Publication:
An adjusted forward curve for spot rate forecasting

Thumbnail Image
Files

Files

An Adjusted Forward Curve for Spot Rate Forecasting.pdf (471.59 KB)
View Statistics
Reference Managers
Mendeley
Indexers
Google Scholar CORE
QR Code
QR Code
Authors

Authors

Sarmiento, Camilo
Abstract (Spanish)
En este documento, proporcionamos ajustes por riesgo de liquidez y crédito a la tasa Libor a plazo para mejorar precisión del tipo forward al pronosticar el tipo Libor a 3 meses. En particular, introducimos la curva adelantada ajustada. (AFC) que modela la actualización en la curva forward de un periodo al siguiente. Un modelado directo del proceso dinámico de La curva directa facilita la especificación de factores de ajuste a la curva directa y subraya el papel de la media. reversión (estacionariedad) en el nexo entre el tipo forward y el tipo spot futuro. Los factores de la AFC que sustentan la El sesgo de la curva directa es estadísticamente relevante con valores de p inferiores a 0,00001. El sesgo alcista en la curva a plazo (es decir, cuando la curva a plazo excede la tasa spot futura esperada) se correlaciona positivamente con la pendiente de la curva de rendimiento en el Modelo AFC. Un sesgo a la baja se correlaciona positivamente con el diferencial de crédito y la utilización de la capacidad industrial. Además, el El efecto de la curva forward instantánea sobre el tipo de cambio spot futuro se atenúa con el tiempo. El poder predictivo de la AFC Sin embargo, el modelo depende de la previsibilidad de los factores subyacentes. Las pruebas indican que todos los factores del modelo AFC tienen un componente de reversión a la media. En general, nuestro modelo anticipa efectivamente movimientos en la curva a plazo que tienden a ceder una mejor previsión del tipo de cambio al contado futuro.
Abstract (English)
In this paper, we provide adjustments for liquidity and credit risk to the forward Libor rate in order to improve accuracy of the forward rate in forecasting the 3-month Libor rate. In particular, we introduce the adjusted forward curve (AFC) that models the update in the forward curve from one period to the next. A direct modeling of the dynamic process of the forward curve facilitates the specification of adjustment factors to the forward curve, and it underscores the role of mean reversion (stationarity) in the nexus between the forward rate and the future spot rate. The AFC factors that underpin the forward curve bias are statistically relevant with p-values that are less than .00001. The upward bias in the forward curve (i.e., when the forward curve exceeds the expected future spot rate) positively correlates with the steepness of the yield curve in the AFC model. A downward bias positively correlates with the credit spread and industrial capacity utilization. Furthermore, the effect of the instantaneous forward curve on the future spot rate tempers off with time. The predictive power of the AFC model, however, hinges on the forecastability of the underlying factors. The testing indicates that all the AFC model factors have a mean reversion component. Overall, our model effectively anticipates movements in the forward curve that tend to yield a better forecast of the future spot rate.
Extent
7 páginas
URI: https://repositorio.escuelaing.edu.co/handle/001/3434
Collections

Collections

AG - Centro de Estudios Económicos
References

Bauer, M. D. and G. D. Rudebusch (2015) “Monetary Policy Expectations at the Zero Lower Bound,” Federal Reserve Bank of San Francisco Working Paper Series

Bernanke, B. S. (1990) "On the Predictive Power of Interest Rates and Interest Rate Spreads," New England Economic Review, 51-68.

Campbell, J. Y., and R. J. Shiller (1991) “Yield Spreads and Interest Rate Movements: A Bird’s Eye View.” Review of Economic Studies, 58, 495–514.

Clark, T. E., and M. W. McCracken (2012) “Advances in Forecast Evaluation,” Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.).

Cochrane, J. H., and M. Piazzesi (2005) “Bond Risk Premia,” American Economic Review 95, 138-160.

Duffee, G. (2013) "Forecasting Interest Rates,” Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.).

Estrella, A., and G. Hardouvelis (1991) “The Term Structure as a Predictor of Real Economic Activity,” Journal of Finance, 46, 555-576.

Fama, E., (1984) "The Information in the Term Structure," Journal of Financial Economics, 13, 509-28

Fama, E and R. Bliss (1987) “The Information in LongMaturity Forward Rates,” American Economic Review, 77, 680-92.

Gibson, R., F. S. Lhabitant,. and D. Talay (2010) “Modeling the Term Structure of Interest Rates: A Review of the Literature, Foundations and Trends” in Finance, 5, p. 1-156.

Gordon, R. J. (1997) ‘The Time-Varying NAIRU and its Implications for Economic Policy.” The Journal of Economic Perspectives 11, 11-32.

Longstaff, F., and E. Schwartz (1995). “A Simple Approach to Valuing Risky Fixed and Floating Rate Exchange Rate,” Journal of Finance, 50, 789-819.

Ludvigson, S. C., and S. Ng, (2009) “Macro Factors in Bond Risk Premia,” Review of Financial Studies 22, 5027-5067.

Malkiel, B. G. (2003) “The Efficient Market Hypothesis and Its Critics.” Journal of Economic Perspectives, 17, 59-82.

Piazzesi, M., and E. Swanson (2004) “Futures Prices as Risk Adjusted Forecasts of Monetary Policy.” NBER Working Paper No. 10547.

Samuelson, P. A. (1965) “Rational Theory of Warrant Pricing,” Industrial Management Review, 6, 13-39.

Shiller, R., Campbell, J. Y., and Schoenholtz, K. L. (1983) "Forward Rates and Future Policy: Interpreting the Term Structure of Interest Rates," Brookings Papers on Economic Activity, 173-217.

Stock, J., and M. Watson (1989) "New Indexes of Coincident and Leading Economic Indicators." NBER Macroeconomics Annual 1989, Olivier J. Blanchard and Stanley Fischer, eds., 351-94. Cambridge, Mass.: The M. I. T. Press.

Wu, J. C., and F. D. Xia (2016) “Measuring the Macroeconomic Impact of Monetary Policy at the Zero Lower Bound.” Journal of Money, Credit and Banking, 48, 253-291.