Previous assessments of nominal exchange rate determination have focused upon a narrow set of models typically of the 1970's vintage. The canonical papers in this literature are by Rogoff (1983, 1988), who examined monetary and portfolio balance models. Succeeding works by Mark (1995) and Chinn and Meese (1995) focused on similar models. In this paper we re-assess exchange rate prediction using a wider set of models that have been proposed in the last decade: interest rate parity, productivity based models, and "behavioral equilibrium exchange rate" models. The performance of these models is compared against a benchmark model -the Dornbusch-Frankel sticky price monetary model. The models are estimated in error correction and first-difference specifications. Rather than estimating the cointegrating vector over the entire sample and treating it as part of the ex ante information set as is commonly done in the literature, we recursively update the cointegrating vector, thereby generating true ex ante forecasts. We examine model performance at various forecast horizons (1 quarter, 4 quarters, 20 quarters) using differing metrics (mean squared error, direction of change), as well as the Aconsistency@ test of Cheung and Chinn (1998). No model consistently outperforms a random walk, by a mean squared error measure; however, along a direction-of-change dimension, certain structural models do outperform a random walk with statistical significance. Moreover, one finds that these forecasts are cointegrated with the actual values of exchange rates, although in a large number of cases, the elasticity of the forecasts with respect to the actual values is different from unity. Overall, model/specification/currency combinations that work well in one period will not necessarily work well in another period.

and conference participants at CES-ifo Venice Summer Institute conference on "Exchange Rate Modeling" for helpful comments, and Jeannine Bailliu, Gabriele Galati and Guy Meredith for providing data. The financial support of faculty research funds of the University of California, Santa Cruz is gratefully acknowledged. The views expressed herein are those of the authors and not necessarily those of the International Monetary Fund or the National Bureau of Economic Research.

This Working Paper should not be reported as representing the views of the IMF. The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate. This paper generalizes a market-based indicator for financial sector surveillance using a multifactor latent structure in the determination of the default probabilities of an n th-todefault credit default swap (CDS) basket of large complex financial institutions (LCFIs). To estimate the multifactor latent structure, we link the market risk (the covariance of the LCFIs' equity) to credit risk (the default probability of the CDS basket) in a coherent manner. In addition, to analyze the response of the probabilities of default to changing macroeconomic conditions, we run a stress test by generating shocks to the latent multifactor structure. The results unveil a rich set of default probability dynamics and help in identifying the most relevant sources of risk. We anticipate that this approach could be of value to financial supervisors and risk managers alike.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may No 2018 / February 2017 AbstractPrevious assessments of nominal exchange rate determination, following have focused upon a narrow set of models. Cheung et al. (2005) augmented the usual suspects with productivity based models, and "behavioral equilibrium exchange rate" models, and assessed performance at horizons of up to 5 years. In this paper, we further expand the set of models to include Taylor rule fundamentals, yield curve factors, and incorporate shadow rates and risk and liquidity factors. The performance of these models is compared against the random walk benchmark. The models are estimated in error correction and firstdifference specifications. We examine model performance at various forecast horizons (1 quarter, 4 quarters, 20 quarters) using differing metrics (mean squared error, direction of change), as well as the "consistency" test of Cheung and Chinn (1998). No model consistently outperforms a random walk, by a mean squared error measure, although purchasing power parity does fairly well. Moreover, along a direction-of-change dimension, certain structural models do outperform a random walk with statistical significance. While one finds that these forecasts are cointegrated with the actual values of exchange rates, in most cases, the elasticity of the forecasts with respect to the actual values is different from unity. Overall, model/specification/currency combinations that work well in one period will not necessarily work well in another period Nontechnical SummaryIn an era characterized by increasingly integrated national economies, the exchange rate remains the key relative price in open economies. As such, a great deal of attention has been lavished upon predicting the behavior of this variable. Unfortunately, it is unclear how much success there has been on this front. Beginning with the work of , many economists have evaluated exchange rate models using a horse race approach: see which model performs the best in predicting the actual level of the exchange rate when it's assumed the determinants are assumed to be known. Earlier studies focused on a fairly narrow set of models, including ones where interest rate differentials, monetary factors, and foreign debt, mattered. In more recent studies (Cheung et al., 2005) this set of models were augmented by those including a role for price levels, for productivity growth, and a composite specification incorporating several different channels whereby...

We re-assess exchange rate prediction using a wider set of models that have been proposed in the last decade: interest rate parity, productivity based models, and a composite specification. The performance of these models is compared against two reference specifications e purchasing power parity and the sticky-price monetary model. The models are estimated in first-difference and error correction specifications, and model performance evaluated at forecast horizons of 1, 4 and 20 quarters, using the mean squared error, direction of change metrics, and the ''consistency'' test of Cheung and Chinn [1998. Integration, cointegration, and the forecast consistency of structural exchange rate models. Journal of International Money and Finance 17, 813e830]. Overall, model/specification/currency combinations that work well in one period do not necessarily work well in another period.