected returns over the period of study. In this paper it is argued that the occurrence of negative jumps in a firm's future earnings and, consequently, in its stock price, is positively related to the level of network externalities in the firm's product market. If the ex post frequency of these negative jumps in a sample does not equal the ex ante assessed probability of occurrence, the sample is subject to a peso problem. The hypothesis is tested for by regressing the skewness coefficient of a firm's realised stock return distribution on the firm's R&D intensity, i.e. the ratio of the firm's research and development expenditure to its net sales. The empirical results support the technology-related peso problem hypothesis. In samples subject to such a peso problem, the returns are biased up and the variances are biased down.