Financial Engineering Practitioners Seminar

The IEOR Department hosts Financial Engineering Seminars throughout the Fall and Spring semesters. There are 4-6 seminars per semester. These seminars feature a variety of academics and professionals in the field of Financial Engineering; they are meant to educate and expose students and the greater Columbia community to the latest research and practice. A full year of the Financial Engineering Practitioners Seminar Series is required for Columbia’s MSFE Program as the 0-credit course, IEOR E4798.

Financial Engineering Practitioners Seminar

The seminar presents research and practice in financial engineering and related fields. It is open to Columbia students, attendees from industry and academia, and the general public (space permitting).

To request more information or express interest in becoming a corporate sponsor, please contact us.

Please click on the expandable sections below to see the slides and information about the talks.

We look forward to seeing you at the next FE Practitioners Seminar.


Ali Hirsa

Professor of Professional Practice, Industrial Engineering & Operations Research
Director of the MS in Financial Engineering
Director of Financial Engineering Practitioners Seminar

Spring 2022 Seminars

Nitin Gupta | September 26th

Speaker: Nitin Gupta
Date: Monday, September 26, 2022
Time: 7:00pm to 8:30pm
Location: Davis Auditorium

Title: Using Data to Drive Value in PE

Bio: Based in New York, Nitin Gupta leads US investments, and is a member of the Global Advisory Investment Committee, and the US Investment Committee.

Nitin joined Caspian Private Equity, a predecessor to Flexstone Partners, in 2008. Prior to Caspian, he was a Principal at Westbury Partners, where he was responsible for deal sourcing, due diligence and serving on the board of portfolio companies. Prior to Westbury Partners, Nitin was a Senior Associate at Saunders Karp & Megrue, where he was responsible for due diligence, with a particular focus on healthcare and retail investments. Prior to Saunders Karp & Megrue, he was an Associate at McCown De Leeuw & Company, where he was responsible for due diligence and a buy and build strategy across a number of industries including business services, industrial, and manufacturing. Prior to McCown DeLeeuw & Company, Nitin was an analyst in the M&A group at Merrill Lynch & Company where he completed a number of buy-side transactions for certain Fortune 500 companies.

Nitin earned his BS at New York University and MBA at Harvard Business School. He serves as a Board member/observer for several portfolio companies of funds managed by Flexstone Partners

Amal Moussa | October 3rd

Speaker: Amal Moussa
Date: Monday, October 3, 2022
Time: 7:00pm to 8:30pm
Location: Davis Auditorium

Title: Introduction to Exotic Derivatives Pricing and Hedging

Bio: Dr. Amal Moussa is a Managing Director at Goldman Sachs where she leads the Single Stocks Exotic Derivatives Trading desk. Prior to that, Amal held senior level positions in equity derivatives trading at other leading financial institutions such as J.P. Morgan, UBS and Citigroup.

In addition to her work in Markets, Amal is an Adjunct Professor at Columbia University where she teaches a graduate course on Modeling and Trading Derivatives in the Mathematics of Finance Master's program.

Amal has a Ph.D. in Statistics, obtained with distinction, from Columbia University. Her thesis “Contagion and Systemic Risk in Financial Networks” shed light on the importance of the network structure in identifying systemic financial institutions and formulating regulatory policies, and has been cited by several scholars and industry professionals including former Federal Reserve president Janet Yellen. She was also awarded the Minghui Yu Teaching Award at Columbia University.

Amal is a board member of Teach for Lebanon, an NGO working to ensure that all children in Lebanon have access to education regardless of socioeconomic background, and she is an active member of the Women in Trading network at Goldman Sachs.

Jon Marymor | October 17th

Speaker: Jon Marymor
Date: Monday, October 17, 2022
Time: 7:00pm to 8:30pm
Location: Davis Auditorium

Title: BAM’s Approach to Macro Risk Management

Bio: Jonathan (Jon) Marymor joined the BAM New York office in December 2018 as Director, Macro Risk Management and was then promoted in January 2021 to Head, Macro Risk Americas. Jon joined BAM from Element Capital, where he started as a Vice President in Modeling and Technology and was promoted through to Risk Management, Director, serving as the lead risk analyst across the $15B core fund. His prior professional experience also includes several roles at Morgan Stanley, where he ultimately covered cash and derivatives in the U.S. Interest Rates Strategy group. Jon holds an M.S. in Mathematics from the University of Michigan and a B.S. in Economics from the University of Pennsylvania’s Wharton School of Business.

