Tag Archives: NYU

Brooklyn Quant Experience Lecture Series: Ting-Kam Leonard Wong

November 30, 2020 Novicki Leave a comment

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

November 18, 2020 Novicki Leave a comment

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

November 18, 2020 Novicki Leave a comment

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Meeting ID: 991 8744 0867
Password: BQEOB

Title

Option-Implied Dependence and Correlation Risk Premium

Abstract

Bio

Seminar

Brooklyn Quant Experience Lecture Series: David Shimko

November 12, 2020 Novicki Leave a comment

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

Brooklyn Quant Experience Lecture Series: Sanjay Nawalkha

November 2, 2020 Novicki Leave a comment

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

October 26, 2020 Novicki Leave a comment

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

October 21, 2020 Novicki Leave a comment

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

[Virtual] Brooklyn Quant Experience Lecture Series: Agostino Capponi

April 23, 2020 Novicki Leave a comment

In light of NYU’s ongoing response to COVID-19, our BQE Lecture Series will take place virtually using Zoom.

Dear All,

You are cordially invited to the Brooklyn Quant Experience Lecture Series (BQE) on Thursday, April 23rd at 6 p.m.

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*Please note a meeting password is required for this event.
Meeting ID: 433 746 420
Password: 003405

Dr. Agostino Capponi will present a talk on the following topic:

Title:

Personalized Robo-Advising: Enhancing Investment through Client Interactions

Abstract

Automated investment managers, or robo-advisors, have emerged as an alternative to traditional financial advisors. Their viability crucially depends on timely communication of information from the clients they serve. We introduce and develop a novel human-machine interaction framework, in which the robo-advisor solves an adaptive mean-variance control problem with the risk-return tradeoff dynamically updated based on the risk profile communicated by the client. We quantify the tradeoff between more frequent interactions, which allow the robo-advisor to construct a portfolio tailored to the client’s risk profile, and less frequent communication, which mitigates the effect of behavioral biases in the client’s risk profile. We show that a high frequency of interaction may have the unintended consequence of lowering the Sharpe ratio of the optimal investment strategy. (joint work with S. Olafsson and T. Zariphopoulou)

Bio:

Agostino Capponi is an Associate Professor in the Department of Operations Research at Columbia University, and a member of the Data Science Institute. He also serves as a consultant at the U.S. Commodity Futures Trading Commission, Office of the Chief Economist, on topics related to clearinghouses and financial stability. Agostino’s current research interests are in systemic risk, networks, market microstructure, and financial technology. Agostino’s research has been funded by NSF, DARPA, the Institute for New Economic Thinking, the Global Risk Institute, the Clearpool Group, and the OCP Group. Agostino’s research has been recognized with the 2018 NSF CAREER award, the JP Morgan AI Research Faculty award, and an honorable mention from the MIT Center for Finance and the Harvard Crowd Innovation Laboratory. Agostino serves or has served on the editorial board of several journals in his field, including Management Science, Operations Research, SIAM Journal in Financial Mathematics, Mathematical Finance, Finance and Stochastics, Mathematics and Financial Economics, Stochastic Systems, and many others. Agostino serves as the chair of the SIAM Activity Group in Financial Engineering, and as the president of the INFORMS Finance Section.

Click on link below for the full spring BQE Lecture Series:
https://engineering.nyu.edu/academics/departments/finance-and-risk-engineering/upcoming-events

Seminar

[Virtual] Brooklyn Quant Experience Lecture Series: Glenn Shafer

March 30, 2020 Novicki Leave a comment

In light of NYU’s ongoing response to COVID-19, our BQE Lecture Series will take place virtually using Zoom.

Dear All,

You are cordially invited to the Brooklyn Quant Experience Lecture Series (BQE) on Thursday, April 2nd at 6 p.m.

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Dr. Glenn Shafer will present a talk on the following topic:

Title:

Let’s Replace P-Values with Betting Outcomes!

