Monthly Archives: March 2021

Seminar

Brooklyn Quant Experience Lecture Series: Maggie Copeland

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Brooklyn Quant Experience Lecture Series, NYU Tandon

Maggie Copeland, NYU Tandon FRE Adjunct Professor, will give the following talk on Thursday, April 1st at 9:30 AM EST. 
*Kindly note that we have changed the time to 9:30 AM on Thursdays. The new time change allows our invited international guests to join these important virtual talks.

Attend Virtually >>

Meeting ID: 940 5574 7877
Password: FREBQEMC

Title

A Tale of Two Tails: Size, Volatility and Uncertainty

Abstract

We derive the firm’s equity valuation mainly by focusing on the two tails that involve optionality. The equity shareholders possess two call options on the firm’s equity value. An upside potential benefit call and a downside risk protection call represent these two tails of the firm. An optimal capital structure could be derived from these two classes of call options. Navigate the SIZE and Volatility portfolios show resulting significant effects on the tails. Furthermore, we show that they are highly significantly correlated with uncertainty indices such as EPU and/or VIX.

Bio

Maggie is an adjunct professor at NYU Tandon, Department of Finance and Risk Engineering. During her long career, she has been a trader and hedge fund manager for long short, market neutral and long only funds. She was a Hedge Fund Portfolio Manager and Trader at Paloma Securities and Salomon Smith Barney Group, a Vice President of proprietary trading at NatWest Securities, a Proprietary Trader at Bear Stearns, a Senior Risk Manager at Fidelity Investments, and a Partner and Portfolio Manager at Roll and Ross Asset Management.

Maggie was the first woman to receive a Ph.D. in Finance, with a minor in Math, from the University of California Los Angeles (UCLA). She has publications in Financial Analysts Journal, Financial Management, and The Journal of Portfolio Management. Her professional public speeches include the D.E Shaw Hedge Fund conference, the Dow Jones Global Conference, and the International Risk Management Conference.

Seminar

Cornell – Citi Financial Data Science Webinars

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Cornell Engineering. Operations Research and Information Engineering. Financial Engineering Manhattan

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

You and your colleagues are invited to attend the Cornell – Citi Financial Data Science Webinars. Through the online talks in Spring 2021, we are excited to collaborate with Citi in highlighting machine learning applications in finance.

All webinars are from 5:00 pm to 6:00 pm EST.

This webinar is free and open to all guests. Registration is required (RSVP). You will receive the webinar link and dial-in info upon registration (the confirmation email will come from
no-reply@zoom.us)

Date: Tuesday, April 13th, 2021
Time: 5:00 pm – 6:00 pm EST
Speaker: Peter Carr | NYU (with Lorenzo Torricelli of the University of Parma)
Title: “Stoptions”

Abstract

We introduce a new derivative security called a stoption. After paying an upfront premium, the owner of a stoption accrues realized price changes in some underlying security until the flow is stopped by the owner. Upon stopping, the reward is the sum of all of the previous price changes plus a deterministic amount which can vary with the stopping time. Stoptions are finite-lived and hence must be stopped at or before a fixed maturity date. We propose dynamics under which we can determine the optimal stopping strategy and value the stoption premium in closed-form. We also present an application to DVA (debit valuation adjustment) under full collateralization.

Program Agenda:

  1. Peter Carr’s Presentation
  2. Q&A
  3. “Lightning Talk” – featuring Lorenzo Torricelli
  4. Discussion

Speaker Bio

Dr. Peter Carr is the Chair of the Finance and Risk Engineering Department at NYU Tandon School of Engineering. Prior to his academic appointment as a professor, he 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.

“Lightning Talk” Info:

In this pre-recorded video, Lorenzo Torricelli will briefly introduce the logistic and Dagum additive martingale option pricing models and visually illustrate some of their probabilistic aspects: probability density functions, cumulant term structures, and implied volatility surfaces.

Bio: Lorenzo Torricelli is assistant professor at the Department of Economics and Management of the University of Parma. His main research interests are the financial applications of stochastic time changes, tempered processes, and subdiffusive processes. He previously worked at LMU Munich as a research fellow and at the Italian pension fund regulatory authority (COVIP).

We hope to see you online!

