Actuarial Science, Financial Risk Management, Risk measures theory, Optimal Portfolio Selection, Extreme events

Shushi, T. & Yao, J. (2020). Multivariate Risk Measures Based on Conditional Expectation and Systemic Risk for Exponential Dispersion Model. Insurance: Mathematics and Economics. Accepted.

Bäuerle N., Shushi T. (2020). Risk Management with Tail Quasi-Linear Means. Annals of Actuarial Science (Cambridge University Press). 1-18.

Landsman, Z., Makov, U., & Shushi, T. (2019). Portfolio Optimization by a Bivariate Functional of the Mean and Variance. Journal of Optimization Theory and Applications, 1-14. Accepted.

Landsman, Z., Makov, U., & Shushi, T. (2019). Analytic solution to the portfolio optimization problem in a mean-variance-skewness model. The European Journal of Finance, 1-14.

Shushi, T. (2019). The Minkowski length of a spherical random vector. Statistics & Probability Letters, 153, 104-107.

Adcock, C., Landsman, Z., & Shushi, T. (2019). Stein’s Lemma for generalized skew-elliptical random vectors. Communications in Statistics-Theory and Methods, 1-16.

Shushi, T. (2018). Towards a Topological Representation of Risks and Their Measures. Risks, 6, 1-15.

Landsman, Z., Makov, U., & Shushi, T. (2018). A Multivariate tail covariance measure for elliptical distributions. Insurance: Mathematics and Economics. 81, 27-35.

Shushi, T. (2018). Generalized skew-elliptical distributions are closed under affine transformations. Statistics & Probability Letters, 134, 1-4.

Landsman, Z, Makov, U., & Shushi, T. (2018). A Generalized Measure for the Optimal Portfolio Selection Problem and its Explicit Solution. Risks, 6, 1-15.

Shushi, T. (2018). A proof for the existence of multivariate singular generalized skew-elliptical density functions. Statistics and Probability Letters. 50-55.

Shushi T. (2017). Skew-elliptical distributions with applications in risk theory. European Actuarial Journal, 7, 1-20.

Landsman, Z., Makov, U., & Shushi, T. (2016). Tail conditional moments for elliptical and log-elliptical distributions. Insurance: Mathematics and Economics, 71, 179-188.

Landsman, Z., Makov, U., & Shushi, T. (2016). Multivariate tail conditional expectation for elliptical distributions. Insurance: Mathematics and Economics, 70, 216-223.

Aharonov, Y., Cohen, E., & Shushi, T. (2016). Accommodating Retrocausality with Free Will. Quanta, 5, 53-60.

Doctor Tomer Shushi is a researcher and a lecturer in Actuarial Science and Risk Management in the Department of Business Administration, Guilford Glazer Faculty of Business and Management, Ben-Gurion University of the Negev. The researchers of Dr. Shushi are focused on risk management, actuary, uncertainty, and finance. In his researches, Dr. Shushi develops and studies models and theories of financial and actuarial risk measurement, systemic risks that may harm entire financial systems, measurement of extreme loss events, analysis of loss distributions, risk decomposition, and optimal portfolio selection. Dr. Shushi publishes his papers in the top tier journals in Actuarial Science and Risk Management.