Giorgio Valente

Monetary Policy Rules, Asset Prices and Exchange Rates

We examine empirically whether asset prices and exchange rates may be admitted into a standard interest rate rule, using data for the United States, the United Kingdom, and Japan since 1979. Asset prices and exchange rates can be employed as information variables for a standard “Taylor-type” rule or as arguments in an augmented interest rate rule. Our empirical evidence, based on measures of the output gap proxied by marginal cost calculations, suggests that monetary policy-makers may use asset prices and exchange rates not only as part of their information set for setting interest rates, but also to set interest rates to offset deviations of asset prices or exchange rates from their equilibrium levels. These results are open to several alternative interpretations.

The Role of Asymmetries and Regime Shifts in the Term Structure of Interest Rates

We examine the relationship between interest rates of different maturities for the US, Germany and Japan over the period 1982-2000, using a general, multivariate vector equilibrium correction modelling framework capable of simultaneously allowing for asymmetric adjustment and regime shifts. This approach has a very general underlying theoretical rationale that allows for time-varying term premia and other short-run deviations from the expectations model of the term structure. The resulting non-linear models provide good in-sample fits, display regime switches closely related to key state variables driving monetary policy decisions and have satisfactory out-of-sample forecasting properties.

The Empirical Failure of the Expectations Hypothesis of the Term Structure of Bond Yields

This paper tests the expectations hypothesis (EH) using US monthly data for bond yields spanning the 1952-2003 sample period and ranging in maturity from 1 month to 10 years. We apply the Lagrange multiplier test developed by Bekaert and Hodrick (2001) and extend it to increase the test power: (a) by introducing economic variables as conditioning information; and (b) by using more than two bond yields in the model and testing the EH jointly on more than one pair of yields. While the conventional bivariate procedure provides mixed results, the more powerful testing procedures suggest rejection of the EH throughout the maturity spectrum examined.

EXCHANGE RATES AND FUNDAMENTALS: FOOTLOOSE OR EVOLVING RELATIONSHIP?

Using novel real-time data on a broad set of economic fundamentals for five major US dollar exchange rates over the recent float, we employ a predictive procedure that allows the relationship between exchange rates and fundamentals to evolve over time in a very general fashion. Our key findings are that: (i) the well-documented weak out-of-sample predictive ability of exchange rate models may be caused by poor performance of model-selection criteria, rather than lack of information content in the fundamentals; (ii) the difficulty of selecting the best predictive model is largely due to frequent shifts in the set of fundamentals driving exchange rates, which can be interpreted as reflecting swings in market expectations over time. However, the strength of the link between exchange rates and fundamentals is different across currencies.

The cost of carry model and regime shifts in stock index futures markets: An empirical investigation

This article examines empirically the dynamic relationship between spot and futures prices in stock index futures markets employing a class of nonlinear, regime‐switching‐vector‐equilibrium‐correction models, which is novel in this context. Using data for the S&P 500 and the FTSE 100 over the post‐1987 crash period, it is shown that a long‐run relationship between spot and futures prices exists, which implies mean reversion of the basis. After providing strong evidence against the hypothesis of linear dynamics in the relationship under investigation, regime‐switching‐vector‐equilibrium‐correction models for spot and futures price movements are developed and shown to capture well the time‐series properties of our data, consistent with a large theoretical and empirical literature.

Federal Funds Rate Prediction

We examine the forecasting performance of a range of time-series models of the daily U.S. effective federal funds (FF) rate recently proposed in the literature. We find that: (1) most of the models and predictor variables considered produce satisfactory one-day-ahead forecasts of the FF rate, (2) the best forecasting model is a simple univariate model where the future FF rate is forecast using the current difference between the FF rate and its target, and (3) combining the forecasts from various models generally yields modest improvements on the best performing model. These results have a natural interpretation and clear policy implications.

The Forward Bias Puzzle and Nonlinearity in Deviations from Uncovered Interest Parity: A New Perspective

We provide empirical evidence that deviations from the uncovered interest rate parity (UIP) condition display significant nonlinearities, which have a natural interpretation consistent with several recent theories based on transactions costs or limits to speculation in the foreign exchange market. This evidence suggests that the forward bias documented in the literature may be less indicative of major inefficiencies in the foreign exchange market than previously thought. Further, Monte Carlo experiments allow us to reconcile our results with the large empirical literature on the forward bias puzzle since we show that, if the true data generating process of UIP deviations were of the nonlinear form we consider, estimation of conventional linear spot-forward regressions would generate the well known anomalies documented in much previous research.

Testing the Economic Value of Asset Return Predictability

Economic value calculations are increasingly used to compare the predictive performance of competing models of asset returns. However, they lack a rigorous way to validate their evidence. This paper proposes a new methodology to test whether utility gains accruing to investors using competing predictive models are equal to zero. Monte Carlo evidence indicates that our testing procedure, that can account for estimation error in the asymptotic variance of the test statistic, provides accurately sized and powerful tests in empirically relevant sample sizes. We apply the test statistics proposed in the paper to revisit the predictability of the US equity premium by means of various predictors.

Asymptotic Inference for Performance Fees and the Predictability of Asset Returns

In this article, we provide analytical, simulation, and empirical evidence on a test of equal economic value from competing predictive models of asset returns. We define economic value using the concept of a performance fee—the amount an investor would be willing to pay to have access to an alternative predictive model used to make investment decisions. We establish that this fee can be asymptotically normal under modest assumptions. Monte Carlo evidence shows that our test can be accurately sized in reasonably large samples. We apply the proposed test to predictions of the U.S. equity premium.

Carry Trades and the Performance of Currency Hedge Funds

We investigate the performance and risk of currency hedge funds using a large and unique consolidated currency hedge fund dataset. We find that a substantial number of hedge funds generate returns that exceed foreign exchange risk premia obtained through carry trades. The best alpha-generating funds exhibit a performance that persists over a one-year horizon. This performance persistence is mostly due to compensation for currency risk-taking as there is no strong evidence of remuneration for active management. The results are robust to biases affecting hedge fund returns, alternative carry trade benchmarks and different methodologies used to correct for sample variability.