The Cornell-Citi Team

**Please excuse any duplication of this announcement

If you are interested in our past seminars, you are welcome to subscribe to our YouTube Channel and watch our videos!

Past CFEM Events

February 16th, 2021
Speaker: Charles-Albert Lehalle (Capital Fund Management)
Title of Presentation: “An Attempt to Understand Natural Language Processing and Illustration on a Financial Dataset”

March 9th, 2021
Speaker: Bruno Dupire (Bloomberg)
Title of Presentation: “Some Applications of Machine Learning in Finance”

Upcoming CFEM Events

May 11th, 2021
Speaker: TBD
Title of Presentation: TBD

Seminar

Brooklyn Quant Experience Lecture Series: Leon Tatevossian

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Brooklyn Quant Experience Lecture Series, NYU Tandon

Leon Tatevossian, NYU Tandon FRE Adjunct Professor, will give the following talk on Thursday, March 25th at 9:30 AM EST. 
*Kindly note that we have changed the time to 9:30 AM on Thursdays. The new time change allows our invited international guests to join these important virtual talks.

Attend Virtually >>

Meeting ID: 949 0708 1079
Password: FREBQELT

Title

Can We Still Blame MBS Hedgers?

Abstract

Part of fixed-income folklore is the idea that directional moves in the rates markets can get exaggerated by the duration-rebalancing decisions of mortgage-backed security (MBS) investors and market-makers.  Under stable regimes, we could posit that this theme resides in the market’s “background noise.”  In those backdrops, there’s a consensus toolkit for interpreting its effect and how it fits with other price drivers.  In periods of harder-to-rationalize repricings in rates space this “convexity effect” attracts more attention:  The risk attributes (such as the distribution across the coupon “stack”) of the outstanding “stock” of MBSs and the sector’s relative value are major determinants of the rebalancing strategy, and thus of the effect’s magnitude.

The advent of the Fed’s quantitative easing (QE) programs (currently taking $40 billion of agency MBSs out of private hands per month, net of principal redemptions) and the continuing sell-down of GSE’s balance sheets mean that there’s a significantly reduced amount of MBS paper held by “players who hedge.”  Can we still blame the MBS hedgers when we experience greater-than-expected rates volatility?

Bio

Leon Tatevossian is a fellow/adjunct instructor in the Mathematics in Finance Program at NYU-Courant Institute. From 2009-16, Leon was a director in Group Risk Management at RBC Capital Markets, LLC, covering market risk for securitized products in secondary-trading, origination, and proprietary-trading areas.  He has twenty-nine years of sell-side experience in the fixed-income markets, including positions as a trader, quantitative strategist, derivatives modeler, and market-risk analyst. His product background includes US Treasury securities, US agency securities, interest-rate derivatives, MBSs, ABSs, and credit derivatives.  Leon graduated from MIT (SB; mathematics); he was a graduate student in mathematics at Brown University.

Seminar

Brooklyn Quant Experience Lecture Series: Viktor Todorov

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Brooklyn Quant Experience Lecture Series, NYU Tandon

Viktor Todorov, Professor of Risk Management and Professor of Finance at the Kellogg School of Management, Northwestern University, will give the following talk on Thursday, March 18th at 9:30 AM EST. 
*Kindly note that we have changed the time to 9:30 AM on Thursdays. The new time change allows our invited international guests to join these important virtual talks.

Attend Virtually >>

Meeting ID: 979 5163 8107
Password: FREBQEVT

Title

Option-Implied Semimartingale Characteristics

Abstract

We propose nonparametric methods for the recovery of the spot semimartingale characteristics of an asset price from noisy short-dated option data. The estimation is based on forming portfolios of options with different strikes that replicate the (risk-neutral) conditional characteristic function of the underlying price in a model-free way. The recovery of spot volatility is done by making use of the dominant role of the volatility in the conditional characteristic function over short time intervals and for large values of the characteristic exponent. The estimation of the tail jump variation measures, on the other hand, is based on their representation as integrals of the Laplace transforms of the jump compensator. The latter are in turn recovered from the second derivative of the option-implied characteristic function estimate, de-biased by its value at high frequencies to account for the diffusive volatility. We apply the estimation techniques to real data and illustrate the use of the extracted option-implied semimartingale characteristics in asset pricing applications.

