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Shape invariant modeling of pricing kernels and risk aversion

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Shape invariant modeling of pricing kernels and risk aversion. / Grith, Maria; Haerdle, Wolfgang; Park, Juhyun.

In: Journal of Financial Econometrics, Vol. 11, No. 2, 2013, p. 370-399.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Grith, M, Haerdle, W & Park, J 2013, 'Shape invariant modeling of pricing kernels and risk aversion', Journal of Financial Econometrics, vol. 11, no. 2, pp. 370-399. https://doi.org/10.1093/jjfinec/nbs019

APA

Grith, M., Haerdle, W., & Park, J. (2013). Shape invariant modeling of pricing kernels and risk aversion. Journal of Financial Econometrics, 11(2), 370-399. https://doi.org/10.1093/jjfinec/nbs019

Vancouver

Grith M, Haerdle W, Park J. Shape invariant modeling of pricing kernels and risk aversion. Journal of Financial Econometrics. 2013;11(2):370-399. https://doi.org/10.1093/jjfinec/nbs019

Author

Grith, Maria ; Haerdle, Wolfgang ; Park, Juhyun. / Shape invariant modeling of pricing kernels and risk aversion. In: Journal of Financial Econometrics. 2013 ; Vol. 11, No. 2. pp. 370-399.

Bibtex

@article{658fa290738c4e1aa3f4a58ec69b256c,
title = "Shape invariant modeling of pricing kernels and risk aversion",
abstract = "Several empirical studies reported that pricing kernels exhibit a common pattern across different markets. The main interest in pricing kernels lies in validating the presence of the peaks and their variability in location among curves. Motivated by this observation we investigate the problem of estimating pricing kernels based on the shape invariant model, a semi-parametric approach used for multiple curves with shape-related nonlinear variation. This approach allows us to capture the common features contained in the shape of the functions and at the same time characterize the nonlinear variability with a few interpretable parameters. These parameters provide an informative summary of the curves and can be used to make a further analysis with macroeconomic variables. Implied risk aversion function and utility function can also be derived. The method is demonstrated with the European options and returns values of the German stock index DAX.",
keywords = "pricing kernals, risk aversion, risk neutral density",
author = "Maria Grith and Wolfgang Haerdle and Juhyun Park",
year = "2013",
doi = "10.1093/jjfinec/nbs019",
language = "English",
volume = "11",
pages = "370--399",
journal = "Journal of Financial Econometrics",
issn = "1479-8409",
publisher = "Oxford University Press",
number = "2",

}

RIS

TY - JOUR

T1 - Shape invariant modeling of pricing kernels and risk aversion

AU - Grith, Maria

AU - Haerdle, Wolfgang

AU - Park, Juhyun

PY - 2013

Y1 - 2013

N2 - Several empirical studies reported that pricing kernels exhibit a common pattern across different markets. The main interest in pricing kernels lies in validating the presence of the peaks and their variability in location among curves. Motivated by this observation we investigate the problem of estimating pricing kernels based on the shape invariant model, a semi-parametric approach used for multiple curves with shape-related nonlinear variation. This approach allows us to capture the common features contained in the shape of the functions and at the same time characterize the nonlinear variability with a few interpretable parameters. These parameters provide an informative summary of the curves and can be used to make a further analysis with macroeconomic variables. Implied risk aversion function and utility function can also be derived. The method is demonstrated with the European options and returns values of the German stock index DAX.

AB - Several empirical studies reported that pricing kernels exhibit a common pattern across different markets. The main interest in pricing kernels lies in validating the presence of the peaks and their variability in location among curves. Motivated by this observation we investigate the problem of estimating pricing kernels based on the shape invariant model, a semi-parametric approach used for multiple curves with shape-related nonlinear variation. This approach allows us to capture the common features contained in the shape of the functions and at the same time characterize the nonlinear variability with a few interpretable parameters. These parameters provide an informative summary of the curves and can be used to make a further analysis with macroeconomic variables. Implied risk aversion function and utility function can also be derived. The method is demonstrated with the European options and returns values of the German stock index DAX.

KW - pricing kernals

KW - risk aversion

KW - risk neutral density

U2 - 10.1093/jjfinec/nbs019

DO - 10.1093/jjfinec/nbs019

M3 - Journal article

VL - 11

SP - 370

EP - 399

JO - Journal of Financial Econometrics

JF - Journal of Financial Econometrics

SN - 1479-8409

IS - 2

ER -