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Dedicated to fostering the profession of quantitative finance

The IAQF is a not-for-profit, professional society dedicated to fostering the profession of quantitative finance by providing platforms to discuss cutting-edge and pivotal issues in the field.

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IAQF & Thalesians Seminar Series: Combining Reinforcement Learning and Inverse Reinforcement Learning for Optimal Asset Allocation. A Seminar by Igor Halperin.

When
22 Mar 2023

6:00 PM (EDT)

Location
Fordham University: McNally Amphitheater 140 West 62nd Street New York, NY 10023

Register

6:00 PM Seminar Begins

7:30 PM Reception

Hybrid Event:

Fordham University

McNally Amphitheater

140 West 62nd Street

New York, NY 10023

Free Registration!

For Virtual Attendees: Please select Virtual instead of member type upon registration.

Proof of Vaccination Upon Entry is Required for In-Person Attendees

Abstract:

We present a simple practical method to combine the human and artificial intelligence to both learn best investment practices of fund managers, and provide recommendations to improve them. Our approach is based on a combination of Inverse Reinforcement Learning (IRL) and RL. First, the IRL component learns the intent of fund managers as suggested by their trading history, and recovers their implied reward function. At the second step, this reward function is used by a direct RL algorithm to optimize asset allocation decisions. We show that our method is able to improve over the performance of individual fund managers.

Bio:

Igor Halperin is an AI researcher and a Group Data Science Leader at Fidelity Investments. His research focuses on using methods of reinforcement learning, information theory, and physics for financial problems such as portfolio optimization, dynamic risk management, and inference of sequential decision-making processes of financial agents. Igor has an extensive industrial and academic experience in statistical and financial modeling, in particular in the areas of option pricing, credit portfolio risk modeling, and portfolio optimization. Prior to joining Fidelity, Igor worked as a Research Professor of Financial Machine Learning at NYU Tandon School of Engineering. Before that, Igor was an Executive Director of Quantitative Research at JPMorgan, and a quantitative researcher at Bloomberg LP. Igor has published numerous articles in finance and physics journals, and is a frequent speaker at financial conferences. He co-authored “Machine Learning in Finance: From Theory to Practice” (Springer 2020) and contributed to “Credit Risk Frontiers” (Bloomberg LP, 2012). Igor has a Ph.D. in theoretical high energy physics from Tel Aviv University, and a M.Sc. in nuclear physics from St. Petersburg State Technical University. In February 2022, Igor was named the Buy-Side Quant of the Year by RISK magazine.

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How I Became a Quant - Washington DC

When
28 Mar 2023

6:30 PM - 8:30 PM (EDT)

Location
2201 G street, School of Business, Funger Hall suite 108. Washington DC, NW 20052

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Financial Engineers Give a Personal View of Their Careers in Quantitative Finance

A Series of Panel Discussions for Students Interested in a Career in Quantitative Finance

Tuesday, March 28th

Program: 6:30 p.m.

Reception: 8:30 p.m.

2201 G Street, School of Business

Funger Hall Suite 108

Washington DC, NW 20052

In Partnership with:

The George Washington University

School of Business

Panelists

Dr. Aurèle Houngbedji, International Finance Corporation

Richard Schwinn, SEC’s Office of Analytics and Research

Ryan Henning, Freddie Mac

Suzan Isazadeh, Fannie Mae

Moderator

Stephen Young, Wells Fargo

Registration is Free!

Proof of Vaccination is Required

Sponsored by:

Panelist Biographies

Dr. Aurèle Houngbedji, Bio Coming Soon

Richard Schwinn, is an economist and mathematician. He serves as a senior financial analyst at the Securities and Exchange Commission (SEC), where he creates algorithms for detecting anomalies in market data and applies NLP in the rule-making process. Prior to the SEC, he worked as a research economist at the Small Business Administration’s Office of Advocacy, where he co-authored a widely cited paper on small business GDP. He taught graduate and undergraduate courses for more than a decade at universities including Loyola University Chicago. He has an MS in Mathematics and a PhD in Economics from the University of Illinois at Chicago.

