creator: Barkoulas, John
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An Empirical Investigation of Risk Premia in the Foreign Currency Futures Basis
description- – Significant time-varying risk premia exist in the foreign currency futures basis, and these risk premia are meaningfully correlated with common macroeconomic risk factors from equity and bond markets. The stock index dividend yield and the bond default and term spreads in the U.S. markets help forecast the risk premium component of the foreign currency futures basis. The specific source of risk matters, but the relationships are robust across currencies. The currency futures basis is positively associated with the dividend yield and negatively associated with the spread variables. These correlations cannot be attributed to the expected spot price change component of the currency futures basis, thus establishing the presence of a time-varying risk premium component in the currency futures basis.
- – WP281
- – 1996-01-01
- – application/pdf
Fractional Differencing Modeling and Forecasting of Eurocurrency Deposit Rates
description- – We investigate the low frequency properties of three- and six-month rates for Eurocurrency deposits denominated in eight major currencies with specific emphasis on fractional dynamics. Using the fractional integration testing procedure suggested by Geweke and Porter-Hudak (1983), we find that several of the Eurocurrency deposit rates are fractionally integrated processes with long memory. These findings have important implications for econometric modeling, forecasting, and cointegration testing of Eurocurrency rates.
- – WP317
- – 1996-10-01
- – application/pdf
Fractional Cointegration Analysis of Long Term International Interest Rates
description- – DeGennaro, Kunkel, and Lee (1994) studied the long run dynamics of a system of long term interest rates of five industrialized countries by means of sophisticated cointegration methods. They found little evidence in support of the cointegration hypothesis, thus concluding that a separate set of fundamentals drives the dynamics of each of the individual long term interest rate series. In this study, we extend their analysis by exploring the possibility of very slow mean reverting dynamics (fractional cointegration) in the system of the five long term interest rates. We use the GPH test as our testing methodology for fractional integration and cointegration. Through rigorous investigation of the full system of the five long term interest rate series and its various subsystems, we provide evidence that the error correction term follows a fractionally integrated process with long memory, that is, it is mean reverting, though not covariance stationary. Despite significant persistence in the short run, a shock to the system of long term interest rates eventually dissipates so that an equilibrium relationship prevails in the long run.
- – WP315
- – 1996-10-01
- – application/pdf
Long Term Dependence in Stock Returns
description- – This paper investigates the presence of fractal dynamics in stock returns. We improve upon existing literature in two ways: i) instead of rescaled-range analysis, we use the more efficient semi-nonparametric procedure suggested by Geweke and Porter-Hudak (GPH, 1983), and ii) to ensure robustness, we apply the GPH test to a variety of aggregate and sectoral stock indices and individual companies' stock returns series at both daily and monthly frequencies. Our results indicate that fractal structure is not exhibited by stock indices, but it may characterize the behavior of some individual stock returns series.
- – WP314
- – 1996-04-01
- – application/pdf
Nearest-Neighbor Forecasts of U.S. Interest Rates
description- – We employ a nonlinear, nonparametric method to model the stochastic behavior of changes in several short and long term U.S. interest rates. We apply a nonlinear autoregression to the series using the locally weighted regression (LWR) estimation method, a nearest-neighbor method, and evaluate the forecasting performance with a measure of root mean square error. We compare the forecasting performance of the nonparametric fit to the performance of two benchmark linear models: an autoregressive model and a random-walk-with-drift model. The nonparametric model exhibits greater out-of-sample forecast accuracy than that of the linear predictors for most U.S. interest rate series. The improvements in forecasting accuracy are statistically significant and robust. This evidence establishes the presence of significant nonlinear mean predictability in U.S. interest rates, as well as the usefulness of the LWR method as a modeling strategy for these benchmark series.
- – WP313
- – 1996-02-01
- – application/pdf
Fractional Monetary Dynamics
description- – We test for fractional dynamics in U.S. monetary series, their various formulations and components, and velocity series. Using the spectral regression method, we find evidence of a fractional exponent in the differencing process of the monetary series (both simple-sum and Divisia indices), in their components (with the exception of demand deposits, savings deposits, overnight repurchase agreements, and term repurchase agreements), and the monetary base and money multipliers. No evidence of fractional behavior is found in the velocity series. Granger's (1980) aggregation hypothesis is evaluated and implications of the presence of fractional monetary dynamics are drawn.
