Quant Insights Conference
27th May 2021
13:30 - 23:30 CST / 06:30 - 16:30 BST / 11:00 - 21:00 IST
Globally Live-Online
7th Conference
Brought to you by
CQF Institute, Fitch Learning and Wilmott

1 Day

11+ Talks

Free Tickets

30 Days Video on Demand

About the Conference

The Quant Insights Conference is back this May for its 7th event. Join talks from Dr. Paul Wilmott, Dr. John Hull, Professor Emanuel Derman, Dr. Thomas Ho, Professor Sang Bin Lee, Dr. Alexei Kondratyev, Professor Helyette Geman, and many more to discover the latest industry innovations.

Tickets are free for all CQF Institute members and include: access to all talks and panels, breakout and networking activities, plus 30 days of video on demand. Become a member to claim your complimentary ticket today.

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Conference Speakers

Confirmed speakers and panelists.

Paul Wilmott

Dr. Paul Wilmott, President, CQF Institute
Dr. Paul Wilmott, President, CQF Institute

Paul is the founder of the Certificate in Quantitative Finance and Wilmott.com and he is internationally renowned as a leading expert on quantitative finance. His research work is extensive, with more than 100 articles in leading mathematical and finance journals, as well as several internationally acclaimed books on mathematical modeling and derivatives, including the best-selling Paul Wilmott On Quantitative Finance, published by John Wiley & Sons.

Alexei Kondratyev
Quantum Machine Learning

The main focus of applied quantum computing research is an experimental demonstration of the quantum advantage. The emerging discipline of Quantum Machine Learning (QML) is likely to be the first area of quantum computing research to produce a definite evidence of quantum advantage using a hybrid quantum classical approach to training and running the parameterised quantum circuits. With exceptionally fast rate of quantum hardware development we can detect the first signs of the quantum advantage on finance related use cases. This presentation will cover parameterised quantum circuits (quantum neural networks) trained as both generative and discriminative ML models.

Dr. Alexei Kondratyev, Managing Director, Head of Data Science and Innovation, Standard Chartered Bank
Dr. Alexei Kondratyev, Managing Director, Head of Data Science and Innovation, Standard Chartered Bank

In his role as Managing Director and Head of Data Science and Innovation, DCDA, Dr. Alexei Kondratyev is responsible for providing data analytics services to Corporate, Commercial and Institutional Banking division of Standard Chartered Bank. He joined Standard Chartered Bank in 2010 from Barclays Capital where he managed a model development team within Credit Risk Analytics. Prior to joining Barclays Capital in 2004, he was a senior quantitative analyst at Dresdner Bank in Frankfurt.
Alexei holds MSc in Theoretical Physics from the Taras Shevchenko National University of Kiev and PhD in Mathematical Physics from the Institute for Mathematics, National Academy of Sciences of Ukraine.
He was the recipient of the 2019 Quant of the Year award from Risk magazine.

David Liu

David Liu, CRMO, Bank of Communications, New York Branch
David Liu, CRMO, Bank of Communications, New York Branch

David Liu is the Chief Risk Management Officer at Bank of Communications, New York Branch, running the risk management department and credit management department. He joined the Bank of Communications in 2009 from JP Morgan Chase, where he was a private banker covering Asian markets from New York. Prior to that, he spent 10 years at Deutsche Bank as a market risk controller overseeing the risk and independent price verification for banks' proprietary trading portfolio. Prior to joining Deutsche Bank in 1997, David worked various positions, including floor trader at Shanghai Stock Exchange for Industrial and Commercial Bank of China Deyang Branch. David received his MS in Finance from Texas Tech University, and BS in Finance from Southwestern University of Finance and Economics. He was named the chairman of the Asian Financial Society in 2008.

Emanuel Derman
A Stylized History of Quantitative Finance

The evolution of a quantitative approach to finance has proceeded through many small but significant steps and occasional large epiphanies. This talk outlines how, over the past 70 years, financial models have quantified the notion of derivatives, diffusion, risk, volatility, the riskless rate, diversification, hedging, replication, and the principle of no riskless arbitrage, and points out some of the inconsistencies in this approach.

Professor Emanuel Derman, Financial Engineering Professor at Columbia University
Professor Emanuel Derman, Financial Engineering Professor at Columbia University

Emanuel Derman is a professor at Columbia University, where he directs their program in financial engineering. He was born in South Africa, but has lived most of his professional life in Manhattan. He started out as a theoretical physicist, doing research on unified theories of elementary particle interactions. At AT&T Bell Laboratories in the 1980s he developed programming languages for business modeling. From 1985 to 2002 he worked on Wall Street where he co-developed the Black-Derman-Toy interest rate model and the local volatility model. He is the author of ‘The Volatility Smile’ (Wiley, 2017) and ‘Models.Behaving.Badly’ (Free Press 2011) - one of Business Week’s top ten books of 2011. He is also the author of ‘My Life As A Quant’ (Wiley 2004), as well as one of Business Week's top ten of 2004, in which he introduced the quant world to a wider audience.