Reza Gharavi | November 14th

Speaker: Reza Gharavi
Date: Monday, November 7, 2022
Time: 7:00pm to 8:30pm
Location: Davis Auditorium

Title: To Be A Quant...

Bio: Reza is a Director at Citi’s Market Quantitative Analysis team. He joined Citi in 2005. Before that he held a number of quant positions starting from 1998. He holds a B.Sc. from Boston University and a Ph.D. from Cornell University, both in Electrical Engineering.  

Fabrizio Lecci | November 21st

Speaker: Fabrizio Lecci
Date: Monday, November 21, 2022
Time: 7:00pm to 8:30pm
Location: Davis Auditorium

Title: Survival Analysis for Business Applications

Abstract: Survival Analysis is a branch of statistics for analyzing the expected duration of time until one event occurs, such as death in biological organisms and failure in mechanical systems. However, Survival Analysis techniques are often neglected in business analytics in favor of linear regression models or other nonparametric machine learning solutions. In this talk we go over the fundamentals of Survival Analysis and we discuss why it is an effective tool for studying a variety of business events such as: customer churn, product adoption, employee hiring and resignation, engineering ticket events, loan repayment, inventory issues. 

Bio: Fabrizio Lecci is a statistician and a Data Science executive. After receiving a PhD in Statistics from Carnegie Mellon University he worked in tech and fintech companies (Uber, New York Life, Better) in various leadership roles. He has published in peer-reviewed journals and he has taught Statistics & Probability for the MBA program at the Fuqua School of Business. Fabrizio recently co-founded a boutique consulting firm, Data Captains, which partners with organizations that are committed to using data to improve their business and products for their customers. The common goal of his work is to advance the fields of applied Data Science and Machine Learning and help others leverage data tools in a rigorous yet pragmatic way.

Dave Baggett | December 5th

Speaker: Dave Baggett
Date: Monday, December 5, 2022
Time: 7:00pm to 8:30pm
Location: Davis Auditorium

Title: TBD

Abstract: TBD

Bio: TBD

--Past Seminars--

Spring 2020 Seminars

Fabio Mercurio | January 27th

Thank you for attending! Please find the slides from the seminar here.


FE Seminar Speaker: Fabio Mercurio

Hosted by IEOR and kindly sponsored by Guzman and Co.

Date: Monday, January 27th, 2020

Time: 6:00 pm to 7:30 pm

Location: Davis Auditorium, CEPSR Building


Title: Looking Forward to Backward-Looking Rates: A Modeling Framework for Term Rates Replacing LIBOR


Abstract: In this talk, we define and model forward risk-free term rates, which appear in the payoff definition of derivatives and cash instruments, based on the new interest-rate benchmarks that will be replacing IBORs globally.  We show that the classic interest-rate modeling framework can be naturally extended to describe the evolution of both the forward-looking (IBOR-like) and backward-looking (setting-in-arrears) term rates using the same stochastic process.


We then introduce an extension of the LIBOR Market Model (LMM) to backward-looking rates.  This extension, which we call generalized forward market model (FMM), completes the LMM by providing additional information about the rate dynamics between fixing/payment times, and by implying dynamics of forward rates under the classic money-market measure.


Our FMM formulation is based on the concept of extended zero-coupon bonds, which proves to be very convenient when dealing with backward-looking setting-in-arrears rates. Thanks to this, not only the bonds themselves, but also the forwards and swap rates, along with their associated forward measures, can be defined at all times, even those beyond their natural expiries.


Bio: Fabio is global head of Quantitative Analytics at Bloomberg LP, New York.  His team is responsible for the research on and implementation of cross-asset analytics for derivatives pricing, XVA evaluations and credit and market risk. Fabio is also an adjunct professor at NYU.  He has jointly authored the book "Interest rate models: theory and practice" and published extensively in books and international journals, including 19 cutting-edge articles in Risk Magazine. Fabio is the recipient of the 2020 Risk quant of the year award.