- – 1998-01-01
- – application/pdf
Fractional Monetary Dynamics
description- – We test for fractional dynamics in U.S. monetary series, their various formulations and components, and velocity series. Using the spectral regression method, we find evidence of a fractional exponent in the differencing process of the monetary series (both simple-sum and Divisia indices), in their components (with the exception of demand deposits, savings deposits, overnight repurchase agreements, and term repurchase agreements), and the monetary base and money multipliers. No evidence of fractional behavior is found in the velocity series. Granger's (1980) aggregation hypothesis is evaluated and implications of the presence of fractional monetary dynamics are drawn.
- – WP321
- – 1998-01-01
- – application/pdf
A Nonparametric Investigation of the 90-Day T-Bill Rate
description- – We employ a nonlinear, nonparametric method to model the stochastic behavior of changes in the 90-day U.S. T-bill rate. The estimation technique is locally weighted regression (LWR), a nearest-neighbor method, and the forecasting criteria are the root mean square error (RMSE) and mean absolute deviation (MAD) measures. We compare the forecasting performance of the nonparametric fit to the performance of two benchmark linear models: an autoregressive model and a random-walk-with-drift model. The nonparametric fit results in significant improvements in forecasting accuracy as compared to benchmark linear models both in-sample and out-of-sample, thus establishing the presence of substantial nonlinear mean predictability of changes in the 90-day T-bill rate.
- – WP320
- – 1997-05-01
- – application/pdf
Long Memory and Forecasting in Euroyen Deposit Rates
description- – We test for long memory in 3- and 6-month daily returns series on Eurocurrency deposits denominated in Japanese yen (Euroyen). The fractional differencing parameter is estimated using the spectral regression method. The conflicting evidence obtained from the application of tests against a unit root as well as tests against stationarity provides the motivation for testing for fractional roots. Significant evidence of positive long-range dependence is found in the Euroyen returns series. The estimated fractional models result in dramatic out-of-sample forecasting improvements over longer horizons compared to benchmark linear models, thus providing strong evidence against the martingale model.
- – WP361
- – 1997-02-01
- – application/pdf
Long-Memory Forecasting of U.S. Monetary Indices
description- – Several studies have tested for long-range dependence in macroeconomic and financial time series but very few have assessed the usefulness of long-memory models as forecast generating mechanisms. This study tests for fractional differencing in the U.S. monetary indices (simple sum and divisia) and compares the out-of-sample fractional forecasts to benchmark forecasts. The long-memory parameter is estimated using RobinsonÍs Gaussian semiparametric and multivariate log-periodogram methods. The evidence amply suggests that the monetary series possess a fractional order between one and two. Fractional out-of-sample forecasts are consistently more accurate (with the exception of the M3 series) than benchmark autoregressive forecasts but the forecasting gains are not generally statistically significant. In terms of forecast encompassing, the fractional model encompasses the autoregressive model for the divisia series but neither model encompasses the other for the simple sum series.
- – 2003-05-01
- – application/pdf
Dynamics of Intra-EMS Interest Rate Linkages
description- – A number of previous studies have questioned the dominant role of Germany within the EMS. These conclusions are often based on empirical findings that interest rates of member countries of the EMS are not affected by German interest rates, even in the long run. In this study we establish evidence to the contrary by demonstrating that intra-EMS interest rate differentials (vis-a-vis Germany) exhibit mean-reverting behavior (a necessary but not sufficient condition for German dominance) characterized by long-memory dynamics. In a system incorporating six EMS countries and one non-EMS country (the U.S.), estimates from a fractional error correction model suggest the presence of short-run intra-EMS monetary-policy interdependencies, but they validate the German Dominance Hypothesis in the long run.
- – WP492
- – 2004-05-04
- – application/pdf
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