NYU FRE Lecture Series: Aparna Gupta

NYU Tandon School of Engineering

Dear All,

You are cordially invited to attend the FRE Lecture Series on Thursday, November 7th in LC 400, Bern Dibner Library, 4th Floor (5 MetroTech Center), at 6:00PM.

Dr. Aparna Gupta will present a talk on the following topic:

Title:

Identifying the Risk Culture of Banks Using Machine Learning

Abstract:

We introduce text mining and unsupervised machine-learning algorithms to define the risk culture for U.S. bank holding companies and examine the relation between risk culture and performance. Applying principal component analysis on textually extracted features from 10-K filings identifies uncertainty, litigious and constraining sentiments among risk culture features to be significant in defining risk culture of banks. Cluster analysis of these features proposes three distinct risk culture clusters which we label as good, fair and poor. Consistent with regulatory expectations, sound risk culture in banks is characterized by high profitability ratios, bank stability, lower default risk and good governance.

Bio:

Aparna Gupta is an associate professor of quantitative finance and director of the Center for Financial Studies in the Lally School of Management at Rensselaer Polytechnic Institute. She has been the founding director of the MS program in Quantitative Finance and Risk Analytics at RPI, and holds a joint appointment in industrial and systems engineering in the School of Engineering at RPI. Dr. Gupta has been a visiting researcher at US SEC in Washington DC for two years. Her research interest is in financial decision support, risk management, and financial engineering. She applies mathematical modeling, machine learning and financial engineering techniques for risk management both in technology-enabled network services, such as, energy and renewable energy systems, communication systems, and technology-enabled service contracts, as well as risk management in the inter-connected financial institutions and financial markets. She has worked on several US National Science Foundation funded research projects in financial innovations for risk management. Dr. Gupta’s research has been published in top quantitative finance and operations research journals, and has been awarded various recognitions, including 2018 best paper award of the Financial Management Association and 2019 best paper award at the 17th FRAP Conference. She is the author of the book, Risk Management and Simulation. Dr. Gupta is a member of WFA, FMA, INFORMS, GARP and IAQF, and serves on the editorial board of several quantitative finance and analytics journals. She earned her doctorate from Stanford University and her B.Sc. and M.Sc. degrees in Mathematics from the Indian Institute of Technology, Kanpur.

We look forward to having you join us for the talk and refreshments. Please mark your calendars.

Bloomberg Quant Seminar Series

November 18, 2019, Bloomberg Quant Seminar Series

Please join us for the next installment of the Bloomberg Quant (BBQ) Seminar Series. The seminar takes place every month and covers a wide range of topics in quantitative finance.

In this session chaired by Bruno Dupire, Peter Carr will present his current research, followed by several “lightning talks” of 5 minutes each in quick succession. This format gives the audience the opportunity to be exposed to a wider variety of topics.

Register today to secure your spot at our event – walk-ins cannot be accommodated.

Keynote

Peter Carr
Peter Carr
Finance and Risk Engineering
Department Chair
NYU Tandon School of Engineering

It Was Fifty Years Ago Today

While the seminal contributions of Black Scholes and Merton to options pricing were published in 1973, much was known by them and others in 1969. In this talk, we turn back the clock exactly 50 years and try to determine what was known and not known about pricing options on November 18, 1969.

Agenda

  • 5:00pm – Check-in
  • 5:30pm – Keynote:
    Peter Carr, Finance and Risk Engineering Department Chair, NYU Tandon School of Engineering
  • 6:15pm – Lightning talks:
    A lightning talk is a very short presentation lasting only 5 minutes. Several ones will be delivered in a single session by different speakers in quick succession
  • 7:00pm – Cocktail reception

When & Where

Monday, November 18, 2019
5:00pm – 8:00pm EDT

Bloomberg L.P.
731 Lexington Avenue
7 MPR
New York, NY 10017

Cornell – Citi Financial Data Science Seminar

You and your colleagues are invited to attend the Cornell – Citi Financial Data Science Seminars at the Bloomberg Center at Cornell Tech, Room 061/071. Through the talks this semester, we are excited to collaborate with Citi in highlighting machine learning applications in finance.

