Tag Archives: Quant

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
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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.

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.

Seminar

IAQF: How I Became a Quant

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IAQF: How I Became a Quant

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

How I Became a Quant: Washington, DC

Wednesday, November 18th
7:30 pm
Virtual Event

In Partnership with

The George Washington University
School of Business

Panelists

Ali Arar, Fimineco

Lipika Hayet, Capital One

Gregg Berman, Citadel

Moderator

Stephen Young, Wells Fargo

Registration is Free!

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Sponsored by:
The George Washington University
School of Business

The George Washington University, Washington D.C.

Seminar

Brooklyn Quant Experience Lecture Series: Sanjay Nawalkha

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Brooklyn Quant Experience Lecture Series, NYU Tandon

The Department of Finance and Risk Engineering at NYU Tandon School of Engineering, welcomes Sanjay K. Nawalkha, Professor of Finance, University of Massachusetts, to the BQE Lecture Series on Thursday, November 5, 2020, at 6 p.m. on Zoom.

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Meeting ID: 945 2031 9822
Password: BQESN

Title

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

Abstract

This paper introduces a theory of equivalent expectation measures, such as the R measure and the R1T measure, generalizing the martingale pricing theory of Harrison and Kreps (1979) for deriving analytical solutions of expected prices (both the expected current price and the expected future price) of contingent claims. We also present new R-transforms which extend the Q-transforms of Bakshi and Madan (2000) and Duffie et al. (2000), for computing the expected prices of a variety of standard and exotic claims under a broad range of stochastic processes. Finally, as a generalization of Breeden and Litzenberger (1978), we propose a new concept of the expected future state price density which allows the estimation of the expected future prices of complex European contingent claims as well as the physical density of the underlying asset’s future price, using the current prices and only the first return moment of standard European OTM call and put options.

Bio

Sanjay Nawalkha is a Professor of Finance at the Isenberg School of Management. His areas of research are fixed income valuation, derivative pricing, and asset pricing. Professor Nawalkha chaired the Finance Department at the Isenberg School of Management from Sept. 2011 until August 2018. He has co-authored four books, Dynamic Term Structure Modeling: The Fixed Income Valuation Course (Wiley & Sons, 2007), Interest Rate Risk Modeling: The Fixed Income Valuation Course (Wiley & Sons, 2005), Interest Rate Risk Measurement and Management (Institutional Investors, 1999) and Closed-Form Duration Measures and Strategy Applications (The Research Foundation of the Institute of Chartered Financial Analysts, 1990). He has published over 35 scholarly articles in the areas of term structure modeling, risk management, and arbitrage pricing theory.

Seminar

Brooklyn Quant Experience Lecture Series: Peter Carr

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Brooklyn Quant Experience Lecture Series, NYU Tandon

The Department of Finance and Risk Engineering at NYU Tandon welcomes Peter Carr, NYU Tandon, FRE Department Chair, to the BQE Lecture Series on Thursday, October 29th at 6 p.m. on Zoom.   

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Meeting ID:996 5148 5212
Password: BQEPC

Title

Simple Bermudan Option Pricing

Abstract

Many option contracts allow exercise at two or more future times. While numerical methods handle Bermudan optionality in stride, analytic approaches have historically been cumbersome. We present a particular Bermudan option and a particular valuation model for which Bermudan option pricing uses high school mathematics.

Bio

Peter Carr is the current Chair of the Finance and Risk Engineering Department at NYU Tandon School of Engineering. Prior to joining NYU, he headed various quant groups in the financial industry for twenty years. He has won numerous awards and has many publications in both academic and industry journals. He is currently ranked second in the world by Google Scholar for citations on derivatives and third in the world for citations on quantitative finance.

Seminar

Brooklyn Quant Experience Lecture Series: Bruno Kamdem

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Brooklyn Quant Experience Lecture Series, NYU Tandon

The Department of Finance and Risk Engineering welcomes Bruno Kamdem, Professorial Lecturer, The George Washington University, to the BQE Lecture Series on Thursday, October 22nd at 6 p.m. on Zoom.   

