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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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Upcoming Events

    • 09 Apr 2024
    • 6:00 PM (EDT)
    • 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.

    Abstract:

    We extract contextualized representations of news text to predict returns using the state-of-the-art large language models in natural language processing. Unlike the traditional word-based methods, e.g., bag-of-words or word vectors, the contextualized representation captures both the syntax and semantics of text, thus providing a more comprehensive understanding of its meaning. Notably, word-based approaches are more susceptible to errors when negation words are present in news articles. Our study includes data from 16 international equity markets and news articles in 13 different languages, providing polyglot evidence of news-induced return predictability. We observe that information in newswires is incorporated into prices with an inefficient delay that aligns with the limits-to-arbitrage, yet can still be exploited in real-time trading strategies. Additionally, we find that a trading strategy that capitalizes on fresh news alerts results in even higher Sharpe ratios.

    Bio:

    Dacheng Xiu is Professor of Econometrics and Statistics at the University of Chicago Booth School of Business. His current research focuses on developing machine learning solutions to big-data problems in empirical finance. Xiu’s work has appeared in the Journal of Finance, Review of Financial Studies, Econometrica, Journal of Political Economy, the Journal of the American Statistical Association, and the Annals of Statistics. He has served as Co-Editor for the Journal of Financial Econometrics and has been on the editorial board as an Associate Editor for many prestigious journals, including the Review of Financial Studies, Journal of the American Statistical Association, Journal of Econometrics, and Management Science. He has received several recognitions for his research, including the Fellow of the Society for Financial Econometrics, Fellow of the Journal of Econometrics, AQR Insight Award, EFA Best Paper Prize, and Swiss Finance Institute Outstanding Paper Award. He has been recognized as one of Poets & Quants’ Best 40-under-40 Business School Professors of 2023. At Booth, he teaches a variety of courses related to FinTech, Big Data, and Statistical Inference to MBA, college, and PhD students. Xiu earned his PhD and MA in applied mathematics from Princeton University.

    • 07 May 2024
    • 6:00 PM (EDT)
    • 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.

    Abstract:

    Topological Data Analysis (TDA) has emerged as a powerful methodology in time-series analysis and signal processing. TDA is able to provide detailed descriptions of complex data which complements statistical methods. Recent applications include detection of critical transitions in financial time series, particularly of financial bubbles. The methodology relies on time-delay coordinate embedding, which is used to construct, from the time-series, a point-cloud in some space. The dynamics on the point-cloud unveils patterns in the time-series. Most of the evidence so far on the adeptness of TDA to detect financial bubbles has been empirical. We present, for the first time, a heuristic argument for why TDA can detect financial bubbles. We use models from economics that assert that the time series exhibit certain oscillatory patterns when approaching a tipping point. These oscillations determine holes in the point-clouds, which can be quantified by TDA. When approaching the tipping point of a bubble, there are significant changes in the nature of the oscillations, and consequently in the TDA output. These changes can be captured via persistence homology and yield early warning signals. As an application, we illustrate this approach on a sample of positive and negative bubbles in the Bitcoin price.

    Bio:

    Marian Gidea is a professor of mathematics at Yeshiva University in New York City. He held previous appointments at the Mathematical Sciences Research Institute in Berkeley, the Institute for Advanced Study in Princeton, Centre de Recerca Matemàtica in Barcelona, Northeastern Illinois University, Northwestern University, and Loyola University Chicago. He also served at the National Science Foundation as a program director in the Mathematical Sciences Division. His research interests include Dynamical Systems, Topological Data Analysis, and Financial Mathematics.

    • 05 Jun 2024
    • 6:30 PM (EDT)
    • The Yale Club, NYC
    Register

    Financial Engineer of the Year:

    Leif Andersen


    IAQF Innovation Award:

    Rachel Schutt


    Award Dinner Information

    Wednesday, June 5, 2024

    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


    About This Year's Award Recipients:

    IAQF congratulates Leif Andersen, the Global Co-Head of the Quantitative Strategies & Data Group (QSDG) at Bank of America, and an Adjunct Professor at NYU’s Courant Institute for Mathematical Sciences and at Carnegie Mellon University’s Department of Mathematical Services, as the 2023 IAQF/Northfield Financial Engineer of the Year (FEOY). A Managing Director and head of Bank of America’s quant team for nearly 22 years, Andersen has grown the team from a small group of mathematical modelers to hundreds of quants, strats, data scientists, and software engineers. Prior to joining BofA, he worked for 9 years at General Re Financial Products (GRFP), an innovative AAA-rated derivatives dealer based in NYC, where he collaborated with luminaries such as Jesper Andreasen, Rupert Brotherton-Ratcliffe, and Antoine Savine.

    IAQF congratulates Dr. Rachel Schutt, Managing Director and Co-Head of BlackRock AI Labs, as the winner of the 2023 IAQF Innovation Award sponsored by Berkeley SkyDeck Fund. Dr. Rachel Schutt, Managing Director and Tech Fellow, is the Co-Head of BlackRock AI Labs along with Professor Stephen Boyd. AI Labs is a central hub to formalize data science efforts and leverage artificial intelligence to solve high priority problems across the firm while driving consistent standards, best practices, and expanding BlackRock's data science community. Previously Rachel was the Chief Data Scientist of News Corp. There she established the company's first data science team for Dow Jones, the Wall Street Journal, and other media brands. Rachel was named a World Economic Forum Young Global Leader in 2015 and is on the 2014 Crain's New York Business 40 under 40 list.

    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. 

Latest News

January 26, 2024

Leif Andersen Selected as the Recipient of the 2023 IAQF/Northfield Financial Engineer of the Year Award.

January 26, 2024 – NEW YORK CITY – The International Association for Quantitative Finance (IAQF) and Northfield Information Services have named Leif Andersen, the Global Co-Head of the Quantitative Strategies & Data Group (QSDG) at Bank of America, and an Adjunct Professor at NYU’s Courant Institute for Mathematical Sciences and at Carnegie Mellon University’s Department of Mathematical Services, as the 2023 IAQF/Northfield Financial Engineer of the Year (FEOY). The award will be presented to Professor Andersen at a celebration in New York City in the spring of 2024.

Read the full press release here.

February 20, 2024

Rachel Schutt, Co-Head of BlackRock’s AI Labs, Selected as the Recipient of the 2023 IAQF Innovation Award.

February 20, 2024 – NEW YORK CITY – The International Association for Quantitative Finance (IAQF) has named Dr. Rachel Schutt, Managing Director and Co-Head of BlackRock AI Labs, as the winner of the 2023 IAQF Innovation Award sponsored by Berkeley SkyDeck Fund. The award will be presented to Dr. Schutt at a celebration in New York City in on June 5 , 2024.

“I am incredibly honored to be selected for the inaugural IAQF Innovation Award. Running the AI Labs alongside Professor Stephen Boyd has allowed us to make fundamental contributions in bridging the worlds of academia and practice,” said Schutt. “It's an affirmation of the impact of data science in solving high-priority problems and advancing innovation. Thank you, IAQF, for this exciting recognition.”

Read the full press release here.


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Jon Ingersoll

Professor Ingersoll is the Adrian C. Israel Professor of International Trade and Finance, Emeritus, at Yale's School of Management.  He received his S.B. in Physics (1971) and an S.M. (1973) and Ph.D. (1976) all from M.I.T. Prior to coming to Yale, Professor Ingersoll was an Assistant and Associate Professor at the Graduate School of Business of the University of Chicago.

He specialized in multiperiod models of asset valuation, including the pricing of options and futures, and the term structure of interest rates. He is the author of numerous papers, most notably, the Cox-Ingersoll-Ross Term Structure model.  He is also well known for his PhD text book The Theory of Financial Decision Making. He is currently working a new digital-only PhD text Financial Models and Theories

He was a member of the founding committee of the Society for Financial Studies and served as one of the original editors of its Review of Financial Studies. He was also as associate editor of  Journal of Financial Economics, Journal of Finance, Review of Derivatives Research, Journal of Financial Research, Journal of Business, Finance and Accounting, and Journal of Financial Literature.

His awards include Batterymarch Financial Management Fellowship in Investments and Finance, Alfred P. Sloan Foundation Research Fellowship in Economics, Risk Magazine Hall of Fame, International Association of Financial Engineers “Financial Engineer of the Year”, and Barclays Global Investors/Michael Brennan Best Paper Award.

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