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Sense, nonsense and the S&P500

Author

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  • L. C. G. Rogers

    (University of Cambridge)

Abstract

The theory of financial markets is well developed, but before any of it can be applied there are statistical questions to be answered: Are the hypotheses of proposed models reasonably consistent with what data show? If so, how should we infer parameter values from data? How do we quantify the error in our conclusions? This paper examines these questions in the context of the two main areas of quantitative finance, portfolio selection and derivative pricing. By looking at these two contexts, we get a very clear understanding of the viability of the two main statistical paradigms, classical (frequentist) statistics and Bayesian statistics.

Suggested Citation

  • L. C. G. Rogers, 2018. "Sense, nonsense and the S&P500," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 41(2), pages 447-461, November.
    • Handle: RePEc:spr:decfin:v:41:y:2018:i:2:d:10.1007_s10203-018-0230-3
    DOI: 10.1007/s10203-018-0230-3
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    Cited by:

    1. Giuseppe Orlando & Michele Bufalo, 2021. "Empirical Evidences on the Interconnectedness between Sampling and Asset Returns’ Distributions," Risks, MDPI, vol. 9(5), pages 1-35, May.

    More about this item

    Keywords

    Bayesian statistics; Frequentist statistics; Derivative pricing; Hedging;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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