IE Seminar: “Systemic Risk Measures Based On Value-at-Risk”, Wissam Al-Ali, 1:00PM July 25 (EN)

Thesis Defense Announcement: Wissam Al-Ali

Title: Systemic Risk Measures Based On Value-at-Risk

Advisor: Assistant Professor Çağın Ararat

Date & Time: July 25, 2023, Tuesday at 13:00

Place: Topic: My Meeting
Time: Jul 25, 2023 01:00 PM Istanbul

This is an online seminar. To obtain seminar details please send a message to department.

Abstract: This thesis describes a method for approximating systemic set-valued risk measures. The proposed method incorporates the Eisenberg-Noe (EN) model clearing mechanism as an aggregation function with the Value at Risk as the underlying risk measure. The set-valued systemic risk is then approximated using a grid algorithm, where each grid point is evaluated by solving non-convex sample average approximation vector optimization problems, namely Pascoletti Serafini and norm minimization scalarization problems, after solving the weighted sum scalarization problem to establish the grid compact region. We provide proofs that demonstrate the convergence of the optimal value of the sample average scalarization problems to their respective true problems. Moreover, we demonstrate the convergence of the sample average approximated set-valued risk measure to the true measure in both the Wijsman and Hausdorff senses. In order to provide empirical evidence and demonstrate the applicability of our findings, we constructed an economic network based on the Bollobás preferential attachment model. In addition, we model economic disruptions using independent and identically distributed random vectors with a Pareto distribution. Comprehensive sensitivity analyses are conducted to investigate the effect of various scenarios, correlation coefficients, and Bollobás network parameters on the measures of systemic risk. The results highlight the minimal influence of the number of scenarios and correlation coefficients on the risk measure, demonstrating its stability and robustness, while shedding light on the profound significance of Bollobás network parameters in determining network dynamics and the overall level of systemic risk.
Bio: Wissam Al-Ali completed his high school education at UNRWA High School for Palestinian Refugees in Lebanon. In June 2021, Wissam graduated with High Honors from the Department of Industrial Engineering at Bilkent University, receiving his Bachelor of Science degree. Currently, he is pursuing a Master of Science degree in the same department. Under the guidance of Prof. Çağın Ararat, Wissam is involved in research focused on financial systemic risk measures, a sub-class of Financial Engineering. His research interests also extend to Operations Research and their applications in Financial Mathematics.