Helyette Geman

Professor Helyette Geman, Director of the Commodity Finance Centre, Birkbeck University of London and Research Professor, Johns Hopkins University
Professor Helyette Geman, Director of the Commodity Finance Centre, Birkbeck University of London and Research Professor, Johns Hopkins University

Helyette Geman is the Director of the Commodity Finance Centre at Birkbeck - University of London and a Research Professor at Johns Hopkins University. She is a graduate of Ecole Normale Supérieure in Mathematics and holds a PhD in Probability from the University Pierre et Marie Curie and a PhD in Finance from the University Pantheon Sorbonne. Professor Geman has been a scientific advisor to major financial institutions and energy companies for the last 21 years, covering the spectrum of interest rates, electricity, crude oil, metals and cryptocurrencies She was the PhD adviser of Nassim Taleb, has published more than 145 papers in top finance journals, and was the first President of the Bachelier Finance Society, featuring Paul Samuelson and Robert Merton. Professor Geman is one of the authors of the CGMY model, a pure jump Lévy process widely used in finance and insurance and since 2007 has been on the Board of the Bloomberg Commodity Index. Her book ‘Commodities and Commodity Derivatives’ is the reference in the field.

John Hull
Valuing Exotic Options and Estimating Model Risk

A common approach to valuing exotic options involves choosing a model and then determining its parameters to fit the volatility surface as closely as possible. We refer to this as the model calibration approach (MCA). This research examines an alternative approach where the points on the volatility surface are features input to a neural network. We refer to this as the volatility feature approach (VFA). We conduct experiments showing that VFA can be expected to outperform MCA for the volatility surfaces encountered in practice. Once the upfront computational time has been invested in developing the neural network, the valuation of exotic options using VFA is very fast. VFA is a useful tool for the estimation of model risk. We illustrate this using S&P 500 data for the 2001 to 2019 period.

Dr. John Hull, Maple Financial Professor of Derivatives and Risk Management, Joseph L. Rotman School of Management, University of Toronto
Dr. John Hull, Maple Financial Professor of Derivatives and Risk Management, Joseph L. Rotman School of Management, University of Toronto

John Hull is the Maple Financial Professor of Derivatives and Risk Management at the Joseph L. Rotman School of Management, University of Toronto. In 2016, he was awarded the title of University Professor (an honor granted to only 2% of faculty at University of Toronto.) He is an internationally recognized authority on derivatives and risk management and has many publications in this area. His work has an applied focus. His areas of research have included the impact of stochastic volatility on the pricing and hedging of options, the valuation of interest rate derivatives and credit derivatives, the calculation of value at risk, the evaluation of model risk, the regulation of financial institutions, and machine learning. He was, with Alan White, one of the winners of the Nikko-LOR research competition for his work on the Hull-White interest rate model, which is widely used by practitioners. In 1999 he was voted Financial Engineer of the Year by the International Association of Financial Engineers. He has acted as consultant to many financial institutions throughout the world and has won many teaching awards, including University of Toronto's prestigious Northrop Frye award. His current research interests are concerned with the application of machine learning to finance.
He is well known for his four books: “Risk Management and Financial Institutions” (now in its 5th edition); "Options, Futures, and Other Derivatives" (11th edition published in 2021); "Fundamentals of Futures and Options Markets" (now in its 9th edition); and “Machine Learning in Business: An Introduction to the World of Data Science” (now in its second edition). The books have been translated into many languages and are widely used by practicing managers as well as in the classroom.
Dr. Hull is academic director of FinHub (Rotman’s Financial Innovation Lab) and co-director of Rotman’s Master of Finance and Master of Financial Risk Management programs. In addition to the University of Toronto, Dr. Hull has taught at York University, University of British Columbia, New York University, Cranfield University, and London Business School.

Mary Hardy
Risk Sharing Pension Plans

Traditional final average salary defined benefit (DB) plans are declining, largely because of the volatility of costs. However, the defined contribution (DC) design has significant and important deficiencies, including uncertain and potentially inadequate retirement income. This talk will adapt results from theoretical, stylized work on pension design, to explore a form of target benefit (TB) plan that allows for structured, transparent intergenerational risk sharing. It will compare the TB plan with a traditional DB plan, based on five broad areas of comparison: affordability, sustainability, efficiency, adequacy, and fairness.

Dr. Mary Hardy, Professor of Actuarial Science, University of Waterloo
Dr. Mary Hardy, Professor of Actuarial Science, University of Waterloo

Dr. Mary Hardy is a Professor of Actuarial Science at the University of Waterloo in Canada. Her research focuses on actuarial risk management, particularly in the context of equity-linked life insurance, and employer sponsored pension plans. She has written three books and around 70 papers on a range of topics in actuarial and quantitative risk management. Dr. Hardy is a Fellow of the Institute and Faculty of Actuaries, and of the Society of Actuaries, and is a Chartered Enterprise Risk Analyst. She was awarded the Finlaison Medal of the Institute and Faculty of Actuaries, for services to the actuarial profession in the areas of governance, education, research, and the application of research to practice.

Peter Hafez

Peter Hafez, Chief Data Scientist, RavenPack
Peter Hafez, Chief Data Scientist, RavenPack

Peter Hafez is the Head of Data Science at RavenPack. Since joining RavenPack in 2008, he’s been a pioneer in the field of applied news analytics bringing alternative data insights to the world’s top banks and hedge funds. Peter has more than 15 years of experience in quantitative finance with companies such as Standard and Poor's, