Category Archives: Seminar

Seminar

Brooklyn Quant Experience Lecture Series: Laura Ballotta

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Brooklyn Quant Experience Lecture Series, NYU Tandon

 Laura Ballotta, Reader in Financial Mathematics at Cass Business School, will give the following talk on Thursday, March 4th at 9:30 AM EST. 
*Kindly note that we have changed the time to 9:30 AM on Thursdays. The new time change allows our invited international guests to join these important virtual talks.

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Meeting ID: 999 3949 8124
Password: FREBQELB

Title

Fourier-based methods for the management of complex insurance products

Abstract

This paper proposes a framework for the valuation and the management of complex life insurance contracts, whose design can be described by a portfolio of embedded options, which are activated according to one or more triggering events. These events are in general monitored discretely over the life of the policy, due to the contract terms. Similar designs can also be found in other contexts, such as counterparty credit risk for example.

The framework is based on Fourier transform methods as they allow to derive convenient closed analytical formulas for a broad spectrum of underlying dynamics. Multidimensionality issues generated by the discrete monitoring of the triggering events are dealt with efficiently designed Monte Carlo integration strategies. We illustrate the tractability of the proposed approach by means of a detailed study of ratchet variable annuities, which can be considered a prototypical example of these complex structured products.

This is joint work with Ernst Eberlein, Thorsten Schmidt and Raghid Zeineddine.

Bio

Laura Ballotta is a reader in Financial Mathematics at Cass Business School, London. She works in the areas of quantitative finance and risk management and has written on topics including stochastic modelling for financial valuation and risk management, numerical methods aimed at supporting financial applications, and the interplay between finance and insurance. She holds a Ph.D. in Mathematical and Computational Methods for Economics and Finance from the Università degli Studi di Bergamo (Italy).

Seminar

Brooklyn Quant Experience Lecture Series: J. Doyne Farmer

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Brooklyn Quant Experience Lecture Series, NYU Tandon

J. Doyne Farmer, Director of Complexity Economics at the Institute for New Economic Thinking at the Oxford Martin School, and Baillie Gifford Professor of Mathematics at the University of Oxford, will give the following talk on Thursday, February 25th at 9:30 AM EST. 
*Kindly note that we have changed the time to 9:30 AM on Thursdays. The new time change allows our invited international guests to join these important virtual talks.

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Meeting ID: 994 9055 8266
Password: FREBQEDF

Title

How Market Ecology Explains Market Malfunction

Abstract

Standard approaches to the theory of financial markets are based on equilibrium and efficiency. Here we develop an alternative based on concepts and methods developed by biologists, in which the wealth invested in a financial strategy is like the abundance of a species. We study a toy model of a market consisting of value investors, trend followers, and noise traders. We show that the average returns of strategies are strongly density-dependent, i.e. they depend on the wealth invested in each strategy at any given time. In the absence of noise, the market would slowly evolve toward an efficient equilibrium, but the statistical uncertainty in profitability (which is adjusted to match real markets) makes this noisy and uncertain. Even in the long term, the market spends extended periods of time away from perfect efficiency. We show how core concepts from ecology, such as the community matrix and food webs, give insight into market behavior. The wealth dynamics of the market ecology explain how market inefficiencies spontaneously occur and give insight into the origins of excess price volatility and deviations of prices from fundamental values.

Bio

J. Doyne Farmer is Director of Complexity Economics at the Institute for New Economic Thinking at the Oxford Martin School, and Baillie Gifford Professor of Mathematics at the University of Oxford. He is also an External Professor at the Santa Fe Institute. His current research is in economics, including financial stability, sustainability, technological change, and economic simulation. He was a founder of Prediction Company, a quantitative automated trading firm that was sold to the United Bank of Switzerland in 2006. His past research spans complex systems, dynamical systems, time series analysis, and theoretical biology. He founded the Complex Systems Group at Los Alamos National Laboratory, and while a graduate student in the 1970s he built the first wearable digital computer, which was successfully used to predict the game of roulette.

Seminar

Brooklyn Quant Experience Lecture Series: Ed Weinberger

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Brooklyn Quant Experience Lecture Series, NYU Tandon

Ed Weinberger, Adjunct Professor, NYU Tandon FRE, will give the following talk on Thursday, February 18th at 9:30 AM EST. 
*Kindly note that we have changed the time to 9:30 AM on Thursdays. The new time change allows our invited international guests to join these important virtual talks.

