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Seminar

October 8, 2019: Cornell-Citi Financial Data Science Seminars

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Featuring Machine Learning experts from Cornell, Citi, and more…

***For those of you who missed Tuesday night’s seminar and wish to see Dr. Miquel Noguer i Alonso’s presentation, the recording is now available.

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 6:10 pm to 7:25 pm. This seminar will NOT be recorded.

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

 

Date: Tuesday, October 8, 2019
Time: 6:10pm – 7:25pm
Speaker: Puneet Singhvi | Citi
Title: “What’s Happening with Blockchain in Financial Markets?”

Abstract

Over the past few years, the financial industry has been actively exploring blockchain and distributed ledger technology (DLT) to assess their impact in various use-cases, identify benefits, and separate the hype from reality. Citi has been an active participant and strategic investor in blockchain initiatives across the ecosystem for nearly 5 years now.

In this presentation, we will discuss real use-cases in active implementation across the financial ecosystem and review key drivers for adoption. These emerging use-cases span product lines and geographies – from the digitization of post-trade activities to transformed market exchanges, and from digitized securities to cash-on-chain models, from collateral mobility to trade finance – across North America, Europe, and Asia. We will discuss areas with tangible benefits, and what have been learnings from failed initiatives. We will also review key emerging issues with the technology and potential areas of opportunity going forward.

Speaker Bio

Puneet is Managing Director and Financial Markets Infrastructure (FMI) head for Citi Institutional Client Group. He is responsible for relationship and key initiatives with FMIs such as Exchanges, Payment Systems, Clearing Houses, and Settlement venues. He also leads Blockchain/DLT and Digital Assets initiatives for the Markets and Securities Services business working actively with FMIs, FinTechs and institutional clients on identifying and delivering solutions.

Puneet has worked at Citi across the developed and emerging markets in various management roles within Citi Markets & Securities Services and Citi Trade & Transaction Services businesses. His roles included leading Citi Global Clearing Payments Product, Citi Foreign Exchange & Derivative Clearing Product Management, Trade Finance and Asset Backed Finance.

He has a Bachelor’s degree in Electronics and Communications Engineering and has completed his post-graduation in management from the Indian Institute of Management.

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, 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”

November 5, 2019
Speaker: Adam Grealish (Betterment)
Title: TBD

November 12, 2019
Quant Finance Forum

Seminar

NYU FRE Lecture Series: Matthias Heymann

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NYU Tandon School of Engineering

Dear All,

You are cordially invited to attend the NYU FRE Lecture Series on Thursday, October 3rd in the Event MakerSpace
(6 MetroTech Center – 1st Floor) at 6 p.m.

Dr. Matthias Heymann will present a talk on the following topic:

Title:

The Adaptive Curve Evolution Model for Interest Rates

Abstract:

In this talk, the speaker presents the key results from his recent book of the same title. The ACE model—in its original form developed by Gregory Pelts and now carefully rephrased, refined, and made more accessible by Matthias Heymann—is the first to combine all of the most desirable analytical properties in one interest rate model: It is low-dimensional (with any dimension n ∈ ℕ\{2}), complete (i.e., it models all tenors), arbitrage-free, highly flexible (it provides 2n+1 discrete parameters, plus the functional noise parameter σ(x,t)), and time homogeneous if desired, and it imposes a lower bound on rates; moreover, it has the rare feat of being unspanned (i.e., its bond price function does not depend on σ), which simplifies calibration. While its original derivation relied on an arsenal of compelling tools borrowed from theoretical physics (in particular, Einstein’s Special Theory of Relativity), the model’s form presented in this talk will only require basic mathematical skills.

Bio:

Matthias Heymann has a Ph.D. in mathematics (2002–07, Courant Institute of Mathematical Sciences, NYU) and did a postdoc in the Duke University Mathematics Department (2007–10). Specializing in probability theory, during his academic career he made contributions related to Wentzell–Freidlin theory, i.e., the study of maximum likelihood transition curves in stochastic dynamical systems with small noise. One of his most notable publications is his monograph “Minimum Action Curves in Degenerate Finsler Metrics — Existence and Properties,” published in Springer’s “Lecture Notes in Mathematics” series.