Bio

Viktor Todorov is Harold H. Hines Jr. Professor of Risk Management and Professor of Finance at the Kellogg School of Management, Northwestern University. Professor Todorov is a Fellow of the Society for Financial Econometrics and the Journal of Econometrics. His research interests are in the areas of theoretical and empirical asset pricing, econometrics, and applied probability. He has published extensively in these fields.

His recent work focuses on the robust estimation of asset pricing models using high-frequency financial data as well as the development and application of parametric and nonparametric methods of inference for studying risks and risk premia using derivatives markets data. He currently serves as a Co-Editor for Econometric Theory and is on the editorial board of a number of leading academic journals, including Econometrica and the Journal of Econometrics. He received his Ph.D. in Economics from Duke University in 2007.

Seminar

Brooklyn Quant Experience Lecture Series: Roza Galeeva

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Brooklyn Quant Experience Lecture Series, NYU Tandon

Roza Galeeva, Adjunct Professor, NYU Tandon FRE, will give the following talk on Thursday, March 11th at 9:30 AM EST. 
*Kindly note that we have changed the time to 9:30 AM on Thursdays. The new time change allows our invited international guests to join these important virtual talks.

Attend Virtually >>

Meeting ID: 928 3123 9504
Password: FREBQERG

Title

In Pursuit of Samuelson: Studies of Commodity Volatilities and Correlations

Abstract

Empirical analysis of price returns is an essential component in the valuation methods in any asset class. Energy commodities present unique challenges: seasonality and inventory are crucial for covariance structure; forward price volatility increases dramatically while approaching contract’s expiration: the famous Samuelson effect; liquidity in commodity futures and options liquidity is concentrated at short tenors.

This fact makes the term structure of volatility and correlations very important in pricing and hedging decisions. In this presentation, I give the results of my work with NYU students devoted to this subject. We will follow three goals:

  • Parameterization of Samuelson effect and the calibration procedures for commodities futures, including seasonal commodities as gas and power.
  • Samuelson effect for commodity correlations, parameterizing calendar correlations.
  • Contrast between the traditional Black and its long-ago predecessor Bachelier model in view of recent dramatic events in oil markets in Spring 2020.

Bio

Roza Galeeva has extensive experience of over 18 years with commodity derivatives – modelling, pricing, and risk management. She has been employed at senior levels as a quant at Williams Energy, Northeast Utilities, and most recently, for 13 years, 2005-2018 at Morgan Stanley. She worked at MS in different roles and departments, including the Valuation Group, and later the MS strats and modelling group. Prior to the industry, Roza was teaching courses in mathematics in different countries. She has a PhD from Moscow State University in Mathematical Physics. She published papers in geometry, PDE, dynamical systems, and financial engineering. She made her come back to academia in 2017 at NYU with teaching courses in financial engineering and working with NYU students on research projects on Commodity Derivatives.

Seminar

Cornell – Citi Financial Data Science Webinars

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Cornell Engineering. Operations Research and Information Engineering. Financial Engineering Manhattan

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

You and your colleagues are invited to attend the Cornell – Citi Financial Data Science Webinars. Through the online talks in Spring 2021, we are excited to collaborate with Citi in highlighting machine learning applications in finance.

All webinars are from 5:00 pm to 6:00 pm EST.

This webinar is free and open to all guests. Registration is required (RSVP). You will receive the webinar link and dial-in info upon registration (the confirmation email will come from
no-reply@zoom.us)

Date: Tuesday, March 9th, 2021
Time: 5:00 pm – 6:00 pm EST
Speaker: Bruno Dupire | Bloomberg L.P.
Title: “Some Applications of Machine Learning in Finance”

Abstract

Finance has always tried to make use of all available information to optimize investment decisions. The advent of efficient Machine Learning algorithms, alternative data, and computational powers has deeply impacted many fields in finance. To mention a few, rotation of factors according to market regimes in factor investing, option pricing and hedging, anomaly detection, covariance matrix cleaning, transaction cost analysis. Alternative data include texts from news and tweets, supply chain data, satellite images, vessel routes, weather data, credit card transactions, geolocation data.

This overflow of information opens the door to endless number crunching and apophenia. The desperate search for a signal leads to overfitting and unstable relationships, so beware. As I like to say, the market is a machine made to destroy the signal!

