## Abstract

In the previous chapters we have introduced the pricing kernel and the information process as two elementary processes for the characterization of asset prices We will now review the empirical and theoretical literature on asset pricing The implications for the information process and the pricing kernel will be emphasised The aim of this chapter is to summarise the main empirical and theoretical results in order to point out still open questions in asset pricing and, thus, to clarify the contribution of new theoretical results on the pricing of risky assets which are presented in the following chapters Since the analysis in the following chapters will be theoretical, in the literature review theoretical contributions are emphasised.

## Keywords

Cash Flow Risk Aversion Asset Price Option Price Implied Volatility## Preview

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## Notes

- 1.For a review of this topic and a recent study for Germany, see Meyer [143].Google Scholar
- 2.For earlier studies see, Merton [141], Poterba and Summers [157], French, Schwert and Stambaugh [77].Google Scholar
- 3.See, Bollerslev, Engle and Nelson [19].Google Scholar
- 4.For an overview, see also Ghysels, Harvey and Renault [82].Google Scholar
- 5.See for example Ding, Granger and Engle [55].Google Scholar
- 6.See Andersen, Bollerslev, Diebold and Ebens [4], Hentschel [93], Mayhew and Stivers [135] and Tauchen, Zhang and Liu [182].Google Scholar
- 7.LeRoy and Porter [119] and Shleifer [175] started the literature For overviews see Cochrane [40] and Cochrane [41].Google Scholar
- 8.Positive serial correlation in index returns has been confirmed for many countries, see for example Poon and Taylor [158] for the FTSE for the time-period 1965–1989 but also Baily, Stulz and Yen [7] for Asian markets from 1977–1985.Google Scholar
- 9.See for example Froot and Perold [79]Google Scholar
- 10.See also p 32 of this monograph.Google Scholar
- 11.For an overview of earlier studies see for example Fama [63].Google Scholar
- 12.Profitability of momentum strategies is also documented for many different countries (see Rouwenhorst [163] and Rouwenhorst [164] for European and emerging markets) as well as on the basis of international stock market indices instead of individual stocks, see Chan, Hameed and Tong [36].Google Scholar
- 13.For a detailed literature review and a thorough analysis of the German market, see Külpmann [116].Google Scholar
- 14.See also Campbell [31] and Daniel [48] for the power of predictability tests and Cochrane [41] for a discussion of the predictive power of dividend yields.Google Scholar
- 15.See also Stambaugh [178].Google Scholar
- 16.See also Fornari and Mele [69] for a related approach However, they analyze futures written on Italian government bonds.Google Scholar
- 17.Jackwerth [103] addresses several reasons including the question of the appropriate bandwidth in the kernel estimation as well as the different calculation of the expected return distribution See also the discussion in Rosenberg and Engle [160].Google Scholar
- 18.See the discussion on implied pricing kernels in Chap 2 and in Sect 4.2 See also Ait-Sahalia, Wang and Yared [2] who estimate the risk-neutral density from asset returns They apply empirically the Girsanov Theorem.Google Scholar
- 19.Many other articles contributed to the understanding of this relationship See for example also Rubinstein [166] or Breeden and Litzenberger [25].Google Scholar
- 20.More precisely, Bick assumes that this process is governed by a geometric Brownian motion Hence, he uses a process as given by (3.3).Google Scholar
- 21.The index (
*B*) is used for the approach of Bick-He/Leland.Google Scholar - 22.However, as already stated these characterizations are equivalent to the “deterministic function” argument In Appendix A.2 we restate the Lemma 2 of Decamps and Lazrak [51] which shows the equivalence of theses conditions.Google Scholar
- 23.For a derivation see He and Leland [91], pp 598 For a derivation of the 2-dimensional case see also the following paragraph “Viability in two-factor models”.Google Scholar
- 24.Hodges and Carverhill [97] and Hodges and Selby [96] analyze special cases of (4.2) and relate the viability conditions to a non-linear partial differential equation known as Burgers’ equation The advantage of Burgers’ equation is that this partial differential equation is well understood.Google Scholar
- 25.See also Sect 2.2.Google Scholar
- 26.The index (
*PT*) on the variables means that these are variables in the model of Pham and Touzi.Google Scholar - 27.This problem has also been addressed in empirical studies where the pricing kernel projected onto an investment index is analyzed, see Brown and Jackwerth [26] and Rosenberg and Engle [160].Google Scholar
- 28.See for example Pranke and Hax [72], pp 377-380 or Ingersoll [101], pp 104-107.Google Scholar
- 29.See Proposition 2 in Franke [71] For a related result see Fama [62].Google Scholar
- 30.For a discussion of preference assumptions see also Rubinstein [167] or Camara [28].Google Scholar
- 31.A seminal article in discrete time is Samuelson [170] Samuelson shows that under the assumption of risk neutrality forward asset prices follow a martingale It was already recognised soon after the article of Samuelson that the assumption of risk neutrality was essential for this result (see, LeRoy [118] and Ohlson [149]).Google Scholar
- 32.For earlier work on learning in an asset pricing context, see for example Detemple [54] and Timmerman [183].Google Scholar
- 33.For an overview on market microstructure theory see O’Hara [148] Consider also the work of Föllmer and Schweizer [68], Frey [78], Kohlmann and Zhou [112] and He and Wang [92], Wang [186] See Bomfim [20] for a general equilibrium model with heterogeneous expectations.Google Scholar
- 34.For related articles, see Guo [88] and Guo [89].Google Scholar
- 35.See also Gul [87].Google Scholar
- 36.For discussions see for example Brennan [23] and Shleifer [177].Google Scholar