2 West Loop Road
New York, NY 10044

All seminars are from 6:10pm to 7:25pm. 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: Tuesday, November 5, 2019
Time: 6:10 pm – 7:25 pm
Speaker: Adam Grealish | Betterment
Title: “An Algorithmic Approach to Personal Investing”

Abstract: In this talk we will explore how technology can be used to improve investor outcomes. Technology and automation can play a significant role in solving traditional asset management problems, such as risk management and rebalancing. Additionally, taxable investing offers a number of opportunities to generate outperformance after tax, not considered in the management of pre-tax portfolios. We will explore various strategies for tax efficient portfolio management, how they can be formulated as mathematical problems and how they can be efficiently implemented in algorithmic frameworks. We will also explore how technology and design can improve investor behavior.  

Speaker Bio

Adam Grealish is the Director of Investing at Betterment, the largest independent online financial advisor with over $15 billion in AUM. Adam and his team are responsible for Betterment’s strategic asset allocation, fund selection, automated portfolio management and tax strategies. Before joining Betterment, Adam founded a natural language processing startup that matched individuals with employment opportunities. Prior to that, he was a vice president at Goldman Sachs’ FICC division, responsible for structured corporate credit and macro credit trading. Earlier in his career, Adam was part of the global quantitative equity portfolio management team at New York Life Investments.

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, bronze building, which is the Bloomberg Center. Check in at the front desk and go downstairs to the basement, where Room 061/071 will be straight ahead on your left.

**Please excuse any duplication of this announcement

Past CFEM Events

September 24, 2019
Speaker: Dr. Miquel Noguer I Alonso I Artificial Intelligence Finance Institute
Title: “Latest Developments in Deep Learning in Finance”

October 8, 2019
Speaker: Puneet Singhvi I Citi
Title: “What’s Happening in Blockchain in Financial Markets?”

Upcoming CFEM Events

November 12, 2019
Quant Finance Forum
Title: “Big Data and Big Responsibility: The New Frontier of ESG”

NYU FRE Lecture Series: Pasquale Cirillo

NYU Tandon School of Engineering

Dear All,

You are cordially invited to attend the FRE Lecture Series on Thursday, October 31st, 6 MetroTech Center),at 6:00PM.

Dr. Pasquale Cirillo will present a talk on the following topic:

Title:

The Distortions of Finance

Abstract:

Finance is a world of distortions. Many tools we use, many findings we know are actually the result of a distortion. Take the well-known Black-Scholes model: the probability to be in the money at maturity under P and Q is a distortion. And the price of a European call? Another distortion. Consider risk management, think about the expected shortfall, and—guess what—a distortion. And if you think that copulas are immune, you are wrong, plenty of distortions there. Model risk is often represented in terms of distortions. So, let’s talk about distortions, and in particular about the special class of Lorenz transforms.

Bio:

Pasquale Cirillo is associate professor of applied probability at Delft University of Technology, The Netherlands, where he also coordinates the Financial Engineering Specialization of the Master in Applied Mathematics. His research interests include quantitative risk management (in particular credit and operational risk), extreme value theory and combinatorial stochastic processes. Besides the academic career, as a statistical consultant, he has collaborated with international institutions, like the World Bank and the European Food Safety Authority, and many private companies and banks.
His MOOCs in risk management have been attended by more than 110’000 students from all over the world. He is a proud amateur cook.

We look forward to having you join us for the talk and refreshments. Please mark your calendars.

NYU Courant: Mathematical Finance Seminar

The mathematical finance seminar covers a broad range of topics in mathematical and quantitative finance, including:

  • Data science and machine learning in finance
  • Big data and econometric techniques
  • Quantitative finance
  • Portfolio and risk management
  • Pricing and risk models
  • Regulation and regulatory models
  • Trading strategies and back testing

Presenters include invited visitors and NYU Courant faculty. A seminar presentation often covers original research. The seminar meets monthly on Tuesdays at 5:30 pm to 7 pm in room 1302 of Warren Weaver Hall at 251 Mercer Street, unless specified otherwise. Please make sure to check the exact schedule and room assignment. Talks generally last an hour, followed by networking.

Seminars are open to the public.

The seminar coordinator is Petter Kolm (email: petter DOT kolm AT nyu DOT edu).