Program Agenda:

  1. Bruno Dupire’s Presentation
  2. Q&A
  3. “Lightning Talk” – Yumeng Ding
  4. Discussion

Speaker Bio

Bruno Dupire is head of Quantitative Research at Bloomberg L.P., which he joined in 2004. Prior to this assignment in New York, he has headed the Derivatives Research teams at Société Générale, Paribas Capital Markets, and Nikko Financial Products where he was a Managing Director. He is best known for having pioneered the widely used Local Volatility model (simplest extension of the Black-Scholes-Merton model to fit all option prices) in 1993 and the Functional Itô Calculus (framework for path dependency) in 2009. He is a Fellow and Adjunct Professor at NYU and he is in the Risk Magazine “Hall of Fame”. He is the recipient of the 2006 “Cutting Edge Research” award of Wilmott Magazine and of the Risk Magazine “Lifetime Achievement” award for 2008.

After a Master’s degree in Artificial Intelligence in 1982 and a Ph.D. in Numerical Analysis in 1985, he has conducted in 1987-88 a study to apply Neural Nets to time series forecasting for Caisse des Dépôts et Consignations. He has been applying Machine Learning to a variety of problems in Finance and has given many lectures on the topic in the Americas, Europe, and Asia over the past few years.

“Lightning Talk” Info:

CFEM alumna Yumeng Ding will discuss her team capstone project, which was titled, “Interpreting Machine Learning Models.” By utilizing Machine Learning interpretability models, the Cornell CFEM team, sponsored by Alliance Bernstein, explored how black-box models can be explained and evaluated in finance. The team analyzed S&P 500 constituents and explored the interpretability of some widely-used ML modes.

Yumeng Ding (MFE Cornell ’20, BA Finance Fudan University‘15) is a soon-to-be analyst in Strategic and Analytics at Deutsche Bank.

We hope to see you online!

The Cornell-Citi Team

**Please excuse any duplication of this announcement

If you are interested in our past seminars, you are welcome to subscribe to our YouTube Channel and watch our videos!

Past CFEM Events

February 16th, 2021
Speaker: Charles-Albert Lehalle (Capital Fund Management)
Title of Presentation: “An Attempt to Understand Natural Language Processing and Illustration on a Financial Dataset”

Upcoming CFEM Events

April 13th, 2021
Speaker: Peter Carr (NYU)
Title of Presentation: Adding Optionality

May 11th, 2021
Speaker: Raja Velu (Syracuse University)
Title of Presentation: TBD

Seminar

Brooklyn Quant Experience Lecture Series: Laura Ballotta

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Brooklyn Quant Experience Lecture Series, NYU Tandon

 Laura Ballotta, Reader in Financial Mathematics at Cass Business School, will give the following talk on Thursday, March 4th at 9:30 AM EST. 
*Kindly note that we have changed the time to 9:30 AM on Thursdays. The new time change allows our invited international guests to join these important virtual talks.

Attend Virtually >>

Meeting ID: 999 3949 8124
Password: FREBQELB

Title

Fourier-based methods for the management of complex insurance products

Abstract

This paper proposes a framework for the valuation and the management of complex life insurance contracts, whose design can be described by a portfolio of embedded options, which are activated according to one or more triggering events. These events are in general monitored discretely over the life of the policy, due to the contract terms. Similar designs can also be found in other contexts, such as counterparty credit risk for example.

The framework is based on Fourier transform methods as they allow to derive convenient closed analytical formulas for a broad spectrum of underlying dynamics. Multidimensionality issues generated by the discrete monitoring of the triggering events are dealt with efficiently designed Monte Carlo integration strategies. We illustrate the tractability of the proposed approach by means of a detailed study of ratchet variable annuities, which can be considered a prototypical example of these complex structured products.

This is joint work with Ernst Eberlein, Thorsten Schmidt and Raghid Zeineddine.

Bio

Laura Ballotta is a reader in Financial Mathematics at Cass Business School, London. She works in the areas of quantitative finance and risk management and has written on topics including stochastic modelling for financial valuation and risk management, numerical methods aimed at supporting financial applications, and the interplay between finance and insurance. She holds a Ph.D. in Mathematical and Computational Methods for Economics and Finance from the Università degli Studi di Bergamo (Italy).