Ryan Henning, is the Head of Financial Engineering at Freddie Mac, a position he has held for most of his 22 year career. In this role he oversees the implementation of the firm's models and risk systems, as well as model governance for a $3.4T balance sheet that helps provide stability and liquidity for our nation's housing stock. Models and systems produced by Financial Engineering include automated underwriting, distressed borrower and property decisions, capital markets trading, debt issuance and redemption, market and credit risk management, home valuation, credit risk transfer, hedge accounting, loan loss reserves, regulatory capital, stress testing, balance sheet forecasting, and corporate strategy. Ryan has degrees in Computer Science, Finance and Accounting from St. Bonaventure University, and a Masters in Computational Finance from Carnegie Mellon University. He also holds CFA and FRM designations.

Suzan Isazadeh, is the director of Modeling and Analytics at Fannie Mae’s Multifamily Division (MF). She has more than 10 years of experience in the Mortgage Industry specialized in Residential and Multifamily Real Estate Mortgages. She joined Fannie Mae in late 2009 after graduating from George Washington University. While at Fannie Mae, Suzan covered modeling and analytics for both Single-Family & Multifamily divisions where she initially managed model vetting processes to ensure smooth producionalization of new/updated credit/Loss models. She specialized in developing credit pricing and risk assessment framework for the execution of MF Credit Risk Transfer Transactions and building innovative Machine Learning/ BI tools for front-end business. She currently manages a team of Data Scientists and a Capital Market Advisor, responsible for developing Machine Leaning models to improve/automate Credit Underwriting processes and building analytics tools and models for Capital Markets Trading desk. She holds a Masters’ degree in Finance from George Washington University and an MBA from Sharif University in Tehran. She also has a bachelor’s degree in Industrial Engineering from Tehran Polytechnic University.

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IAQF/Northfield Financial Engineer of the Year Award Dinner

When
26 Apr 2023

6:30 PM (EDT)

Location
The Yale Club, NYC

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Helyette Geman Selected as the Recipient of the

2022 IAQF/Northfield Financial Engineer of the Year Award

IAQF congratulates Helyette Geman, a Professor of Mathematical Finance at Birkbeck, University of London and a Research Professor at Johns Hopkins University, as the 2022 IAQF/Northfield Financial Engineer of the Year (FEOY).

Upon her acceptance of the award Geman remarked, “I am thrilled and honored to join this group of luminaries in Mathematical Finance and wish to salute the names of my dear friends Marc Yor, Peter Carr and Marco Avellaneda, two of them lost in the year 2022. Looking into the future, I want to associate to this Award to my PhD students from all countries. For myself, my goal is to keep doing what I love and include forests, water and land in the mission of IAQF. Hopefully, my global knowledge will help identifying the Climate Clock and some further steps to make it the first Time Change that takes negative values”

The annual IAQF/Northfield FEOY Award, established in 1993, recognizes individual contributions to the advancement of quantitative finance. A nominating committee of approximately 60 people consisting of all the IAQF governing boards submits nominations, which are reviewed in a two-step process by a selection committee of 25 members. The selection committee includes the IAQF board of directors and senior fellows and was chaired by Dr. Paul Glasserman, an IAQF senior fellow and 2020 FEOY award winner.

Award Dinner Information:

Wednesday, April 26, 2023

The Yale Club

New York City

6:30pm Cocktails 7:30pm Dinner

Corporate sponsorships including tables of ten are available

Individual seats are available for $600

For more information please contact the

IAQF office at 646-736-0705 or info@iaqf.org

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more events

IAQF & Thalesians Seminar Series: Combining Reinforcement Learning and Inverse Reinforcement Learning for Optimal Asset Allocation. A Seminar by Igor Halperin.

How I Became a Quant - Washington DC

IAQF/Northfield Financial Engineer of the Year Award Dinner