Seminar Organizer(s): Petter Kolm


Tuesday, October 29, 2019
5:30PM, Warren Weaver Hall 1302
Relearning the Lessons of the Global Financial Crisis
David M. Rowe, President of David M. Rowe Risk Advisory

NYU Courant: Mathematical Finance Seminar

The mathematical finance seminar covers a broad range of topics in mathematical and quantitative finance, including:

  • Data science and machine learning in finance
  • Big data and econometric techniques
  • Quantitative finance
  • Portfolio and risk management
  • Pricing and risk models
  • Regulation and regulatory models
  • Trading strategies and back testing

Presenters include invited visitors and NYU Courant faculty. A seminar presentation often covers original research. The seminar meets monthly on Tuesdays at 5:30 pm to 7 pm in room 1302 of Warren Weaver Hall at 251 Mercer Street, unless specified otherwise. Please make sure to check the exact schedule and room assignment. Talks generally last an hour, followed by networking.

Seminars are open to the public.

The seminar coordinator is Petter Kolm (email: petter DOT kolm AT nyu DOT edu).

Seminar Organizer(s): Petter Kolm


Tuesday, October 22, 2019
5:30PM, Warren Weaver Hall 1302
Increasing After-tax Returns in Wealth Management – Tax Optimization
Eric Bronnenkant, Head of Tax, Betterment

NYU FRE Lecture Series: Nassim Nicholas Taleb

NYU Tandon School of Engineering

Dear All,

You are cordially invited to attend the FRE Lecture Series on Thursday, October 24th in the Pfizer Auditorium  on the 1st Floor of the Dibner Library (5 MetroTech Center) at 6:30PM.

Dr. Nassim N. Taleb will present a talk on the following topic:

Title:

The Statistical Consequences of Fat Tails

Abstract:

While everyone seems to be aware of Fat Tailedness, little has been done to take them into account in statistical inference, particularly where it cancels current methods in use. Modern Portfolio Theory, for instance, becomes merely a rent seeking academic exercise. We present the contradictions with conventional tools used in statistics and risk management and propose solutions. The discussion is presented in a book found at: https://www.academia.edu/37221402/STATISTICAL_CONSEQUENCES_OF_FAT_TAILS_TECHNICAL_INCERTO_COLLECTION_

Bio:

Nassim Nicholas Taleb was an options trader for 23 years before starting a career as a researcher dealing with mathematical, philosophical, and, mostly, practical problems with probability. He is currently the Distinguished Professor of Risk Engineering at NYU’s Tandon School of Engineering.

We look forward to having you join us for the talk and refreshments. Please mark your calendars.

NYU FRE Lecture Series: John Crosby

NYU Tandon School of Engineering

Dear All,

You are cordially invited to attend the FRE Lecture Series on Thursday, October 17th in the Pfizer Auditorium  on the 1st Floor of the Dibner Library (5 MetroTech Center) at 6PM.

Dr. John Crosby will present a talk on the following topic:

Title:

Unspanned Risks, Negative Local Time Risk Premiums, and Empirical Consistency of Models of Interest-Rate Claims

Abstract:

We formalize the notion of local time risk premium in the context of a theory in which the pricing kernel is a general diffusion process with spanned and unspanned components. We derive results on the expected excess return of options on bond futures. These results are organized around our new empirical finding that the average returns of out-of-the-money puts and calls on Treasury bond futures are both negative. Our theoretical reconciliation warrants a negative local time risk premium, and our treatment considers models with market incompleteness and sources of volatility uncertainty. Our results provide a way to differentiate between the myriad of term-structure models.

Bio:

John gained a first class honours degree in Mathematics at Girton College, Cambridge University before going on to study Electrical Engineering at University College, Oxford University. He was in investment banking (Barclays, Lloyds, UBS) for some 20 years working as a quant, heading quant teams and trading foreign exchange options.
More recently, John has moved into academia. He is at the Smith School of Business, University of Maryland. He is best known for publishing a number of papers on the theme of international risk sharing, exchange rates, term-structure modelling and incomplete markets (for example, one paper recently published at the Review of Financial Studies).

We look forward to having you join us for the talk and refreshments. Please mark your calendars.

October 16, 2019: IAQF/Thalesians – Systematic Strategies and Machine Learning

IAQF Upcoming Event

Systematic Strategies and Machine Learning

 

Kevin Noel

A Talk by
Kevin Noel

Wednesday, October 16

5:45 PM Registration
6:00 PM Seminar Begins
7:30 PM Reception

Abstract

Systematic strategies have a long history in the field of investment area, encompassing the high-frequency ones as well as low-frequency strategies. Over the last decade, the rise of ETF, Robo-allocator made them a popular choice compared to discretionary strategies. More recently, progresses in machine learning renew the theoretical development in that field as well as highlight new perspectives.