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Meeting ID: 971 4847 6117
Password: FREBQEEW

Title

Pragmatic Information and Market Efficiency

Abstract

“Standard,” information theory says nothing about the semantic content of information. Nevertheless, financial markets demand consideration of precisely this aspect of information, yet the search for a suitable measure of an “amount of meaning” has been, up until now, largely unsuccessful. This talk represents an attempt to move beyond this impasse, based on the observation that the meaning of a message can only be understood relative to its receiver. Positing that the semantic value of information is its usefulness in making an informed decision, I define pragmatic information as the information gain in the probability distributions of the receiver’s actions, both before and after receipt of a message in some predefined ensemble. The efficient market hypothesis (EMH) is then the statement that the pragmatic information of available information (previous prices, news items, etc.) in predicting future prices from zero. I contrast this version of the EMH with the more familiar claim that price processes are martingales by observing that the familiar GARCH(1, 1) process, though a martingale, violates the present version of the EMH.

Bio

Ed began his post Ph.D. career as a researcher in theoretical evolutionary biology at the University of Pennsylvania and the Max Planck Institute, but he transferred his skills in applied math to quantitative finance when he became a quant on the interest rate desk of HSBC. Upon joining Deutsche Bank, Ed became interested in financial risk management, where he helped establish GARP’s Financial Risk Manager (FRM) exam. Since then, he has since consulted on a number of projects in quantitative finance and financial technology (“fintech”), including his ongoing fintech work at Bank of America. Besides being a long-time adjunct in what is now Tandon’s Department of Finance and Risk Engineering (FRE), Ed was a visiting professor of finance at Clark University from 2014-2016.

Ed currently teaches numerical methods and Python programming in the FRE Department.

Seminar

Brooklyn Quant Experience Lecture Series: Tom Davis

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Brooklyn Quant Experience Lecture Series, NYU Tandon

Tom Davis, Ph.D., CFA, Vice President, Director Research, Fixed Income and Derivatives, FactSet, will give the following talk on Thursday, February 11th at 9:30 AM EST. 
*Kindly note that we have changed the time to 9:30 AM on Thursdays. The new time change allows our invited international guests to join these important virtual talks.

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Meeting ID: 938 8650 9511
Password: FREBQETD

Title

A Likely Gamma

Abstract

In this talk, I will present a derivation of binomial and trinomial trees using the path integral formalism of quantitative finance, resulting in a novel formula for delta is found based on the likelihood ratio method. This formula yields extremely accurate results at virtually no extra computational cost. Further, when combined with automatic differentiation, this method overcomes a known issue in that gamma is not computable on trees. Finally, I will show some current research broadening this new formula for delta to other cases – including a new method to stable “bumped” deltas for Monte Carlo.

Bio

Dr. Tom Davis, Ph.D., CFA is Vice President, Director Research, Fixed Income & Derivatives at FactSet. In this role, he is focused on ensuring FactSet provides the highest quality fixed income and derivative analytics while growing the coverage across all asset classes. His team also conducts cutting-edge research in the models and methods of quantitative finance which will ultimately increase the speed and accuracy of FactSet analytics. Prior to FactSet, Mr. Davis spent four years at Numerix as Vice President of Product Management in charge of their flagship product and before that, four years managing a team of quantitative analysts at FINCAD focused on arbitrage-free modes of interest rates and foreign exchange rates used to price exotic hybrid derivatives. Dr. Davis earned a Doctor of Philosophy in theoretical physics from the University of British Columbia in Vancouver, Canada.

Seminar

Cornell – Citi Financial Data Science Webinars

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Cornell Engineering. Operations Research and Information Engineering. Financial Engineering Manhattan

Featuring Machine Learning experts from Cornell, Citi, and more…

You and your colleagues are invited to attend the Cornell – Citi Financial Data Science Webinars. Through the online talks in Spring 2021, we are excited to collaborate with Citi in highlighting machine learning applications in finance.

All webinars are from 5:00 pm to 6:00 pm EST.

