DEPARTMENT OF MANAGEMENT STUDIES
INDIAN INSTITUTE OF SCIENCE

DEPARTMENT SEMINAR NOTICE

SPEAKER:
Dr. Arjun Beri
2nd-degree connection 2nd India & Philippines Head of Stress Testing,
Balance Sheet & Markets Model Validation, Corporate Model Risk,
Wells Fargo

TITLE: Navigating the Dynamics of Quant Finance

DAY & DATE & TIME:
Wednesday, 4th Octber 2023 2.00 PM

VENUE: Seminar Hall, Department of Management Studies, IISc.

Abstract:
In the dynamic realm of financial securities trading, constant evolution necessitates adaptability. To thrive, institutions must embrace cutting-edge tools and skills, including mathematics, statistics, and technology. The rise of technology-driven systems intensifies the demand for these capabilities, particularly in quantitative finance roles.

Prospective quant finance professionals must blend mathematical prowess, statistical acumen, and technological savvy with domain knowledge. Skill sets can vary across roles, spanning research, analysis, development, programming, risk management, trading, data science, and more. This industry thrives under pressure, offering rapid growth to those eager to learn.
Within Wells Fargo, qualities such as customer-centricity, integrity, collaboration, adaptability, problem-solving, and effective communication are prized. Continuous learning, accountability, leadership, and an inclusive mindset are also key attributes valued in this esteemed institution, ensuring a rewarding career path.

About the Speaker:
Currently, Mr. Arjun Beri works as a Quant in the area of risk and analytics. He works on developing and validating models pertaining to Derivative Valuation, Credit Risk Analysis, Market Risk Analysis, Asset Liability Management, and Stress Testing (Scenario Generation models as part of CCAR, ICAAP).

In his research, he has worked extensively on the applications of Stochastic Differential Equations to practical problems from Finance, Climate Modeling, and Medicine. In his thesis, he developed a general mathematical framework to study the parametric estimation techniques in sub-optimal situations, namely, when there is a mismatch between the observed data and the stochastic model.

Their technique has been applied to the analysis of high-frequency time series from finance and stochastic volatility modelling.

Specialties: Option pricing models, Stochastic Calculus, Black-Scholes Model and Extensions, Monte-Carlo methods, Statistics and Programming. Interned with several international banks and successfully applied these techniques to answer practical problems in financial engineering.

ALL ARE WELCOME