Abstract

How can we test the constantly fluctuating probabilities that Nate Silver offers for the outcomes of elections and sporting events? The natural (and perhaps only) way is to interpret Silver’s probabilities as betting offers and to bet against him. He fails our test if we multiply our money by a large factor. We can test a statistical hypothesis, as well as the efficiency of a financial market, in the same way. In the case of statistical hypotheses, this leads to a new understanding of likelihood ratios and to an alternative to the notion of power. See Working Paper 54 at www.probabilityandfinance.com and Game-Theoretic Foundations for Probability and Finance (Glenn Shafer and Vladimir Vovk, Wiley, 2019).

Bio:

Glenn Shafer is best known for his work on the Dempster-Shafer theory of belief functions, especially his 1976 book A Mathematical Theory of Evidence. Beginning in the 1980s, Glenn has studied the mathematical, philosophical, and historical foundations of standard probability theory and on its limitations as a theory of evidence. Since the 1990s, he has collaborated with Vladimir Vovk on understanding the benefits of using betting games (as opposed to measure theory) as a mathematical foundation for the standard theory. Glenn began his career as an educator by teaching geometry in Afghanistan in 1968; he subsequently taught at Princeton, the University of Kansas, and Rutgers. From January 2011 to December 2014, he served as dean of the Rutgers Business School.

Click on link below for the full spring BQE Lecture Series:
https://engineering.nyu.edu/academics/departments/finance-and-risk-engineering/upcoming-events

Seminar

Brooklyn Quant Experience (BQE) Lecture Series: Kimberly Weston

February 28, 2020 Novicki Leave a comment

Please note: this event was previously with Dr. Kimberly Weston, Associate Professor at Rutgers University. Please find the updated details below.

Dear All,

You are cordially invited to the Brooklyn Quant Experience Lecture Series (BQE) on Thursday, March 5th at 6 p.m. in the NYU Tandon Bern Dibner Library at 5 MetroTech Center, 4th Floor – LC 400, in Downtown Brooklyn.

Dr. Stephan Sturm will present a talk on the following topic:

Title:

Portfolio Selection using the Distribution Builder

Abstract

Portfolio optimization subject to personal preferences of an economic agent is a mainstay in financial mathematics. The common way this problem is set up is via a utility function representing the agent’s preferences. This supposes in practice that agents behave rationally as well as that there is a practical and tangible way to determine their utility function. An alternative approach, known as Distribution Builder, has been proposed by Goldstein, Sharpe and Blythe: investors should determine directly the distribution of the terminal payoff given their budget constraint. In this talk we first review the concept of the distribution builder and the mathematical model behind it, and then propose extensions to optimization of intertemporal consumption and in incomplete markets. This is based on ongoing joint work with Carole Bernard and Mauricio Elizalde Mejía.

Bio:

Stephan Sturm is Associate Professor of Mathematical Sciences at Worcester Polytechnic Institute (WPI) in Massachusetts and currently spends his sabbatical at the Chinese University of Hong Kong and NYU. After obtaining his PhD in Mathematics from TU Berlin (Germany), he became a Postdoctoral Research Associate and Lecturer at the Department of Operations Research and Financial Engineering at Princeton University before joining WPI as faculty member. Sturm’s research covers mainly different areas of financial mathematics, but he is interested in stochastic modeling in general, such as applications to climate science. In finance, his work is devoted in particular in questions of value adjustments for derivative securities (XVAs), optimal portfolio selection and systemic risk in financial markets.

We look forward to having you join us for the talk and refreshments.

Click on link below for the full spring BQE Lecture Series:
https://engineering.nyu.edu/academics/departments/finance-and-risk-engineering/upcoming-events

Collaborative events organized by Bloomberg LP, Global Risk Institute, Cornell Financial Engineering Manhattan, International Association of Quantitative Finance (IAQF), NYU Courant Institute of Mathematical Sciences, and NYU Tandon School of Engineering.