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Seminar, Uncategorized

Brooklyn Quant Experience Lecture Series: Steve Heston

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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, September 24th at 6 p.m. on Zoom.

Attend Virtually >>

*Please note a meeting password is required for this event.
Meeting ID:971 5155 1289
Password: BQESH

Dr. Steve Heston, Professor of Finance at the University of Maryland, College Park, will give the following talk:

Title:

Option Momentum

Abstract

This paper computes exact returns on equity-V IX option portfolios to investigate momentum in options across different S&P 500 stocks. Stock options with high historical returns continue to outperform options with low returns. This predictability has a quarterly pattern, resembling the pattern of stock momentum found by Heston and Sadka (2008). In contrast to stock momentum, option momentum lasts for up to five years and does not reverse.

The profitability of option momentum is distinct from the profitability of option value, as measured by historical variance divided by current equity-V IX price. It is also not explained by systematic risk, stock characteristics, nor bid-ask spreads.

Bio:

Steve Heston graduated with a BS double major in Mathematics and Economics from the University of Maryland, College Park in 1983. He attended the Graduate School of Industrial Administration and earned an MBA in 1985 followed by a Ph.D. in Finance in 1990. He has held previous faculty positions at Yale, Columbia, Washington University, and the University of Auckland in New Zealand. He has worked in the private sector with Goldman Sachs in Fixed Income Arbitrage and in Asset Management Quantitative Equities. He is known for analyzing options with stochastic volatility and international stock risk.

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Brooklyn Quant Experience Lecture Series: Jon Hill

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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, September 17th at 6 p.m.  on Zoom.

Attend Virtually >>

*Please note a meeting password is required for this event.
Meeting ID:958 8116 1956
Password: BQEJH

Dr. Jon Hill, NYU Tandon Adjunct Professor, will give the following talk:

Title:

A Smarter Model Risk Management Discipline Will Follow From Making Smarter Models

Abstract

What if a financial firm decided to delete its entire set of models and redevelop them from scratch. What might it do differently in the process of rebuilding its entire model eco-system in order to avoid and leverage from some of its previous mistakes? How could such a firm make the Model Risk Management (MRM) platform smarter and less resource intensive than it was before?

This article describes one forward-looking possibility for making the manually intensive practice of MRM smarter by building models that are smarter in the sense of having a rudimentary level of ‘self-awareness’. Similar to the ways that tech firms have tracked the usage of their smartphones, cars, laptop computers and printers for many years, active intelligent agents embedded in model source code can support the creation of a dynamic model inventory to serve as a repository of historical data that accurately describes how, when and where a firm’s models are used and to diagram firm-wide inter-dependencies between data and models.

Keywords: model risk management, governance, validation, dynamic model inventory, model usage, transponder function, model-embedded, active intelligent agents, machine learning, big data, SR11-7, OCC2011-16.

Bio:

Jon leads the New York Chapter of the Model Risk Managers International Association. With over twenty years of experience in diverse areas of quantitative finance, Jon is recognized as a subject matter expert in model risk management, governance and validation and is the author of numerous publications on these topics. Jon is also an adjunct professor in NYU’s Financial Risk Engineering Dept. where he teaches a graduate course in Advanced Model Risk Management, Governance and Validation.

Jon holds a Ph.D. in Biophysics from the University of Utah. He is a frequent speaker and chairperson at model risk conferences throughout the US and Europe.

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Financial Engineering Seminar Series

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Adding Optionality

Stevens Institute of Technology

Einstein’s velocity addition formula keeps the “sum” of two velocities inside [-c,c], where c is the speed of light. Similarly, a $1 bet that a security will be priced below a threshold must have a value inside [-1,1] . We explore the consequences of reducing derivative security valuation to a generalized sum. We find in particular that the value of repeated optionality is just repeated generalized summation. As a result, we can value particular kinds of Bermudan options in closed form and hedge them with vanilla.

August 27, 2020

5:00 PM – 6:00 PM
Online Zoom discussion
RSVP >>

Presenter: Peter Carr

Peter CarrDr. Peter Carr has been chair of the finance and risk engineering department at NYU Tandon School of Engineering for the last four years. He also presently serves as a trustee for the National Museum of Mathematics and WorldQuant University. Previously, he had a 20-year career heading quant groups in finance. Prior to joining the financial industry, Dr. Carr was a finance professor at Cornell University, after obtaining his Ph.D. from UCLA in 1989. He has more than 90 publications in academic and industry-oriented journals and serves as an associate editor for eight 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.

About this series

The Financial Engineering Seminar Series is a recurring event featuring thought leaders from industry and academia, who bring their experiences to a variety of important topics in this discipline. For more on financial engineering at Stevens, visit the master’s program homepage.

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[Virtual] Brooklyn Quant Experience Lecture Series: Agostino Capponi

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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 23rd at 6 p.m.  

Attend Virtually >>
*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

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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.  

Attend Virtually >>

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

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Brooklyn Quant Experience Lecture Series (BQE): Peter Carr

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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.  

Attend Virtually >>

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

Seminar

Brooklyn Quant Experience (BQE) Lecture Series: Kimberly Weston

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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

Seminar

Cornell – Citi Financial Data Science Seminars

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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

Seminar

Brooklyn Quant Experience Lecture Series: Marina Di Ciacinto

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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, 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

Seminar

Machine Learning and AI in Wealth Management: A Revolution in the Making

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About this Event

The wealth management industry is going through a revolution: financial advisory firms are facing immense pressure from increased client expectations, mounting regulations with higher demand on disclosure and transparency, and fee compression due increased competition, lowfee products and robo-advisors.

In this talk, we discuss how sound financial analytics, risk management tools and scenario analysis technology can empower firms to develop integrated investment advice that is consistent across the entire wealth life cycle, for thousands of clients. Quantitative engines, leveraging risk analytics, factor models and Machine Learning techniques, provide advisors with interactive tools to understand exposures, attribute performance and manage risks for a single client, a complex family hierarchy or the entire enterprise.

Technology, analytics and AI/ML tools will have a great impact on the wealth management industry, but will not eliminate the need for the “human touch”. Instead, these advances can empower firms to scale up the high-value, human services that will set them apart in an increasingly digital and automated world.

Bio – Dan Rosen

Dan Rosen is the co-founder and CEO of d1g1t, the first enterprise wealth management platform, powered by institutional-grade analytics and risk management tools, that firms to elevate the quality of their advice and demonstrate its value to clients.

An internationally recognized Quant and Fintech entrepreneur, Dan is also an Adjunct Professor of Mathematical Finance at the University of Toronto, and was the first Director of the Center for Financial Institutions at the Fields Institute. He has worked with numerous financial institutions around the world, lectures extensively on risk and portfolio management, financial engineering, and Fintech innovation, and has authored numerous academic and industry publications, as well as several patents. In 2010, he was inducted a Fellow of the Fields Institute for his “outstanding contributions to the Fields Institute, its programs, and to the Canadian mathematical community”.

Dan was the co-founder and CEO of R² Financial Technologies, acquired by S&P Capital IQ in 2012. Prior to this, he was part of the executive team at Algorithmics (acquired by IBM), where he had a successful career over a decade. Dan holds an M.A.Sc. and Ph.D.in Chemical Engineering from the University of Toronto.

March 4, 2020
6:00 PM – 7:00 PM

Manhattan Institute of Management
2 Washington Street
17th Floor
New York, NY 10004

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