Martin Fridson | February 10th


Thank you for attending! Please find the slides from the seminar here.


FE Seminar Speaker: Martin Fridson

Hosted by IEOR and kindly sponsored by Guzman and Co.

Date: Monday, February 10th, 2020

Time: 6:00 pm to 7:30 pm

Location: Davis Auditorium, CEPSR Building


Title: The Credit Market:  Analysis, Dynamics, and Outlook


Abstract: U.S credit is a vast and diverse market comprising investment grade corporates, high yield bonds, and leveraged loans.  These instruments’ behavior is driven by interest rates, the business cycle, idiosyncratic changes in default risk, and variations in market liquidity. The talk will address analysis of these factors and how they shape current market levels and prospects. 


Bio: Martin Fridson is “perhaps the most well-known figure in the high yield world,” according to Investment Dealers’ Digest.  At brokerage firms including Salomon Brothers, Morgan Stanley, and Merrill Lynch, he became known for his innovative work in credit analysis and investment strategy.  For nine consecutive years he was ranked number one in high yield strategy in the Institutional Investor All America Research Survey. 


Fridson received his B.A. cum laude in history from Harvard College and his M.B.A. from Harvard Business School.  He has served as president of the Fixed Income Analysts Society, governor of the CFA Institute, director of the New York Society of Security Analysts, and consultant to the Federal Reserve Board of Governors.  


The Financial Management Association International named Fridson the Financial Executive of the Year in 2002.  In 2000, he became the youngest person inducted up to that time in the Fixed Income Analysts Society Hall of Fame.  The CFA Society New York bestowed its Ben Graham Award on Fridson in 2017. A study based on 16 core journals ranked Fridson among the ten most widely published authors in finance in the period 1990-2001.  In 2013 Fridson served as Special Assistant to the Director for Deferred Compensation, Office of Management and the Budget, The City of New York. 


In 2000, The Green Magazine called Fridson’s Financial Statement Analysis “one of the most useful investment books ever.”  The Boston Globe said his 2006 book, Unwarranted Intrusions: The Case Against Government Intervention in the Marketplace, should be short-listed for best business book of the decade.  


Fridson’s commentary on economics and financial markets can be found  


Marcos Lopez de Prado | February 24th


Thank you for attending! Please find the slides from the seminar here.


FE Seminar Speaker: Marcos Lopez de Prado

Hosted by IEOR and kindly sponsored by Guzman and Co.

Date: Monday, February 24th, 2020

Time: 6:00 pm to 7:30 pm

Location: Davis Auditorium, CEPSR Building


Title: Portfolio Construction in the Age of Machine Learning


Abstract: Classical portfolio construction methods (e.g., Markowitz, Black-Litterman) deliver notoriously unstable solutions. This instability has two main sources: noise and signal. In this seminar, we trace back the two sources of instability, and explain machine learning algorithms that address them. Monte Carlo experiments demonstrate that these algorithms outperform out-of-sample the classical solutions.


Bio: Prof. Marcos López de Prado is the CIO of True Positive Technologies (TPT), and Professor of Practice at Cornell University’s School of Engineering. He has over 20 years of experience developing investment strategies with the help of machine learning algorithms and supercomputers. Marcos launched TPT after he sold some of his patents to AQR Capital Management, where he was a principal and AQR’s first head of machine learning. Marcos also founded and led Guggenheim Partners’ Quantitative Investment Strategies business, where he managed up to $13 billion in assets, and delivered an audited risk-adjusted return (information ratio) of 2.3.


Concurrently with the management of investments, since 2011 Marcos has been a research fellow at Lawrence Berkeley National Laboratory (U.S. Department of Energy, Office of Science). He has published dozens of scientific articles on machine learning and supercomputing in the leading academic journals, is a founding co-editor of The Journal of Financial Data Science, has testified before the U.S. Congress on AI policy, and SSRN ranks him as the most-read author in economics. Among several monographs, Marcos is the author of several graduate textbooks, including Advances in Financial Machine Learning (Wiley, 2018) and Machine Learning for Asset Managers (Cambridge University Press, forthcoming).