Here, we focus on low-frequency strategies and first recall briefly the history of such strategies through a common statistical framework (dynamic basket allocation): Markowitz, CPPI, Buy-Write, Vol. Control, Risk Budgeting, Factor-based, Arbitrage based,… We illustrate those strategies through actual use cases and highlight the importance of underlying risk framework.

In the second part, we focus on the various machine learning methods available to develop or optimize systematic strategies. Especially, we underline the paradigm difference with traditional statistical/stochastic methods by deepening on the fundamental concept of learning vs calibration, as well as the role of prior knowledge.

In the final part, we will evoke some potential future research to go beyond the paradigm of covariance matrix: neural control, graph representation learning.

Biography

Kevin Noel is graduated from Ecole Centrale, in financial mathematics and data mining. From 2007, He worked at BNP Paribas and then at US bank Merrill Lynch on developing advanced statistical framework and risk solutions for Institutional Investor systematic strategies in Asia/Japan. Among those solutions: volatility based, arbitrage Premium, dynamic replication of mutual/ hedge funds, long short… Then, at ING Japan, he co-leads in Re-Insurance hedging/valuation of large scale Japanese Variable Annuities, modeling complex insurance derivatives product, as well as complex modeling of optimal end-user decision process. For the latter, he started to develop machine learning and data analytics for semi-structured, unstructured data, decided to pursue research in Machine Learning/Deep learning applied to optimality or in information processing. He joined Rakuten as Principal Data Scientist and is working on solutions for unstructured or semi-structured Big Data.

Acknowledgments
Special thanks to the Fordham University Gabelli School of Business for hosting and sponsoring the seminar.

About the Series
The IAQF’s Thalesians Seminar Series is a joint effort on the part of the IAQF (www.iaqf.org) and the Thalesians (www.thalesians.com). The goal of the series is to provide a forum for the exchange of new ideas and results related to the field of quantitative finance. This goal is accomplished by hosting seminars where leading practitioners and academics present new work, and following the seminars with a reception to facilitate further interaction and discussion.

Registration Fees:

Complimentary for IAQF members
Login and Register

Thalesians Members can register for $25

Non-Members: $25.00 by registering

NYU FRE Lecture Series: Mykhaylo Shkolnikov

NYU Tandon School of Engineering

Dear All,

You are cordially invited to attend the NYU FRE Lecture Series on Thursday, October 10th in the Dibner Auditorium
(5 MetroTech Center – 1st Floor) at 6 p.m.

Dr. Mykhaylo Shkolnikov will present a talk on the following topic:

Title:

From Systemic Risk to Supercooling and Back

Abstract:

I will explain how structural models of default cascades in the systemic risk literature naturally lead to the supercooled Stefan problem of mathematical physics. On the one hand, this connection allows us to uncover a notion of global solutions to the supercooled Stefan problem, which we analyze in detail. On the other hand, the supercooled Stefan problem formulation allows to provide a truly intrinsic definition of systemic crises and to characterize the fragile states of the economy. Time permitting, I will also explain the network and game extensions of the problem. Based on a series of works with Francois Delarue and Sergey Nadtochiy.

Bio:

Mykhaylo (Misha) Shkolnikov is currently an assistant professor in the Department of Operations Research and Financial Engineering, an affiliated faculty member with the Bendheim Center for Finance, and an associated faculty member with the Program in Applied & Computational Mathematics (PACM) at Princeton University. Prior to that, he was an assistant professor in the Department of Mathematics at Princeton and a postdoctoral fellow at the University of California, Berkeley and MSRI. He earned his PhD in mathematics at Stanford University. Shkolnikov is the recipient of the 2018 Erlang Prize from the Applied Probability Society of INFORMS and of the 2019 Early Career Prize from the SIAM Activity Group on Financial Mathematics and Engineering. His research focuses on stochastic portfolio theory (and, more generally, optimal investment), interacting particle systems, random matrix theory, as well as probabilistic approaches to partial differential equations.

We look forward to having you join us for the talk and refreshments. Please mark your calendars.

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.