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26 - Excess Returns: The Recent Literature – I

from Part VI - Excess Returns

Published online by Cambridge University Press:  25 May 2018

Riccardo Rebonato
Affiliation:
Pacific Investment Management Company (PIMCO), California
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Summary

It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.

Sir Arthur Conan Doyle, “A Scandal in Bohemia”, The Adventures of Sherlock Holmes

The experiments are so sophisticated these days that they can match the theory almost perfectly.

A former colleague at the high-flux research nuclear reactor at the Institut Laue Langevin (Grenoble), commenting on the power of the local experimental facilities.

THE PURPOSE OF THIS CHAPTER

We have presented in the previous chapter the results of some basic regressions to explain excess returns. We looked at nominal and real excess returns. What we found is broadly in line with earlier work by Fama and Bliss (1987) and Campbell and Shiller (1991) (discussed in Section 26.2), but seems to be at odds with the more recent findings. To understand the origin of these differences, in this chapter we look in considerable detail at the results obtained by Cochrane and Piazzesi (2005). We do so because their work has become the standard against which subsequent regression studies (such as those by Cieslak and Povala (2010a, 2010b), Ludvigson and Ng (2009), and Radwanski (2010) examined in the next chapter) have pitted themselves. Once these literature results have been presented, we will try in Chapter 28 to reconcile, to the extent possible, the traditional, slope-based, results (we include ours in the traditional class) with the new findings.

We devote a lot of time to understanding the empirical findings well, because we think that a solid anchor with empirical reality is essential, lest we get carried away by the beauty of the models and confuse what the world should look like (if the models were true) with how the world actually behaves. Hence the first quote.

Furthermore, newer-generation affine models are endowed with such richness and flexibility that they can now perform tricks and stunts totally beyond the capabilities of the early-generation models. This is good and bad, as richer models must be kept in check by correspondingly richer and more ‘constraining’ empirical evidence. Hence the second quote.

Type
Chapter
Information
Bond Pricing and Yield Curve Modeling
A Structural Approach
, pp. 473 - 496
Publisher: Cambridge University Press
Print publication year: 2018

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