In 2010 he started working as a quantitative analyst at Goldman Sachs. During this time he began his work on the ACE model, which eventually turned into his second book, whose results are presented in this talk.

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

Seminar

October 2, 2019: FinTech Seminar Series

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Join us on October 2nd for a discussion about Dynamic Replication and Hedging: A Reinforcement Learning Approach presented by Petter Kolm.

About this Event

In this talk we address the problem of how to optimally hedge an options book in a practical setting, where trading decisions are discrete and trading costs can be nonlinear and difficult to model.

Based on reinforcement learning (RL), a well-established machine learning technique we propose a model that is flexible, accurate and very promising for real-world applications. A key strength of the RL approach is that it does not make any assumptions about the form of trading cost. RL learns the minimum variance hedge subject to whatever transaction cost function one provides. All that it needs is a good simulator, in which transaction costs and options prices are simulated accurately.

This is joint work with Gordon Ritter.

Published Paper:
https://jfds.iijournals.com/content/1/1/159

View Peter Kolm’s Profile.

 

Location

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

Seminar

September 30, 2019: Bloomberg Quant Seminar Series

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Bloomberg Quant (BBQ) Seminar Series | September 30, 2019

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, Jerome Pesenti 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

Jerome PesentiJerome Pesenti
VP, Artificial Intelligence
Facebook
Approaching AI at scale

Facebook is currently using AI across its family of apps to benefit billions of people around the world. VP of AI Jerome Pesenti will speak to how Facebook approaches deploying AI at this scale, the challenges to successfully doing so, and the specific tools and techniques that can help other businesses solve for these issues.

Agenda

  • 5:00pm – Check-in
  • 5:30pm – Keynote:
    Jerome Pesenti, VP, Artificial Intelligence, Facebook
  • 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.
    Including “An Upper Bound for VIX” by Peter Carr
  • 7:00pm – Cocktail reception

When & Where

Monday, September 30, 2019
5:00pm – 8:00pm EDT

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

Seminar

September 24, 2019: Cornell-Citi Financial Data Science Seminars: Miquel Noguer i Alonso (Artificial Intelligence Finance Institute)

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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 6:00 pm to 7:00 pm. 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, September 24, 2019
Time: 6:10 pm – 7:25 pm
Speaker: Miquel Noguer I Alonso, PhD | Artificial Intelligence Finance Institute
Title: “Latest Developments in Deep Learning in Finance”

Miguel Noguer i Alonso

Miquel Noguer i Alonso is a financial markets practitioner with more than 20 years of experience in asset management, and he is the Founder of Artificial Intelligence Finance Institute. Head of Development at Global AI (Big Data Artificial Intelligence in Finance company) and Head on Innovation and Technology at IEF. He worked for UBS AG (Switzerland) as Executive Director. He is a member of European Investment Committee for the last 10 years. He worked as a Chief Investment Officer and CIO for Andbank from 2000 to 2006. He started his career at KPMG.

He is Adjunct Professor at Columbia University teaching Asset Allocation, Big Data in Finance and Fintech. He is also Professor at ESADE teaching Hedge Fund, Big Data in Finance and Fintech. He taught the first Fintech and Big Data course at the London Business School in 2017.

He received an MBA and a Degree in business administration and economics in ESADE in 1993. In 2010 he earned a PhD in quantitative finance with a Summa Cum Laude distinction (UNED – Madrid Spain). He completed a Postdoc in Columbia Business School in 2012. He collaborated with the Mathematics department of Fribourg during his PhD. He also holds the Certified European Financial Analyst (CEFA) 2000.

His research interests range from asset allocation, big data, machine learning to algorithmic trading and Fintech. His academic collaborations include a visiting scholarship in Columbia University in 2013 in the Finance and Economics Department, in Fribourg University in 2010 in the mathematics department, and giving presentations in Indiana University, ESADE and CAIA and several industry seminars like the Quant Summit USA 2017 and 2010.

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, 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

Upcoming CFEM Events

October 8, 2019
Speaker & Title TBD

November 5, 2019
Speaker: Adam Grealish (Betterment)
Title: TBD

November 12, 2019
Quant Finance Forum