This webinar is free and open to all guests. Registration is required (RSVP). You will receive the webinar link and dial-in info upon registration (the confirmation email will come from
no-reply@zoom.us)

Date: Tuesday, Feb. 16th, 2021
Time: 5:00 pm – 6:00 pm EST
Speaker: Charles-Albert Lehalle | Capital Fund Management
Title: “An Attempt to Understand Natural Language Processing And Illustration On A Financial Dataset”

Abstract

I will present a theoretical analysis of word2vec language models and explain how the resulting understanding can generalize to more nonlinear ones (like BERT).

This analysis relies on trying to exhibit a generative model allowing to explain the asymptotic meaning of the loss functions used by these kinds of models. In particular, it allows to produce synthetic languages having a controlled number of “synonyms” and try to learn them with standard algorithms. I will then show how learning the language of financial news reflects (or not) the celebrated Loughran-McDonald sentiment lexicon. This on-going work is conducted with Mengda Li (ENS Paris Saclay).

Program Agenda:

1) Charles-Albert Lehalle’s Presentation
2) Q&A
3) “Lightning Talk” about NLP featuring CFEM alumna Silvia Ruiz
4) Discussion

Speaker Bio

Currently Head of Data Analytics at Capital Fund Management (CFM, Paris) and visiting researcher at Imperial College (London), Charles-Albert Lehalle studied machine learning for stochastic control during his PhD 20 years ago. He started his career being in charge of AI projects at the Renault research center and moved to the financial industry with the emergence of automated trading in 2005. He became an expert in market microstructure and has been appointed Global Head of Quantitative Research at Crédit Agricole Cheuvreux, and Head of Quantitative Research on Market Microstructure in the Equity Brokerage and Derivative Department of Crédit Agricole Corporate Investment Bank after the crisis. He provided research and expertise on these topics to investors and intermediaries, and is often heard by regulators and policy-makers like the European Commission, the French Senate, the UK Foresight Committee, etc. He chairs the Index Advisory Group of Euronext, is a member of the Scientific Committee of the French regulator (AMF), and has been part of the Consultative Workgroup on Financial Innovation of the European Authority (ESMA).

Moreover, Charles-Albert received the 2016 Best Paper Award in Finance from Europlace Institute for Finance (EIF) and published more than fifty academic papers and book chapters. He co-authored the book “Market Microstructure in Practice” (World Scientific Publisher, 2nd ed 2018), analyzing the main features of modern markets. He is chairing the “Finance and Insurance Reloaded” transverse research program of the Louis Bachelier Institute; this program explores the influence of new technologies (from blockchain to artificial intelligence) on our industries.

“Lightning Talk” Info: CFEM alumna Silvia Ruiz will discuss her capstone project, which was titled, “How to Predict Stock Movements Using NLP Techniques.” By utilizing NLP techniques, the Cornell CFEM team, sponsored by Rebellion Research, explored whether investing signals can be extracted financial data. The team analyzed 10K and 10Q reports from S&P500 companies using techniques such as FinBERT and word2vec.

Silvia Ruiz (MFE Cornell ’20, BS Mathematics Universidad Del Valle ’17) has experience working as a Data Scientist for Corporación Multi Inversiones and as a Risk Analytics Analyst for Morgan Stanley.

We hope to see you online!

The Cornell-Citi Team

**Please excuse any duplication of this announcement

Upcomng CFEM Events

March 9th, 2021

Speaker: Bruno Dupire (Bloomberg L.P.)

Title of Presentation: Some Applications of Machine Learning in Finance

April 13th, 2021

Speaker: Peter Carr (NYU)

Title of Presentation: Adding Optionality

May 11th, 2021

Speaker: Raja Velu (Syracuse University)

Title of Presentation: TBD

Seminar

Brooklyn Quant Experience Lecture Series: Keith Lewis

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Brooklyn Quant Experience Lecture Series, NYU Tandon

Welcome back to the spring 2021 semester. We hope that you all are doing well and look forward to a productive year.

Below please find the first BQE Lecture Series scheduled this semester. Kindly note that we have changed the time to 9:30 AM on Thursdays. The new time change allows our invited international guests to join these important virtual talks.

Keith Lewis, Managing Member of KALX, LLC, will give the following talk on Thursday, February 4th at 9:30 AM EST.