Marcos earned a PhD in financial economics (2003), a second PhD in mathematical finance (2011) from Universidad Complutense de Madrid, and is a recipient of Spain's National Award for Academic Excellence (1999). He completed his post-doctoral research at Harvard University and Cornell University, where he is a faculty member. Marcos has an Erdős #2 according to the American Mathematical Society, and in 2019, he received the ‘Quant of the Year Award’ from The Journal of Portfolio Management.


Mark Broadie | March 23rd

FE Seminar Speaker: Mark Broadie

Hosted by IEOR and kindly sponsored by Guzman and Co.

Date: Monday, March 23rd, 2020

Time: 6:00 pm to 7:30 pm

Location: Davis Auditorium, CEPSR Building


Title: Topics in Golf and Sports Analytics


Description: After a brief overview of sports analytics, this talk will focus on data, modeling techniques and recent advances in golf analytics.  Some connections with methods and models for financial modeling will also be mentioned.


Bio:  Mark Broadie is the Carson Family Professor of Business at Columbia Business School. Professor Broadie's research addresses issues in quantitative finance and sports analytics and, more generally, methods for decision making under uncertainty.  His quantitative finance research focused on problems in the pricing of derivative securities, risk management, and portfolio optimization. In his golf research, Broadie developed the strokes gained stats that are used by the PGA Tour. He works with a number of PGA Tour pros and writes a monthly column for GOLF magazine. His New York Times bestselling book Every Shot Counts uses data and analytics to measure and improve golf performance and strategy. Broadie worked with Turner Sports to bring the first live golf win probabilities to the network broadcast of the Woods-Mickelson match. He has been a member of the USGA's handicap research team since 2003. He currently teaches courses on business analytics and sports analytics. Professor Broadie received a BS from Cornell University and a PhD from Stanford University.

Paul Wilmott | March 30th

FE Seminar Speaker: Paul Wilmott

Hosted by IEOR and kindly sponsored by Guzman and Co.

Date: Monday, March 30th, 2020

Time: 6:00 pm to 7:30 pm

Location: Davis Auditorium, CEPSR Building


Title: Quantifying the Pleasure and Pain of Investing


Bio: Paul was a professional juggler with the Dab Hands troupe, and has been an undercover investigator for Channel 4. He also has three half blues from Oxford University for Ballroom Dancing. He makes his own cheese. Its flavour has been described as "challenging."

Paul was the first man in the UK to get an online divorce.

He was recently an "expert" on a TV show, tasked with forecasting a royal baby name and the winner of the Eurovision Song Contest among other things. He got everything wrong.

He played bridge for his school's D team. There was no E team.

And he plays the ukulele.

Victor Haghani | April 6th

FE Seminar Speaker: Victor Haghani

Hosted by IEOR and kindly sponsored by Guzman and Co.

Date: Monday, April 6th, 2020

Time: 6:00 pm to 7:30 pm

Location: Davis Auditorium, CEPSR Building


Title: Puzzles and Paradoxes Posed by Negative Interest Rates


Abstract: For centuries, economists have proposed theories of interest rates which presumed rates will always be positive in the long term. At the same time, while it’s been recognized that long-term financial decisions are best made on the basis of real rather than nominal return and risk, until recently our historical perspective has been almost exclusively framed in terms of nominal, not real, returns. In this talk, we will revisit the historical record in conjunction with conventional theories of interest rates in the light of fresh scholarly research and recent market experience. We will suggest that a future in which negative long-term interest rates may be the “new normal” will have profound implications for our most fundamental models for valuing stocks and bonds under uncertainty.

Bio: Victor founded Elm in 2011 to help himself and his friends manage their savings in an efficient and disciplined manner, and to capture the long-term returns they ought to earn. He has spent nearly 30 years actively involved in markets and financial innovation, having been a Managing Director in the bond-arbitrage group at Salomon Brothers and later a founding partner of Long-Term Capital Management (LTCM).

