Ben Tims

Why panel tests of purchasing power parity should allow for heterogeneous mean reversion

Recent studies of purchasing power parity (PPP) use panel tests that fail to take into account heterogeneity in the speed of mean reversion across real exchange rates. In contrast to several other severe restrictions of panel models and tests of PPP, the assumption of homogeneous mean reversion is still widely used and its consequences are virtually unexplored. This paper analyzes the properties of homogeneous and heterogeneous panel unit root testing methodologies. Using Monte Carlo simulation, we uncover important adverse properties of the panel approach that relies on homogeneous estimation and testing. More specifically, power functions are low and assume irregular shapes. Furthermore, homogeneous estimates of the mean reversion parameters exhibit potentially large biases. These properties can lead to misleading inferences on the validity of PPP. Our findings highlight the importance of allowing for heterogeneous estimation when testing for a unit root in panels of real exchange rates.

A Range-Based Multivariate Stochastic Volatility Model for Exchange Rates

In this paper we present a parsimonious multivariate model for exchange rate volatilities based on logarithmic high–low ranges of daily exchange rates. The multivariate stochastic volatility model decomposes the log range of each exchange rate into two independent latent factors, which could be interpreted as the underlying currency specific components. Owing to the empirical normality of the logarithmic range measure the model can be estimated conveniently with the standard Kalman filter methodology. Our results show that our model fits the exchange rate data quite well. Exchange rate news seems to be currency specific and allows identification of currency contributions to both exchange rate levels and exchange rate volatilities.

International Portfolio Choice

The allocation of securities in an investor’s portfolio is one of the oldest and most investigated problems in modern finance. Most financial studies that address the portfolio allocation problem focus on the issue of determining what the optimal allocation should be given a predefined set of securities and a predefined objective function. From a practitioner’s point of view, the resulting allocations may differ considerably from the existing portfolio allocations. It is well known that the computed optimal allocations are not very stable. See, for example, Best and Grauer (1991) and Black and Litterman (1992), who show that a small change in the mean of an asset return will have a huge impact on the optimal allocation of the portfolio but not on its performance. Therefore, a practitioner may be very cautious in deciding to follow the computed optimal allocations.

Asymmetric Extreme Sampling, Developed Versus Emerging Countries, and the Forward Premium Puzzle

We analyse the validity of UIP in a panel of 41 currencies over the time window 1975-2010. We confirm that in general UIP does not hold for developed countries, whereas it does hold for emerging countries. This result is found for various metrics of ‘developed’ and ‘emerging’ countries (IMF country classification, per capita GNI, inflation, inflation volatility). We confirm that UIP may hold in the extremes for developed countries, but this result is only found in the right-hand side tail of interest rate differentials (IRDs). Contrasting with earlier work (that assumed absolute IRDs) our findings suggest an asymmetric relationship. For emerging countries we find an inverse relationship, namely UIP does not hold in the extremes but it does hold in the centre 80% of observations.

Conditioning carry trades: Less risk, more return

textabstractPrior studies show that extreme interest rate dfferentials (IRDs) and high foreign exchange rate (FX) volatility have substantial explanatory power for the validity of UIP. We show that these contemporaneous drivers also have predictive power by implementing a conditional currency carry trade (CT) strategy that excludes regimes for which UIP is likely to hold. Conditioning high FX volatility only, or on both FX volatility and extreme IRDs outperforms the base-case unconditional CT strategy in virtually any of the settings analyzed. Conditioning on very large IRDs only shows mixed findings. Our strategy works best for smaller CT portfolios.