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Meeting ID: 953 8089 0352
Password: FREBQEKL

Title

A Unified Model of Derivative Securities

Abstract

Market instruments can be bought or sold at a price and ownership entails cash flows. Shares of instruments can be traded based on available information that accrue to positions. The mark-to-market value and amounts involved with trading correspond to price and cash flows. The Unified Model demonstrates the connection between dynamic trading and how to value, hedge, and manage the risk of a derivative security. It can be used for any portfolio of instruments. Every arbitrage-free model of prices and cash flows is parameterized by a vector-valued martingale whose components are indexed by market instruments and a positive, adapted process called a deflator. If repurchase agreements are available they determine a canonical deflator.

Bio

Keith A. Lewis started his professional career as a J. D. Tamarkin assistant professor at Brown where he pioneered the use of computers as a classroom tool in mathematics. He went on to a Wall Street career at Bankers Trust, Morgan Stanley, and Banc of America Securities where his team built the equity derivative libraries used by the trading desk to run their business. Since 2002 Keith has been a consultant for hedge funds building valuation models and tools for exploring, testing, and implementing trading strategies. Other projects include insurance companies involved with GPU computing, law firms certifying tax conformance of trades, and municipal bond advance refunding. He has spun off a number of open source projects based on his experience with building tools his clients found useful and has been using them in courses he has taught at NYU, Rutgers, Cornell, and Columbia.

Seminar

Brooklyn Quant Experience Lecture Series: Ting-Kam Leonard Wong

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Brooklyn Quant Experience Lecture Series, NYU Tandon

The Department of Finance and Risk Engineering welcomes Ting-Kam Leonard Wong, Assistant Professor, Department of Statistical Sciences at the University of Toronto, to the BQE Lecture Series on Thursday, December 3, 2020, at 6 p.m. on Zoom.

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Meeting ID: 916 8329 0348
Password: BQETKLW

Title

Statistical Modeling of Capital Distribution and Portfolio Optimization

Abstract

Capitalization-weighted market indexes such as S&P500 summarize the performance of equity markets and serve as benchmarks of many individual and institutional investors. The ranked weights of a market index are called the capital distribution. In stochastic portfolio theory, it was shown that market diversity, a measure of the concentration of capital distribution, is significantly correlated with the relative performance of active portfolio managers. Statistical modeling of the capital distribution, however, is lacking in the literature. In this talk, we present an ongoing study on capital distribution from the viewpoint of high dimensional time series analysis. Using dynamic factor models, we show that the notion of market diversity can be justified statistically in terms of the most efficient dimension reduction of capital distribution. We also introduce a nonparametric portfolio optimization in the framework of stochastic portfolio theory to exploit the stability of the capital distribution.

Bio

Leonard Wong is an assistant professor in the Departments of Statistical Sciences at the University of Toronto and Computer and Mathematical Sciences at the University of Toronto Scarborough. He completed his Ph.D. in Mathematics at the University of Washington, after which he was a non-tenure track assistant professor at the University of Southern California. His current research interests include probability, mathematical finance, and optimal transport.

Seminar

Brooklyn Quant Experience Lecture Series: Oleg Bondarenko

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Brooklyn Quant Experience Lecture Series, NYU Tandon

The Department of Finance and Risk Engineering welcomes Oleg Bondarenko, Professor, the University of Illinois at Chicago, to the BQE Lecture Series on Thursday, November 19, 2020, at 6 p.m. on Zoom.

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Meeting ID: 991 8744 0867
Password: BQEOB

Title

Option-Implied Dependence and Correlation Risk Premium

Abstract

We propose a novel model-free approach to obtain the joint risk-neutral distribution among several assets that is consistent with all market prices of options on these assets and their weighted index. In an empirical application, we use options on the S&P 500 index and its nine industry sectors. The results of our analysis reveal that the option-implied dependence for the nine sectors is highly non-normal, asymmetric, and time-varying. The estimated joint distribution allows us to study two conditional correlations: when the market moves down or up. We find that the risk premium for the down correlation is strongly negative, while the opposite is true for the up correlation. These findings are consistent with the economic intuition that investors dislike the loss of diversification when markets fall, but they actually prefer high correlation when markets rally.

Bio

Oleg Bondarenko is a Professor of Finance at the University of Illinois at Chicago. He received an MS degree from the Moscow Institute of Physics and Technology and a Ph.D. from the California Institute of Technology. His primary research interests include option pricing, financial econometrics, and market microstructure. His research has appeared in top Finance and Economics journals and has been featured in Morningstar, Economist, and other media outlets.

