Tag Archives: Seminar

Brooklyn Quant Experience Lecture Series: David Shimko

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.

Brooklyn Quant Experience Lecture Series: Peter Carr

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.

Brooklyn Quant Experience Lecture Series: Bruno Kamdem

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.

Brooklyn Quant Experience Lecture Series: Pasquale Cirillo

Brooklyn Quant Experience Lecture Series, NYU TandonDear All,

You are cordially invited to the Brooklyn Quant Experience Lecture Series (BQE) on Thursday, October 1st at 6 p.m. on Zoom.

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*Please note a meeting password is required for this event.
Meeting ID: 925 3238 8440
Password:
BQEPC

Pasquale Cirillo, Professor of Risk Management at the University of Nicosia, Cyprus, and NYU FRE Boot Camp Instructor, will give the following talk:

Title

From P to Q and Beyond, a Tale of Inequality

Abstract

We use tools from inequality studies, like the Lorenz curve and the Gini index, to study the relation between the market measure P and the risk-neutral measure Q, but we also deal with the share measure and the T-forward measure. This alternative approach to the change of measure operation is extremely useful to understand some profound and non-trivial connections among measures, and—in some cases— it can also simplify pricing problems. No preliminary knowledge of inequality measures will be assumed.

Bio

Pasquale Cirillo is a Professor of Risk Management at the University of Nicosia, Cyprus, where he is also a member of the Institute For the Future. He previously held positions at the Delft University of Technology (NL) and the University of Bern (CH). He has been a visiting scholar of NYU FRE, and one of the instructors of the FRE Summer boot camp. His research interests include quantitative risk management, extreme value theory, and urn models. He has published in top international journals and is currently writing a book on fat tails. Besides his academic career, Pasquale has also collaborated with international institutions and many top private companies and banks as a statistical consultant. His MOOCs in risk management have been attended by more than a hundred thousand students from all over the world. He is a proud amateur cook.

[Virtual] Brooklyn Quant Experience Lecture Series: Glenn Shafer

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

Brooklyn Quant Experience Lecture Series, NYU TandonDear 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

Brooklyn Quant Experience Lecture Series (BQE): Peter Carr

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

Brooklyn Quant Experience Lecture Series, NYU TandonDear All,

You are cordially invited to the Brooklyn Quant Experience Lecture Series (BQE) on Thursday, March 12th at 6 p.m.  

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Dr. Peter Carr will present a talk on the following topic:

Title:

Addition, Multiplication and Options

Abstract

We treat optionality as a binary operation, on an equal footing with addition and multiplication.
We begin with optionality between real-valued securities, but then use a change of arithmetic to cover optionality between assets whose prices are never negative.
We conclude with several examples illustrating how changes of arithmetic can connect disparate geometric and financial truths.

Bio:

Dr. Peter Carr is the Chair of the Finance and Risk Engineering Department at NYU Tandon School of Engineering. He has headed various quant groups in the financial industry for the last twenty years. He also presently serves as a trustee for the National Museum of Mathematics and WorldQuant University. Prior to joining the financial industry, Dr. Carr was a finance professor for 8 years at Cornell University, after obtaining his Ph.D. from UCLA in 1989. He has over 85 publications in academic and industry-oriented journals and serves as an associate editor for 8 journals related to mathematical finance. He was selected as Quant of the Year by Risk Magazine in 2003 and Financial Engineer of the Year by IAQF/Sungard in 2010. From 2011 to 2014, Dr. Carr was included in Institutional Investor’s Tech 50, an annual listing of the 50 most influential people in financial technology.

In the 2.5 years Dr. Carr has been FRE dept. chair, applications increased from 1,300 per year to 1,800 per year. For the 2018 class, current quant GRE is 169/170 and GPA is 3.82. FRE moved up in QuantNet rankings both years. An online summer course was initiated 2 summers ago and an on-campus bootcamp was initiated this past summer. Six electives on machine learning in finance were introduced. The distance learning room became operational this past summer.

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

Brooklyn Quant Experience (BQE) Lecture Series: Kimberly Weston

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

Brooklyn Quant Experience Lecture Series, NYU TandonDear 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

Cornell – Citi Financial Data Science Seminars

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

You and your colleagues are invited to attend the Cornell – Citi Financial Data Science Seminars at the Tata Innovation Center at Cornell Tech, Room 131. Through the talks this semester, we are excited to collaborate with Citi in highlighting machine learning applications in finance.

11 West Loop Road
New York, NY 10044

All seminars are from 6:00pm to 7:00pm. This seminar will be recorded, and you can watch the livestream.

Seminars are free. However, registration is required for NYC attendees as seating is limited.

 

Date: Wednesday, March 4, 2020
Time: 6:00 pm – 7:00 pm
Speaker: Alok Dutt | Citigroup
Title: Data Science in Financial Markets: Hype vs. Useful Practical Reality

Abstract: The data-driven fields of AI and ML are ubiquitous in the financial industry, but despite the promise there are many obstacles to effective application. Few firms are able to reap their full rewards and it is increasingly important to distinguish what works from what doesn’t in practice. How does one navigate the opportunities and challenges amid the plethora of techniques and complexities of implementation? This talk will present a number of general principles and case studies that can help make the necessary choices to realize the transformational potential of data within a financial institution.