Spring 2019 Seminars

Marcos Lopez de Prado | January 28

Speaker: Marcos Lopez de Prado
Date: Monday, January 28, 2019
Time: 6:00pm to 7:30pm
Location: Uris 301- location change

Title: Financial Machine Learning
Abstract: Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. In this presentation, we review some of the most important current financial applications of ML.
Bio: Marcos López de Prado is a principal at AQR Capital Management, and its head of machine learning. Concurrently with the management of investments, between 2011 and 2018 Marcos was also a research fellow at Lawrence Berkeley National Laboratory (U.S. Department of Energy, Office of Science). He has published dozens of scientific articles on machine learning and supercomputing in the leading academic journals, and SSRN ranks him as one of the most-read authors in economics. Among several monographs, he is the author of the graduate textbook Advances in Financial Machine Learning (Wiley, 2018). Marcos earned a PhD in financial economics (2003), a second PhD in mathematical finance (2011) from Universidad Complutense de Madrid, and is a recipient of Spain's National Award for Academic Excellence (1999). He completed his post-doctoral research at Harvard University and Cornell University, where he teaches a financial machine learning course at the School of Engineering. His research website address is

Ole Peters | February 4

Speaker: Ole Peters
Date: Monday, February 4, 2019
Time: 6:00pm to 7:30pm
Location: Davis Auditorium, CEPSR Building

Title: The ergodicity problem in economics

Abstract: The ergodicity problem queries the equality or inequality of time averages and expectation values. I will trace its curious history, beginning with the origins of formal probability theory in the context of gambling and economic problems in the 17th century. This is long before ergodicity was a word or a known concept, which led to an implicit assumption of ergodicity in the foundations of economic theory. 200 years later, when randomness entered physics, the ergodicity question was made explicit. Over the past decade I have asked what happens to foundational problems in economic theory if we export what is known about the ergodicity problem in physics and mathematics back to economics. Many problems can be resolved. Following an overview of our theoretical and conceptual progress, I will report on a recent experiment that strongly supports our view that human economic behavior is better described as optimizing time-average growth rates of wealth than as optimizing expectation values of wealth or utility of wealth.

Bio: Ole Peters is a Fellow at the London Mathematical Laboratory and External Professor at the Santa Fe Institute. He works on different conceptualizations of randomness in the context of economics. His thesis is that the mathematical techniques adopted by economics in the 17th and 18th centuries are at the heart of many problems besetting the modern theory. Using a view of randomness developed largely in the 20th century he has proposed an alternative solution to the discipline-defining problem of evaluating risky propositions. This implies solutions to the 300-year-old St. Petersburg paradox, the leverage optimization problem, the equity premium puzzle, and the insurance puzzle. It leads to deep insights into the origin of cooperation and the dynamics of economic inequality. He maintains a popular blog at that also hosts the ergodicity economics lecture notes.

Adam Grealish | February 25

Speaker: Adam Grealish
Date: Monday, February 25, 2019
Time: 6:00pm to 7:30pm
Location: Davis Auditorium, CEPSR Building

Title: Fintech: Better Investing Through Technology

Bio: Adam Grealish is the Director of Investing at Betterment, the largest independent online financial advisor with over $14 billion in assets under management. 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. Before that, Adam was part of the global quantitative equity portfolio management team at New York Life Investments. 

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, as well as unique problems faced by taxable investors. We will also explore how technology can improve investor behavior.

View Slides

Richard Robb | March 4

Speaker: Richard Robb 
Date: Monday, March 4, 2019
Time: 6:00pm to 7:30pm
Location: Davis Auditorium, CEPSR Building

Title: Choice with Reason

Abstract: This talk will draw from Richard Robb’s forthcoming book, Willful: How We Choose What We Do, Yale University Press, Fall 2019. This book identifies a new dimension of behavior that can’t be described by rational choice or behavioral biases: acting willfully on the world. These actions are undertaken for their own sake rather than to obtain a preferred outcome. Exploring this uncharted sphere, we learn to see time as a flow and economic life as a high-stakes game. Beliefs, which constitute our identity, are neither infinitely flexible or easily transmitted, even if every agent is rational, trustworthy and properly incentivized. The theory has far-reaching consequences for institutional investing, opportunities for individual investing, reformulated notions of market efficiency and the fundamental limits to communication that cause markets to seize up.

