Home > Research > Publications & Outputs > Density forecast comparisons for stock prices, ...

Electronic data

  • density forecast comparisons paper pure version

    Rights statement: This is the peer reviewed version of the following article: Fan R, Taylor SJ, Sandri M. Density forecast comparisons for stock prices, obtained from high-frequency returns and daily option prices. J Futures Markets. 2018;38:83–103. https://doi.org/10.1002/fut.21859 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002fut.21859/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

    Accepted author manuscript, 1.16 MB, PDF document

    Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License

Links

Text available via DOI:

View graph of relations

Density forecast comparisons for stock prices, obtained from high-frequency returns and daily option prices

Research output: Contribution to journalJournal articlepeer-review

Published

Standard

Density forecast comparisons for stock prices, obtained from high-frequency returns and daily option prices. / Fan, Rui; Taylor, Stephen John; Sandri, Matteo.

In: Journal of Futures Markets, Vol. 38, No. 1, 01.2018, p. 83-103.

Research output: Contribution to journalJournal articlepeer-review

Harvard

APA

Vancouver

Author

Bibtex

@article{05e2060a58544743bd9e306026e1e848,
title = "Density forecast comparisons for stock prices, obtained from high-frequency returns and daily option prices",
abstract = "This paper presents the first comparison of the accuracy of density forecasts for stock prices. Six sets of forecasts are evaluated for DJIA stocks, across four forecast horizons. Two forecasts are risk-neutral densities implied by the Black-Scholes and Heston models. The third set are historical lognormal densities with dispersion determined by forecasts of realized variances obtained from 5-minute returns. Three further sets are defined by transforming risk-neutral and historical densities into real-world densities. The most accurate method applies the risk transformation to the Black-Scholes densities. This method outperforms all others for 87% of the comparisons made using the likelihood criterion.",
author = "Rui Fan and Taylor, {Stephen John} and Matteo Sandri",
note = "This is the peer reviewed version of the following article: Fan R, Taylor SJ, Sandri M. Density forecast comparisons for stock prices, obtained from high-frequency returns and daily option prices. J Futures Markets. 2018;38:83–103. https://doi.org/10.1002/fut.21859 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002fut.21859/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.",
year = "2018",
month = jan,
doi = "10.1002/fut.21859",
language = "English",
volume = "38",
pages = "83--103",
journal = "Journal of Futures Markets",
issn = "0270-7314",
publisher = "Wiley-Liss Inc.",
number = "1",

}

RIS

TY - JOUR

T1 - Density forecast comparisons for stock prices, obtained from high-frequency returns and daily option prices

AU - Fan, Rui

AU - Taylor, Stephen John

AU - Sandri, Matteo

N1 - This is the peer reviewed version of the following article: Fan R, Taylor SJ, Sandri M. Density forecast comparisons for stock prices, obtained from high-frequency returns and daily option prices. J Futures Markets. 2018;38:83–103. https://doi.org/10.1002/fut.21859 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002fut.21859/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

PY - 2018/1

Y1 - 2018/1

N2 - This paper presents the first comparison of the accuracy of density forecasts for stock prices. Six sets of forecasts are evaluated for DJIA stocks, across four forecast horizons. Two forecasts are risk-neutral densities implied by the Black-Scholes and Heston models. The third set are historical lognormal densities with dispersion determined by forecasts of realized variances obtained from 5-minute returns. Three further sets are defined by transforming risk-neutral and historical densities into real-world densities. The most accurate method applies the risk transformation to the Black-Scholes densities. This method outperforms all others for 87% of the comparisons made using the likelihood criterion.

AB - This paper presents the first comparison of the accuracy of density forecasts for stock prices. Six sets of forecasts are evaluated for DJIA stocks, across four forecast horizons. Two forecasts are risk-neutral densities implied by the Black-Scholes and Heston models. The third set are historical lognormal densities with dispersion determined by forecasts of realized variances obtained from 5-minute returns. Three further sets are defined by transforming risk-neutral and historical densities into real-world densities. The most accurate method applies the risk transformation to the Black-Scholes densities. This method outperforms all others for 87% of the comparisons made using the likelihood criterion.

U2 - 10.1002/fut.21859

DO - 10.1002/fut.21859

M3 - Journal article

VL - 38

SP - 83

EP - 103

JO - Journal of Futures Markets

JF - Journal of Futures Markets

SN - 0270-7314

IS - 1

ER -