Steven L. Beach

Personal Details

First Name:	Steven
Middle Name:	L.
Last Name:	Beach
Suffix:
RePEc Short-ID:	pbe320
	College of Business Mesa Building 2202 University of Texas Permian Basin Odessa, TX 79762-0001
	432-552-2173
Terminal Degree:	1999 College of Business and Economics; Washington State University (from RePEc Genealogy)

Affiliation

School of Business
University of Texas of the Permian Basin

Odessa, Texas (United States)
http://bus.utpb.edu/
RePEc:edi:sbtpbus (more details at EDIRC)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Articles

1. Alper Gormus & Saban Nazlioglu & Steven L. Beach, 2023. "Environmental, Social, and Governance Considerations in WTI Financialization through Energy Funds," JRFM, MDPI, vol. 16(4), pages 1-17, April.

   Cited by:

   1. Alper Gormus & Saban Nazlioglu & Elif Gormus, 2024. "ESG impact on oil and natural gas financialization through price transmission," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 48(3), pages 685-707, September.

2. Beach, Steven L., 2011. "Semivariance decomposition of country-level returns," International Review of Economics & Finance, Elsevier, vol. 20(4), pages 607-623, October.

   Cited by:

   1. Sree Vinutha Venkataraman, 2023. "A remark on mean‐semivariance behaviour: Downside risk and capital asset pricing," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2683-2695, July.
   2. Tsai, Hsiu-Jung & Chen, Ming-Chi & Yang, Chih-Yuan, 2014. "A time-varying perspective on the CAPM and downside betas," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 440-454.
   3. Philip A. Horvath & Amit K. Sinha, 2017. "Asymmetric reaction is rational behavior," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 41(1), pages 160-179, January.
   4. Manuel Monge & Luis A. Gil-Alana, 2020. "The Lithium Industry and Analysis of the Beta Term Structure of Oil Companies," Risks, MDPI, vol. 8(4), pages 1-17, December.
   5. Richard T. Baillie & Fabio Calonaci & George Kapetanios, 2019. "Hierarchical Time Varying Estimation of a Multi Factor Asset Pricing Model," Working Papers 879, Queen Mary University of London, School of Economics and Finance.
   6. Lajos Horváth & William Pouliot & Shixuan Wang, 2017. "Detecting at-Most-m Changes in Linear Regression Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(4), pages 552-590, July.

3. Steven Beach & Alexei Orlov, 2007. "An application of the Black–Litterman model with EGARCH-M-derived views for international portfolio management," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 21(2), pages 147-166, June.

   Cited by:

   1. Erindi Allaj, 2020. "The Black–Litterman model and views from a reverse optimization procedure: an out-of-sample performance evaluation," Computational Management Science, Springer, vol. 17(3), pages 465-492, October.
   2. Erindi Allaj, 2013. "The Black–Litterman model: a consistent estimation of the parameter tau," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 27(2), pages 217-251, June.
   3. Han, Yingwei & Li, Jie, 2023. "The impact of global economic policy uncertainty on portfolio optimization: A Black–Litterman approach," International Review of Financial Analysis, Elsevier, vol. 86(C).
   4. Shea D. Chen & Andrew E. B. Lim, 2020. "A Generalized Black–Litterman Model," Operations Research, INFORMS, vol. 68(2), pages 381-410, March.
   5. Becker, Franziska & Gürtler, Marc, 2008. "Quantitative forecast model for the application of the Black-Litterman approach," Working Papers IF27V2, Technische Universität Braunschweig, Institute of Finance.
   6. Harris, Richard D F & Stoja, Evarist & Tan, Linzhi, 2016. "The dynamic Black-Litterman approach to asset allocation," Bank of England working papers 596, Bank of England.
      • Harris, Richard D.F. & Stoja, Evarist & Tan, Linzhi, 2017. "The dynamic Black–Litterman approach to asset allocation," European Journal of Operational Research, Elsevier, vol. 259(3), pages 1085-1096.
   7. Barua, Ronil & Sharma, Anil K., 2023. "Using fear, greed and machine learning for optimizing global portfolios: A Black-Litterman approach," Finance Research Letters, Elsevier, vol. 58(PC).
   8. Patrick Bielstein, 2018. "International asset allocation using the market implied cost of capital," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 32(1), pages 17-51, February.
   9. François Ogliaro & Robert K Rice & Stewart Becker & Raul Leote de Carvalho, 2012. "Explicit coupling of informative prior and likelihood functions in a Bayesian multivariate framework and application to a new non-orthogonal formulation of the Black–Litterman model," Journal of Asset Management, Palgrave Macmillan, vol. 13(2), pages 128-140, April.
   10. Zhao, Daping & Bai, Lin & Fang, Yong & Wang, Shouyang, 2022. "Multi‐period portfolio selection with investor views based on scenario tree," Applied Mathematics and Computation, Elsevier, vol. 418(C).
   11. Danish A. Alvi, 2018. "Application of Probabilistic Graphical Models in Forecasting Crude Oil Price," Papers 1804.10869, arXiv.org.
   12. Lawrenz, Jochen & Zorn, Josef, 2017. "Predicting international stock returns with conditional price-to-fundamental ratios," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 159-184.

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