Nonparametric prediction of stock returns with generated bond yields
The question of whether empirical models are able to forecast the equity premium more accurately than the simple historical mean is intensively debated in the nancial literature. The low prediction power is disappointing, even when using nonparametric models that make use of typical predictor variables. Motivated by the co-movement of bond and stock returns, the inclusion of the current bond yield in a prediction model is proposed. This results in a notable improvement in the prediction of stock returns, as measured by the validated R2. Since the current bond yield is unknown, it is predicted in a prior step. The essential point is that the inclusion of the generated bond can be seen as a kind of dimension and complexity reduction that imposes more structure in an appropriate way that circumvents the curse of dimensionality and complexity.
|Date of creation:||Dec 2012|
|Date of revision:|
|Contact details of provider:|| Postal: University of Graz, Universitaetsstr. 15/F4, 8010 Graz, Austria|
Phone: ++43 316 380-3440
Fax: ++43 316 380-9520, 9521
Web page: http://volkswirtschaftslehre.uni-graz.at/
More information through EDIRC
|Order Information:||Web: http://www100.uni-graz.at/vwlwww/forschung/RePEc/|
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Campbell, John Y., 1987.
"Stock returns and the term structure,"
Journal of Financial Economics,
Elsevier, vol. 18(2), pages 373-399, June.
- Allan Timmermann & Massimo Guidolin, 2006.
"An econometric model of nonlinear dynamics in the joint distribution of stock and bond returns,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 21(1), pages 1-22.
- Massimo Guidolin & Allan Timmerman, 2005. "An econometric model of nonlinear dynamics in the joint distribution of stock and bond returns," Working Papers 2005-003, Federal Reserve Bank of St. Louis.
- Lieven Baele & Geert Bekaert & Koen Inghelbrecht, 2007.
"The determinants of stock and bond return comovements,"
Working Paper Research
119, National Bank of Belgium.
- Lieven Baele, 2010. "The Determinants of Stock and Bond Return Comovements," Review of Financial Studies, Society for Financial Studies, vol. 23(6), pages 2374-2428, June.
- Lieven Baele & Geert Bekaert & Koen Inghelbrecht, 2009. "The Determinants of Stock and Bond Return Comovements," NBER Working Papers 15260, National Bureau of Economic Research, Inc.
- Martin Lettau & Stijn Van Nieuwerburgh, 2008.
"Reconciling the Return Predictability Evidence,"
Review of Financial Studies,
Society for Financial Studies, vol. 21(4), pages 1607-1652, July.
- Martin Lettau & Stijn Van Nieuwerburgh, 2006. "Reconciling the Return Predictability Evidence," 2006 Meeting Papers 29, Society for Economic Dynamics.
- Martin Lettau & Stijn Van Nieuwerburgh, 2006. "Reconciling the Return Predictability Evidence," NBER Working Papers 12109, National Bureau of Economic Research, Inc.
- McMillan, David G., 2007. "Non-linear forecasting of stock returns: Does volume help?," International Journal of Forecasting, Elsevier, vol. 23(1), pages 115-126.
- Engsted, Tom & Tanggaard, Carsten, 2001. "The Danish stock and bond markets: comovement, return predictability and variance decomposition," Journal of Empirical Finance, Elsevier, vol. 8(3), pages 243-271, July.
- Stefan Sperlich, 2009. "A note on non-parametric estimation with predicted variables," Econometrics Journal, Royal Economic Society, vol. 12(2), pages 382-395, 07.
- Massimo Guidolin & Stuart Hyde & David McMillan & Sadayuki Ono, 2009.
"Non-linear predictability in stock and bond returns: when and where is it exploitable?,"
2008-010, Federal Reserve Bank of St. Louis.
- Guidolin, Massimo & Hyde, Stuart & McMillan, David & Ono, Sadayuki, 2009. "Non-linear predictability in stock and bond returns: When and where is it exploitable?," International Journal of Forecasting, Elsevier, vol. 25(2), pages 373-399.
- Valkanov, Rossen, 2003. "Long-horizon regressions: theoretical results and applications," Journal of Financial Economics, Elsevier, vol. 68(2), pages 201-232, May.
- Nielsen, Jens Perch & Sperlich, Stefan, 2003. "Prediction of Stock Returns: A New Way to Look at It," ASTIN Bulletin: The Journal of the International Actuarial Association, Cambridge University Press, vol. 33(02), pages 399-417, November.
- Vieu, Philippe, 1994. "Choice of regressors in nonparametric estimation," Computational Statistics & Data Analysis, Elsevier, vol. 17(5), pages 575-594, June.
- Dell'Aquila, Rosario & Ronchetti, Elvezio, 2006. "Stock and bond return predictability: the discrimination power of model selection criteria," Computational Statistics & Data Analysis, Elsevier, vol. 50(6), pages 1478-1495, March.
- Mammen, Enno & MartÃnez Miranda, MarÃa Dolores & Nielsen, Jens Perch & Sperlich, Stefan, 2011. "Do-Validation for Kernel Density Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 106(494), pages 651-660.
- Kim, Tae Yoon & Park, Byeong U. & Moon, Myung Sang & Kim, Chiho, 2009. "Using bimodal kernel for inference in nonparametric regression with correlated errors," Journal of Multivariate Analysis, Elsevier, vol. 100(7), pages 1487-1497, August.
- Rapach, David E. & Wohar, Mark E. & Rangvid, Jesper, 2005. "Macro variables and international stock return predictability," International Journal of Forecasting, Elsevier, vol. 21(1), pages 137-166.
When requesting a correction, please mention this item's handle: RePEc:grz:wpaper:2012-10. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael Scholz)
If references are entirely missing, you can add them using this form.