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Moments by Integrating the Moment-Generating Function

Peter Reinhard Hansen, Chen Tong

arXiv 31 Oct 2024 · Econometrics

arXiv:2410.23587 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We introduce a novel method for obtaining a wide variety of moments of a random variable with a well-defined moment-generating function (MGF). We derive new expressions for fractional moments and fractional absolute moments, both central and non-central moments. The new moment expressions are relatively simple integrals that involve the MGF, but do not require its derivatives. We label the new method CMGF because it uses a complex extension of the MGF and can be used to obtain complex moments. We illustrate the new method with three applications where the MGF is available in closed-form, while the corresponding densities and the derivatives of the MGF are either unavailable or very difficult to obtain.

Citation extraction

34
references
46
in-text mentions
34
distinct cited
2
self-citations
9,509
main-text words

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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Hansen, P. R. and Tong, C (2025) A unifying integral representation of the Gamma function and its reciprocal self0.64422100%
2Meng, X.-L (2005) From unit root to Stein's estimator to Fisher's k statistics: If you have a moment, I can tell you more0.58531100%
3Schürger, K (2002) Laplace transforms and suprema of stochastic processes0.5113233%
4Cressie, N. and Borkent, M (1986) The moment generating function has its moments0.5112250%
5Kawata, T (1972) Fourier analysis in probability theory0.5112250%
6Laue, G (1980) Remarks on the relation between fractional moments and fractional derivatives of characteristic functions0.5112250%
7Barndorff-Nielsen, O. E. and Stelzer, R (2005) Absolute moments of generalized hyperbolic distributions and approximate scaling of normal inverse gaussian lévy processes0.51121100%
8Huang, X. and Oosterlee, C. W (2011) Saddlepoint approximations for expectations and an application to CDO pricing0.51121100%
9Kim, Y. S., Rachev, S. T., Bianchi, M. L., and Fabozzi, F. J (2010) Computing VaR and AVaR in infinitely divisible distributions0.51121100%
10Andersen, T. G., Bollerslev, T., Frederiksen, P., and rregaard Niels… (2010) Continuous-time models, realized volatilities, and testable distributional implications for daily stock returns0.40511100%

Showing the top 10 of 34 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Option Pricing with Time-Varying Volatility Risk Aversion0.00011