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Begin New Search Topic International Relations Author Jonathan H. Wright

1. Uncovered Interest Parity: It Works, But Not For Long

Author:
Jonathan H. Wright and Alain P. Chaboud
Publication Date:
01-2003
Content Type:
Working Paper
Institution:
Board of Governors of the Federal Reserve System
Abstract:
The failure of uncovered interest parity can be ascribed to the existence of a risk premium. The size of this risk premium may shrink to zero over sufficiently small intervals of time. In contrast, because no interest is paid on intradaily positions and interest is instead paid discretely at the point when a position is rolled over from one day to the next, the size of the interest differential remains fixed over any interval that covers the time of the discrete interest payment. This is true no matter how short that interval is. Using a large dataset of high frequency exchange rate data, we run uncovered interest parity regression over different time intervals. We replicate the rejection of the uncovered interest parity hypothesis with daily data, but find results that are consistently much more supportive of the uncovered interest parity hypothesis over short windows of intradaily data that span the time of the discrete interest payment.
Topic:
Conflict Prevention, International Relations, Economics, and International Trade and Finance

2. The High-Frequency Response of Exchange Rates and Interest Rates to Macroeconomic Announcements

Author:
John H. Rogers, Jonathan H. Wright, Jon Faust, and Shing-Yi B. Wang
Publication Date:
10-2003
Content Type:
Working Paper
Institution:
Board of Governors of the Federal Reserve System
Abstract:
Many recent papers have studied movements in stock, bond, and currency prices over short windows of time around macro announcements. This paper adds to the announcement effects literature in two ways. First, we study the joint announcement effects across a broad range of assets--exchange rates and U.S. and foreign term structures. In order to evaluate whether the joint effects can be reconciled with conventional theory, we interpret the joint movements in light of uncovered interest rate parity or changes in risk premia. For several real macro announcements, we find that a stronger than expected release appreciates the dollar today, but that it must either (i) lower the relative risk premium for holding foreign currency rather than dollars, or (ii) imply considerable future expected dollar depreciation. The latter implies an overshooting behavior akin to that described by Dornbusch (1976). Second, we use a longer span of high frequency data than has been common in announcement work. A longer span of high frequency data contributes to the precision of our estimates and allows us to explore the possibility that the effects of macro surprises on asset prices have varied over time. We find evidence, for example, that PPI releases had a larger effect on U.S. interest rates before about 1992 than subsequently.
Topic:
International Relations, Economics, Government, and International Trade and Finance
Political Geography:
United States

3. Forecasting U.S. Inflation by Bayesian Model Averaging

Author:
Jonathan H. Wright
Publication Date:
09-2003
Content Type:
Working Paper
Institution:
Board of Governors of the Federal Reserve System
Abstract:
Recent empirical work has considered the prediction of inflation by combining the information in a large number of time series. One such method that has been found to give consistently good results consists of simple equal weighted averaging of the forecasts over a large number of different models, each of which is a linear regression model that relates inflation to a single predictor and a lagged dependent variable. In this paper, I consider using Bayesian Model Averaging for pseudo out-of-sample prediction of US inflation, and find that it gives more accurate forecasts than simple equal weighted averaging. This superior performance is consistent across subsamples and inflation measures. Meanwhile, both methods substantially outperform a naive time series benchmark of predicting inflation by an autoregression.
Topic:
International Relations, Economics, and International Trade and Finance
Political Geography:
United States

4. Bayesian Model Averaging and Exchange Rate Forecasts

Author:
Jonathan H. Wright
Publication Date:
09-2003
Content Type:
Working Paper
Institution:
Board of Governors of the Federal Reserve System
Abstract:
Exchange rate forecasting is hard and the seminal result of Meese and Rogoff (1983) that the exchange rate is well approximated by a driftless random walk, at least for prediction purposes, has never really been overturned despite much effort at constructing other forecasting models. However, in several other macro and financial forecasting applications, researchers in recent years have considered methods for forecasting that combine the information in a large number of time series. One method that has been found to be remarkably useful for out-of-sample prediction is simple averaging of the forecasts of different models. This often seems to work better than the forecasts from any one model. Bayesian Model Averaging is a closely related method that has also been found to be useful for out-of-sample prediction. This starts out with many possible models and prior beliefs about the probability that each model is the true one. It then involves computing the posterior probability that each model is the true one, and averages the forecasts from the different models, weighting them by these posterior probabilities. This is effectively a shrinkage methodology, but with shrinkage over models not just over parameters. I apply this Bayesian Model Averaging approach to pseudo-out-of-sample exchange rate forecasting over the last ten years. I find that it compares quite favorably to a driftless random walk forecast. Depending on the currency-horizon pair, the Bayesian Model Averaging forecasts sometimes do quite a bit better than the random walk benchmark (in terms of mean square prediction error), while they never do much worse. The forecasts generated by this model averaging methodology are however very close to (but not identical to) those from the random walk forecast.
Topic:
International Relations, Economics, and International Trade and Finance
Political Geography:
United States