Regime Shifts in Asian Equity and Real Estate Markets

This paper applies a new statistical technology for identifying regime shifts to analyze recent data on real estate and equity markets in eight developing Far Eastern countries in the 1992–1998 time period. We find that regime shifts in volatility occur in the summer of 1997; however, most of the regime shifts in returns occur in the spring of 1998. While the clustering of regime breaks does not seem to follow any obvious pattern, the country's exposure to trade and firm leverage are important. An analysis of Granger causality suggests that, in most cases, equity returns cause real estate returns but the converse is not true. We also find two-way causality in volatility, suggesting that a common factor drives volatility in these markets. Finally, we provide evidence that the regime shifts generally imply higher relative risk for real estate securities after the estimated breaks.     

Model Uncertainty, Optimal Monetary Policy and the Preferences of the Fed

Monetary policy in the US is characterized by a substantial degree of inertia. While in principle this may well be the outcome of an optimizing central bank behaviour, the ability of any derived policy rule to match the data relies on so large weights for interest rate smoothing into policy makers' preferences as to be theoretically flawed. In this paper we investigate whether such a puzzle can be interpreted as resulting from the concern of monetary authorities for potential misspecifications of the macroeconomic dynamics. Accordingly, we propose a novel thick modelling approach that incorporates model uncertainty into the identification of central bank's preferences. The thick robust policy rule shows the kind of smoothness observed in the data without resorting to implausible values for the preference parameters.     

Strategic Certification and Provision of Quality

We study the effect of the presence of a certification intermediary in an environment where information asymmetries are particularly severe. The intermediary improves the information that buyers have about quality. This in turn increases the incentives that the seller has to provide high-quality goods. Efficiency is increased by the presence of the intermediary, but quality is underprovided in equilibrium relative to full information. The intermediary can implement the optimal policy in many ways. The amount of information revealed ranges from full disclosure to partial, noisy disclosure.     

A comparison of different trading protocols in an agent-based market

We compare price dynamics of different market protocols (batch auction, continuous double auction and dealership) in an agent-based artificial exchange. In order to distinguish the effects of market architectures alone, we use a controlled environment where allocative and informational issues are neglected and agents do not optimize or learn. Hence, we rule out the possibility that the behavior of traders drives the price dynamics. Aiming to compare price stability and execution quality in broad sense, we analyze standard deviation, excess kurtosis, tail exponent of returns, volume, perceived gain by traders and bid-ask spread. Overall, a dealership market appears to be the best candidate, generating low volume and volatility, virtually no excess kurtosis and high perceived gain.     

Forecasting recovery rates on non-performing loans with machine learning

We compare the performance of a wide set of regression techniques and machine-learning algorithms for predicting recovery rates on non-performing loans, using a private database from a European debt collection agency. We find that rule-based algorithms such as Cubist, boosted trees, and random forests perform significantly better than other approaches. In addition to loan contract specificities, predictors that refer to the bank recovery process — prior to the portfolio’s sale to a debt collector — are also shown to enhance forecasting performance. These variables, derived from the time series of contacts to defaulted clients and client reimbursements to the bank, help all algorithms better identify debtors with different repayment ability and/or commitment, and in general those with different recovery potential.     

Short-memory equilibrium in stochastic overlapping generations economies

In stochastic OLG exchange economies, we show that short-memory equilibria—the natural extension from deterministic economies of steady states, low-order cycles, or finite state-space stationary sunspots equilibria—fail to exist generically in utilities. As a result, even with independent and identically distributed exogenous shocks there is serial correlation in endogenous economic variables in equilibrium. This arises even if utilities are time-separable, some goods inferior, and there are no technological lags. Hence, the origins of economic fluctuations can be traced only to the demographic structure of a heterogeneous agent, multiple-good economy.     

Revisiting Savage in a conditional world

Summary. I present an axiomatization of subjective expected utility and Bayesian updating in a conditional decision problem. This result improves our understanding of the Bayesian standard from two perspectives: 1) it uses a set of axioms which are weak and intuitive; 2) it provides a formal proof to results on the relation between dynamic consistency, expected utility and Bayesian updating which have never been explicitly proved in a fully subjective framework. Received: December 1, 2000; revised version: February 26, 2001