Systematic risk in the biopharmaceutical sector: a multiscale approach

Gazi Salah Uddin; Muhammad  Yahya; Stelios Bekiros; Ranadeva Jayasekera; Gerhard Kling

doi:10.1007/s10479-021-04402-8

Systematic risk in the biopharmaceutical sector: a multiscale approach

Gazi Salah Uddin, Muhammad Yahya^* (Corresponding Author), Stelios Bekiros, Ranadeva Jayasekera, Gerhard Kling

^*Corresponding author for this work

Accountancy & Finance, Finance

Research output: Contribution to journal › Article › peer-review

Abstract

It is well documented that the biopharmaceutical sector has exhibited weak financial returns, contributing to underinvestment. Innovations in the industry carry high risks; however, an analysis of systematic risk and return compared to other asset classes is missing. This paper investigates the time-frequency interconnectedness between stocks in the biotech sector and ten asset classes using daily cross-country data from 1995 to 2019. We capture investors' heterogeneous investment horizons by decomposing time series according to frequencies. Using a maximal overlap discrete wavelet transform (MODWT)
and a dynamic conditional correlation (DCC)-Student-t copula, diversification potentials are revealed, helping investors to reap the benefits of investing in biotech. Our findings indicate that the underlying assets exhibit nonlinear asymmetric behavior that strengthens during periods of turmoil.

Original language	English
Pages (from-to)	243–266
Number of pages	24
Journal	Annals Of Operations Research
Volume	330
Early online date	21 Nov 2021
DOIs	https://doi.org/10.1007/s10479-021-04402-8
Publication status	Published - 1 Nov 2023

Bibliographical note

Acknowledgements: Authors are thankful to the Trinity Business School, University of Dublin for the academic facilities provided to Gazi S. Uddin during his stay at Trinity where important parts of this research work was completed.Gazi Salah Uddin is thankful for the Visiting Fellow Programme Grant provided by the
University of Jyväskylä, Finland.

Funding: Open Access funding provided by Inland Norway University Of Applied Sciences.

Data Availability Statement

Data availability: The data that support the findings of this study are available from Datastream (published by Thomson Reuters Eikon), but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are, however, available from the authors upon reasonable request and with the permission of Thomson Reuters. The MATLAB code that replicates our findings is available from the authors.

Keywords

OR in medicine
biotech
time-varying copulas
wavelets
risk management

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Cite this

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abstract = "It is well documented that the biopharmaceutical sector has exhibited weak financial returns, contributing to underinvestment. Innovations in the industry carry high risks; however, an analysis of systematic risk and return compared to other asset classes is missing. This paper investigates the time-frequency interconnectedness between stocks in the biotech sector and ten asset classes using daily cross-country data from 1995 to 2019. We capture investors' heterogeneous investment horizons by decomposing time series according to frequencies. Using a maximal overlap discrete wavelet transform (MODWT)and a dynamic conditional correlation (DCC)-Student-t copula, diversification potentials are revealed, helping investors to reap the benefits of investing in biotech. Our findings indicate that the underlying assets exhibit nonlinear asymmetric behavior that strengthens during periods of turmoil.",

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Systematic risk in the biopharmaceutical sector: a multiscale approach

Abstract

Bibliographical note

Data Availability Statement

Keywords

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