Tag Archives: Seminar

Seminar

Brooklyn Quant Experience Lecture Series: Dhruv Madeka

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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 6th at 6PM in LC 400, Dibner Building, 5 Metrotech Center – 4th Floor.

Dr. Dhruv Madeka who will present a talk on the following topic:

Title:

Practical Deep Reinforcement Learning

Abstract

We present a Deep Reinforcement Learning approach to solving a dynamic periodic review inventory system with stochastic vendor lead times, lost sales, correlated demand, and price matching. While this dynamic program has historically been considered intractable, we show that different policy learning approaches are competitive or outperform classical baseline policies. In order to train these algorithms, we develop techniques to convert historical data into off-policy data for a simulator.

Bio:

Dhruv Madeka is a Senior Machine Learning Scientist at Amazon. His current research focuses on applying Deep Reinforcement Learning to inventory management problems. Dhruv has also worked on developing generative and supervised deep learning models for probabilistic time series forecasting. In the past – Dhruv worked in the Quantitative Research team at Bloomberg LP, developing open source tools for the Jupyter Notebook and conducting advanced mathematical research in derivatives pricing, quantitative finance and election forecasting.

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

Seminar

Brooklyn Quant Experience Lecture Series: Milind Sharma

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Brooklyn Quant Experience Lecture Series, NYU Tandon

Dear All,

We are delighted to announce the new Brooklyn Quant Experience (BQE) Lecture Series (formerly known as the FRE Lecture Series), which will begin Thursday, January 30th at 6PM in the Event MakerSpace, 6 Metrotech Center, 1st Floor.

To kickoff our first lecture this spring, we have invited Dr. Milind Sharma who will present a talk on the following topic:

Title:

From Smart Betas to Smart Alphas

Bio:

Milind Sharma’s 24 years of market experience span running prop desks at RBC & Deutsche Bank (Saba unit) as well as hedge funds (QuantZ) & mutual funds (MLIM) not to mention his fintech venture QMIT. His funds have won many awards over the years including those from Morningstar, Lipper, WSJ, Battle of the Quants & BattleFin. He was also a co-founder of Quant Strategies at MLIM (now BlackRock) & Manager of the Risk Analytics and Research Group at Ernst & Young where he was co-architect of Raven TM. His publications have appeared in Risk, JoIM, Elsevier, World Scientific, Wiley etc. In addition to dual MS degrees he was also in the Logic/ AI PhD program at Carnegie Mellon. Other education includes Oxford, Vassar & Wharton.

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

Seminar

FinTech Seminar Series

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FinTech Applications of AI & Machine Learning in B2B space

With its formidable datasets within domain sets like credit default, economic, security ratings, firmographic & people data, Moody’s is well positioned to develop new products to serve the needs of its clients. The Moody’s Analytics Accelerator group aims to identify, research and develop new business products for new clients and new markets using sophisticated AI & Machine learning techniques that are now ubiquitous in the Consumer space. This talk will focus on how we have brought to market products in the Compliance, Loan Origination, Financial Spreading and Commercial Real Estate domains.

Bio

Rakesh Parameshwar is a Senior Director for Strategy & Innovation in the Moody’s Analytics Accelerator (MAA) group. The MAA group aims to identify, research, and develop new business opportunities, with a special focus on emerging technologies like AI & ML. Before joining Moody’s Analytics in 2018, he was in charge of business strategy and product development for Bloomberg’s Desktop API, Alerts and Quant Solutions group. Prior to this, he had extensive experience working for global banks where he advised clients with risk management solutions and built technology solutions. Rakesh has an MBA from NYU Stern, a Bachelor’s degree in Electrical Engineering from IIT Kharagpur in India and a certificate in Quantitative Finance (CQF)

When

Wednesday January 29, 2020
6 PM – 7PM

Where

University of Waterloo @ Manhattan Institute of Management
2 Washington Street, 17th floor
New York, New York

Seminar

NYU Courant: Mathematical Finance Seminar

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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, November 12, 2019
5:30PM 
251 Mercer St.
Warren Weaver Hall 1302
Model Risk Management for Alpha Strategies created with Deep Learning
Ben Steiner, Global Fixed Income, BNP Paribas Asset Management

Seminar

NYU FRE Lecture Series: Aparna Gupta

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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.

Seminar

Bloomberg Quant Seminar Series

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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

Seminar

Cornell – Citi Financial Data Science Seminar

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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”

Seminar

NYU FRE Lecture Series: Pasquale Cirillo

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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.

Seminar

NYU Courant: Mathematical Finance Seminar

Leave a comment

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

Seminar

NYU FRE Lecture Series: Nassim Nicholas Taleb

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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.