Bio: Richard Robb is Professor of Professional Practice at SIPA where he directs the Concentration in International Finance and Economic Policy. He is also CEO of fund manager Christofferson, Robb & Company (CRC), with over $4 bn under management. Prior to cofounding CRC, he was the Global Head of the derivatives and securities subsidiaries of the Dai-Ichi Kangyo Bank in New York, London and Hong Kong. He has a B.A. from Duke University and a PhD in Economics from The University of Chicago.



Michael Miller | March 11

Speaker: Michael Miller
Date: Monday, March 11, 2019
Time: 6:00pm to 7:30pm
Location: Davis Auditorium, CEPSR Building

Title: Risk-Based Performance Attribution

Abstract: Traditional performance attribution may work well for long-only strategies, but it can be inaccurate and even misleading when applied to hedge fund strategies. Risk-based performance attribution, while more difficult to perform, provides a more accurate picture of the drivers of hedge fund performance.

This presentation will start with a general overview of performance analysis, before moving on to factor analysis and risk-based performance attribution. 

Bio: Michael B. Miller is the founder and CEO of Northstar Risk. Before starting Northstar, he was the Chief Risk Officer for Tremblant Capital and before that the Head of Quantitative Risk Management at Fortress Investment Group.

Mike is the author of Quantitative Financial Risk Management and Mathematics and Statistics for Financial Risk Management. He is also the co-author, along with Emanuel Derman, of The Volatility Smile. Mike is an adjunct professor at Columbia University and the co-chair of the Global Association of Risk Professional’s Research Fellowship Committee. Before starting his career in finance, he studied economics at the American University of Paris and the University of Oxford.


Vasant Dhar | April 8

Speaker: Vasant Dhar
Date: Monday, April 8, 2019
Time: 6:00pm to 7:30pm
Location: Davis Auditorium, CEPSR Building

Title: Artificial Intelligence and Data Science in modern financial decision making
Abstract: There’s a tremendous amount of interest in the use of machine learning in modern day financial decision making. Much of this interest is fueled by increasing amounts of available data and the general success of machine learning in other domains such as perception. I start by assessing the opportunities and key challenges for machine learning in exchange traded and OTC markets, and how finance problems are uniquely challenging. I describe the conditions in which we should trust automated decision making in these markets by breaking down trust into two key risk factors, namely, how often an automated decision system makes mistakes and the consequences of such mistakes. I use my model of trust to present results that show under what conditions we should trust autonomous learning systems with decision making.
Bio: Vasant Dhar is Professor, Stern School of Business and Center for Data Science at New York University. He is the director of NYU’s PhD program in Data Science. Dhar is also the founder of SCT Capital Management a , a machine-learning-based hedge fund in New York City.
Dhar’s central research question asks when we should trust AI machines that learn and make decisions autonomously based on ongoing data. His research has addressed this question in a number of areas, most notably, in financial markets.  Dhar has authored over 100 research papers, as well as articles for publications such as the Financial Times, Wall Street Journal, Forbes, Wired, and the Harvard Business Review. He has appeared on CNBC, Bloomberg TV, and National Public Radio. 

Fall 2018 Seminars

Julien Guyon | September 17

FE Seminar Speaker: Julien Guyon
Hosted by Columbia IEOR/Waterloo
Date: Monday, September 17, 2018
Time: 6:00 pm to 7:30 pm
Location: Davis Auditorium, CEPSR Building

Title: Path-Dependent Volatility

Abstract: So far, path-dependent volatility models have drawn little attention from both practitioners and academics compared with local volatility and stochastic volatility models. This is unfair: in this talk we show that they combine benefits from both. Like the local volatility model, they are complete and can fit exactly the market smile of the underlying asset; smile calibration is achieved using the particle method. Like stochastic volatility models, they can produce rich implied volatility dynamics; for instance, they can generate large negative forward skews, even when they are calibrated to a flat smile. But path-dependent volatility models can even do better than that: thanks to their huge flexibility, they can actually produce spot-vol dynamics that are not attainable using stochastic volatility models, thus possibly preventing large mispricings; and they can also capture prominent historical patterns of volatility, such as volatility depending on the recent trend of the underlying asset, for instance. We give many examples and show many graphs to demonstrate their great capabilities.