Professor Bondarenko has consulted with several investment firms and currently serves on the Product Development Committee of Chicago Board Options Exchange (Cboe). His research has been supported by the Chicago Mercantile Exchange, Cboe, Institute of Structured Finance, and Derivatives, among others. He has written two research studies commissioned by Cboe. Professor Bondarenko held visiting faculty positions at the Olin School of Business, Washington University in St. Louis, and Kellogg School of Management, Northwestern University.

Seminar
Leave a comment

Brooklyn Quant Experience Lecture Series, NYU Tandon

The Department of Finance and Risk Engineering welcomes Oleg Bondarenko, Professor, the University of Illinois at Chicago, to the BQE Lecture Series on Thursday, November 19, 2020, at 6 p.m. on Zoom.

Attend Virtually >>

Meeting ID: 991 8744 0867
Password: BQEOB

Title

Option-Implied Dependence and Correlation Risk Premium

Abstract

We propose a novel model-free approach to obtain the joint risk-neutral distribution among several assets that is consistent with all market prices of options on these assets and their weighted index. In an empirical application, we use options on the S&P 500 index and its nine industry sectors. The results of our analysis reveal that the option-implied dependence for the nine sectors is highly non-normal, asymmetric, and time-varying. The estimated joint distribution allows us to study two conditional correlations: when the market moves down or up. We find that the risk premium for the down correlation is strongly negative, while the opposite is true for the up correlation. These findings are consistent with the economic intuition that investors dislike the loss of diversification when markets fall, but they actually prefer high correlation when markets rally.

Bio

Oleg Bondarenko is a Professor of Finance at the University of Illinois at Chicago. He received an MS degree from the Moscow Institute of Physics and Technology and a Ph.D. from the California Institute of Technology. His primary research interests include option pricing, financial econometrics, and market microstructure. His research has appeared in top Finance and Economics journals and has been featured in Morningstar, Economist, and other media outlets.

Professor Bondarenko has consulted with several investment firms and currently serves on the Product Development Committee of Chicago Board Options Exchange (Cboe). His research has been supported by the Chicago Mercantile Exchange, Cboe, Institute of Structured Finance, and Derivatives, among others. He has written two research studies commissioned by Cboe. Professor Bondarenko held visiting faculty positions at the Olin School of Business, Washington University in St. Louis, and Kellogg School of Management, Northwestern University.

Seminar

Brooklyn Quant Experience Lecture Series: David Shimko

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Brooklyn Quant Experience Lecture Series, NYU Tandon

The Department of Finance and Risk Engineering welcomes David Shimko, NYU Tandon, Industry Full Professor, to the BQE Lecture Series on Thursday, November 12, 2020, at 6 p.m. on Zoom.

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Meeting ID: 993 5500 0941
Password: BQEDS

Title

A Theory of Equivalent Expectations Measures for Expected Prices of Contingent Claims

Abstract

Reframing modern portfolio theory with Gaussian cash flows rather than percentage returns, the CFPM (cash flow portfolio model) sets a structural foundation for valuing both traditional capital assets and derivatives. Asset prices are shown to be decreasing functions of both cash flow covariances and variances. The usual single-period CAPM formulas follow, but the expected returns are determined endogenously. All risk is implicitly priced in expected returns, leading to reinterpreted rules for portfolio selection and capital budgeting. Derivatives obey the same total covariance-based pricing relationships as cash flows, except that they exist in zero net supply. After applying a regularity condition, the Bachelier option pricing model obtains in a discrete-time setting without continuous trading. The closed-form CFPM extends to multiple periods. The multiperiod CFPM generalizes risk-neutral pricing to discrete multi-period contingent claim models, such as valuing the capital structure of a firm and CDOs.

Bio

Professor Shimko joined FRE in 2017 following a 30+ year career in investment banking and consulting. After beginning his career as an Assistant Professor at USC, he left to become a Vice President at JPMorgan, and a Principal at Bankers Trust. He co-founded Risk Capital, a successful independent risk management consulting firm, which was sold in 2006. Since that time, he has combined private consulting with entrepreneurial ventures in asset management and credit. His current research focuses on advanced valuation techniques, such as the application of derivative pricing technology to corporate assets, liabilities, and decisions.