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

Seminar

Cornell – Citi Financial Data Science Seminars

February 27, 2020 Novicki 1 Comment

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.

RSVP

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

February 24, 2020 Novicki Leave a comment

Dear 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

February 19, 2020 Novicki 1 Comment

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

Seminar

Brooklyn Quant Experience Lecture Series: Claudio Tebaldi

February 18, 2020 Novicki Leave a comment

Dear All,

You are cordially invited to the Brooklyn Quant Experience Lecture Series (BQE) on Thursday, February 20th at 6PM in the Event MakerSpace – 6 MetroTech Center, 1st Floor.

Dr. Claudio Tebaldi will present a talk on the following topic:

Title:

Arbitrage Pricing Implications of Cascade Risk

Abstract

Traditional approach to valuation by (no) arbitrage has focused on the impact on prices of systematic risk factors. In fact firm-specific risks are assumed to be completely diversifiable. In our research we reconsider intertemporal asset pricing in an economy where distress shocks can propagate through a network of inter-firm connections. It can be shown under general conditions that two classes of equilibria emerge. In the first, firm-specific shocks are diversifiable and do not affect investor expectations. In the second, they generate non-diversifiable cascades that amplify arbitrage risk giving rise to a risk premium component not accountable by any systematic factor. We analyze the impact of cascades on stock and option prices and expected returns. We exemplify our findings focusing on the pricing of claims written on assets of financial intermediaries connected by a network of debt-credit claims.

Bio:

Claudio Tebaldi is a tenured faculty member of the Department of Finance, L. Bocconi University Milano. Associate professor in the field of Quantitative Methods for Economics, Finance and Insurance since 2011, he holds the National Qualification for Full Professorship since 2015. He is a fellow of IGIER and Baffi-CAREFIN research centers and has been Visiting Scholar at UCLA Anderson School of Business. His research interests range in the areas of Derivative, Asset pricing and Portfolio management. His papers are published in leading peer-reviewed journals like the Review of Financial Studies, Mathematical Finance, Journal of Financial and Quantitative Analysis and Journal of Econometrics and two of them have been awarded: one in September 2019 by the Canadian Derivatives Institute as Best Paper in Derivatives of the Northern Finance Association Meeting, one in January 2007 as Best Paper of the Swiss Econometrics and Finance Society Meeting. He is currently serving as Managing Editor of 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

Discussion

Breakfast Roundtable with the IAQF Senior Fellows

February 11, 2020 Novicki Leave a comment

Conversation with Cliff Asness, Douglas Breeden,

Peter Carr, & Emanuel Derman

Friday, February 28th

8:30am Registration & Light Breakfast

9:00-10:00am Roundtable Discussion

The Cornell Club of New York

6 East 44th Street

New York, NY

Brooklyn Quant Experience Lecture Series: Harvey Stein

February 11, 2020 Novicki Leave a comment

Dear 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.

Seminar

Brooklyn Quant Experience Lecture Series: Dhruv Madeka

February 3, 2020 Novicki Leave a comment

Dear 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.

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.

Quantitative Finance Weekly Seminar

Monthly Archives: February 2020

Brooklyn Quant Experience (BQE) Lecture Series: Kimberly Weston

Title:

Abstract

Bio:

Cornell – Citi Financial Data Science Seminars

Brooklyn Quant Experience Lecture Series: Marina Di Ciacinto

Title:

Abstract

Bio:

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

About this Event

Bio – Dan Rosen

Brooklyn Quant Experience Lecture Series: Claudio Tebaldi

Title:

Abstract

Bio:

Breakfast Roundtable with the IAQF Senior Fellows

Brooklyn Quant Experience Lecture Series: Harvey Stein

Title:

Abstract

Bio:

Brooklyn Quant Experience Lecture Series: Dhruv Madeka

Title:

Abstract

Bio:

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.

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