Bio: Julien is a senior quantitative analyst in the Quantitative Research group at Bloomberg L.P., New York. He is also an adjunct professor in the Department of Mathematics at Columbia University and at the Courant Institute of Mathematical Sciences, NYU. Before joining Bloomberg, Julien worked in the Global Markets Quantitative Research team at Societe Generale in Paris for six years (2006-2012), and was an adjunct professor at Universite Paris 7 and Ecole des ponts. He co-authored the book Nonlinear Option Pricing (Chapman & Hall, CRC Financial Mathematics Series, 2014) with Pierre Henry-Labordere. His main research interests include nonlinear option pricing, volatility and correlation modeling, and numerical probabilistic methods. Julien holds a Ph.D. in Probability Theory and Statistics from Ecole des ponts. He graduated from Ecole Polytechnique (Paris), Universite Paris 6, and Ecole des ponts. A big soccer fan, Julien has also developed a strong interest in sports analytics, and has published several articles on the FIFA World Cup, the UEFA Champions League, and the UEFA Euro in top-tier newspapers such as The New York Times, Le Monde, and El Pais, including a new, fairer draw method for the FIFA World Cup.

View Slides

Fabio Mercurio | October 15

FE Seminar Speaker: Fabio Mercurio
Hosted by Columbia IEOR/Waterloo
Date: Monday, October 15, 2018
Time: 6:00 pm to 7:30 pm
Location: Davis Auditorium, CEPSR Building

Title: SOFR so far

Abstract: We propose a simple two-factor multi-curve model where Fed-fund, SOFR and LIBOR rates are modeled jointly. The model is used to price the newly quoted SOFR futures as well as Eurodollar futures. We then derive pricing formulas for SOFR-based swaps, and show how the valuations of LIBOR-based swaps as well as LIBOR-SOFR basis swaps are impacted by the introduction of a new LIBOR fallback.

Bio: Fabio is global head of Quantitative Analytics at Bloomberg LP, New York. His team is responsible for the research on and implementation of cross-asset analytics for derivatives pricing, XVA valuations and credit and market risk. Fabio is also adjunct professor at NYU, and a former CME risk committee member. He has jointly authored the book 'Interest rate models: theory and practice' and published extensively in books and international journals, including 17 cutting-edge articles in Risk Magazine. Fabio holds a BSc in Applied Mathematics from the University of Padua, Italy, and a PhD in Mathematical Finance from the Erasmus University of Rotterdam, The Netherlands

View Slides


Heath Windcliff | November 1

FE Seminar Speaker: Heath Windcliff
Hosted by Columbia IEOR/Waterloo
Date: Thursday, November 1, 2018
Time: 6:00 pm to 7:30 pm
Location: 110 Williams Street, 3rd floor. Manhattan Institute of Management
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Title: Measuring and Using Trading Algorithms Effectively

Abstract: In order to build effective trading algorithms, you need to effectively measure trading algorithms. In this talk we will talk about what factors we look at when measuring trading engine performance in tuning our algorithms.  Specifically we will discuss several common benchmarks and discuss what each of these focus their lens upon, and what these measurements are blind to. We will focus on the precision of these measurements and where these sources of noise and uncertainty come from. We will show a lower bound on the amount of noise expected in these measures so you can determine how precisely one can expect to be able to measure trading performance for a given amount of flow.  This has material implications on the feasibility and applicability of quantitative best-execution measures for many users. Finally we will show how use these methods in our engine tuning process.

Bio: Heath Windcliff, Managing Director, is the head of the Quantitative Research team at MS which is responsible for equity algorithmic trading research and development. He actively works on the design of the optimization tools, the limit order worker and the venue selection models used in our products. He is also responsible for the PostTrade analytics framework that MS uses to design and tune the algorithmic offering for the use cases and needs of users and clients. Heath has a PhD in Computer Science focused on numerical methodologies from the University of Waterloo in 2003 following a Masters and Bachelors in Applied Mathematics

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