Speaker Bio

Alok Dutt is Head of Analytics in the Markets Quantitative Analysis division at Citigroup. He is an architect and manager responsible for various advanced projects in data analytics, trading algorithms and automation across multiple business lines and asset classes. In his role at Citi he applies data and quantitative techniques to automate business processes including research, modeling, trading, simulation and visualization. Alok has extensive experience in several broad areas of quantitative finance, including derivatives modeling, algorithmic trading and market making. Before Citi, he developed the trading models and algorithms for a new automated options market making group at Morgan Stanley that was the subject of a HBS case study on disruptive innovation. Prior to that, Alok was an exotics modeler and trader and established the first multi-asset hybrid trading desk at Bank of America. Alok has a PhD in Computer Science from Yale University and a BA in Mathematics from Cambridge University.

We hope to see you there!

The Cornell-Citi Team

Directions to CFEM&Citi @CornellTech on Roosevelt Island: Take the Tram or the F train to Roosevelt Island; walk to the left along the East River until you see a modern glass building, which is the Tata Innovation Center. Once you enter the lobby and check in, walk straight ahead to Room 131.

**Please excuse any duplication of this announcement

Upcoming CFEM Events

April 1, 2020
May 6, 2020

Brooklyn Quant Experience Lecture Series: Marina Di Ciacinto

Brooklyn Quant Experience Lecture Series, NYU TandonDear All,

You are cordially invited to the Brooklyn Quant Experience Lecture Series (BQE) on Thursday, February 27th at 5 p.m.* in the NYU Tandon MakerSpace at 6 MetroTech Center, 1st Floor in Downtown Brooklyn.

*Please note the time change for this week’s event. The BQE Lecture Series is normally held at 6 p.m. 

Dr. Marina Di Ciacinto will present a talk on the following topic:

Title:

Dynamic Optimal Execution with Inventory Cost

Abstract

We consider the problem of optimal liquidation of a position in a risky security quoted in a financial market, where price evolution is risky and trades have an impact on price as well as uncertainty in filling orders. We generalize the Almgren and Chriss model by adding extra features that model the market maker’s impact on the price by an Ornstein-Uhlenbeck process. During execution, market makers are assumed to mean revert their inventories to a preassigned capacity. The market is populated by a multiplicity of market makers with heterogeneous mean reversion time-scales. The stochastic control problem can be solved by dynamic programming approach. We first solve analytically the related HJB equation finding the value function. Then we apply verification techniques to obtain the optimal allocation strategy in the feedback form and to study its properties. In the limit as the spectrum of market makers’ mean reversion rates approaches a gamma distribution, a volume-weighted average price execution under the resulting model generates a power-law expected execution price path. If time permits, we also discuss the extension of the problem to a trader maximizing a risk-adjusted profit and loss function.

Bio:

Marina Di Giacinto received the Ph.D. degree in Applied Mathematics from Sapienza University of Rome. She is currently a tenured faculty member of the Department of Economics and Law at the University of Cassino. She holds the National Qualification for Associate Professorship since 2018. She has been visiting the Laboratoire CEREMADE at the Université Paris IX Dauphine and the Mathematics Department at Baruch College of The City University of New York. Her research interests include the deterministic and stochastic optimal control theory applied to Economics, Finance and Insurance. Her papers are published in leading peer-reviewed journals like Finance and Stochastics, European Journal of Operational Research, Journal of the Operational Research Society, and Quantitative Finance.

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

Brooklyn Quant Experience Lecture Series: Harvey Stein

Brooklyn Quant Experience Lecture Series, NYU TandonDear All,

You are cordially invited to the Brooklyn Quant Experience Lecture Series (BQE) on Thursday, February 13th at 6PM in LC 400, Dibner Building, 5 MetroTech Center – 4th Floor.

Dr. Harvey Stein will present a talk on the following topic:

Title:

A Unified Framework for Default Modeling

Abstract

Credit risk models largely bifurcate into two classes — the structural models and the reduced form models. Attempts have been made to reconcile the two approaches by adjusting filtrations to restrict information, but they are technically complicated and tend to approach filtration modification in an ad-hoc fashion.

Here we propose a reconciliation inspired by actuarial science’s approach to survival analysis. We model the survival curve and hazard rate curve as stochastic processes. This puts default models in a form resembling the HJM framework for interest rates, yielding a unified framework for default modeling.

Predictability of default has a simple interpretation in this framework. The framework enables us to disentangle predictability and the distribution of the default time from calibration decisions such as whether to use market prices or balance sheet information. It supplies a formal framework for combining models, yielding a simple way to define new default models.

Bio:

Dr. Harvey J. Stein is Head of the Quantitative Risk Analytics Group at Bloomberg, responsible for Bloomberg’s market risk and credit risk models. Dr. Stein is well known in the industry, having published and lectured on mortgage backed security valuation, CVA calculations, interest rate and FX modeling, credit exposure calculations, financial regulation, and other subjects. Dr. Stein is also on the board of directors of the IAQF, an adjunct professor at Columbia University, a board member of the Rutgers University Mathematical Finance program and of the NYU Enterprise Learning program, and organizer of the IAQF/Thalesians financial seminar series. He received his BA in mathematics from WPI in 1982 and his PhD in mathematics from UC Berkeley in 1991.

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