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Meeting ID: 919 9128 5424
Password: BQEBK

Title

Optimal Strategies for Oil Production and Taxation Under Cap‑and‑Trade

Abstract

Rising global oil production is contributing to the increase of domestic revenues through a variety of fiscal mechanisms in many governments around the world. Concomitantly, the global low‑carbon transition is compelling the same governments to require special taxes such as carbon tax on oil fields. This paper develops a repertoire through which an oil field extraction policy and a government fiscal policy are optimal under carbon emissions constraints. Traditional models have not been able to capture the mean reverting regime‑switching jump‑diffusion dimension of the oil price as well as the stochastic differential game aspect of the extraction‑taxation dichotomy under carbon emissions constraints. On the one hand, to account for the sensitivity of the oil price to global and seasonal macroeconomic parameters, we model its evolution as a mean reverting regime‑switching jump‑diffusion process. On the other hand, as oil producing countries rely on taxes levied on oil companies whose aim is to maximize revenues generated from their extracting activities, we categorize our model as a stochastic differential game problem. The existence of a Nash Equilibrium is proven. Value functions of the stochastic differential game problem are characterized as the unique viscosity solutions of the corresponding Hamilton Jacobi Isaacs equations. Under Greenhouse gas emissions constraints, optimal extraction and fiscal policies are derived. In the light of a numerical blueprint, our analysis holds that a strategic cap‑and‑trade fiscal protocol under which oil producing governments and oil companies efficiently cooperate can yield positive effects on climate policies.

Bio

Bruno Kamdem is the Co‑founder and Principal of Lepton Actuarial & Consulting, LLC (http://leptonactuarial.com/), a New York based professional firm. Dr. Kamdem concomitantly teaches at the George Washington University, School of Engineering and Applied Science in the department of Engineering Management & Systems Engineering. Prior to consulting and teaching, he worked with the Office of Research, Evaluation, & Statistics at the Social Security Administration where he advised the commissioner on mathematical statistical trends regarding Medical‑ Vocational Guidelines and formulated models involving retirement probabilities for multiple years designed for optimizing individual retirement decisions. Bruno has published articles at the “Renewable & Sustainable Energy Reviews” (Impact Factor: 12.110) and the “Energy Policy” journal, along with two forthcoming papers at the “Review of Economics and Statistics” and “Econometrica”. For several years, Bruno has accumulated experience in teaching and in working with Analysis & Modeling tools (iThink, GAMS, MINITAB, MATHEMATICA, MAPLE), Applications & Operating Systems (System Dynamics, SAS‑Visual Analytics, e‑Enterprise, MATLAB‑Simulink), and Data Management applications (VBA, R, SAS, MATLAB). Bruno’s background encompasses a Ph.D. (Systems Engineering, Operations Research) from the School of Engineering and Applied Science at the George Washington University, an M.S. (Applied Mathematics), and B.S. (Mathematics & Economics), both from the University of Maryland, Baltimore County.

Seminar

Brooklyn Quant Experience Lecture Series: Weilong Fu

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Brooklyn Quant Experience Lecture Series, NYU TandonDear All,

You are cordially invited to the Brooklyn Quant Experience Lecture Series (BQE) on Thursday, October 15th at 6 p.m. on Zoom.

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*Please note a meeting password is required for this event.
Meeting ID: 921 6010 6824
Password: BQEWF

Weilong Fu is a Ph.D. Candidate in the Department of Industrial Engineering and Operations Research at Columbia University

Title

Fast Pricing of American Options Under Variance Gamma

Abstract

We investigate methods for pricing American options under the variance gamma model. The variance gamma process is a pure-jump process that is constructed by replacing the calendar time by the gamma time in a Brownian motion with drift, which makes it a time-changed Brownian motion. In the case of the Black-Merton-Scholes model, there are fast approximation methods for pricing American options, but they cannot be utilized for the variance gamma model. We develop a new fast and accurate approximation method inspired by the quadratic approximation to get rid of the time steps required in finite difference methods and simulation methods while reducing the error by making use of a machine learning technique on pre-calculated quantities. We compare the performance of our method with those of the existing methods and show that this method is efficient and accurate for practical use.

Bio

Weilong is a fourth-year Ph.D. candidate at Columbia University in the Department of Industrial Engineering and Operations Research. Before that, he received his bachelor’s degree in Statistics from Peking University. Weilong’s research interest is focused on computational and quantitative finance.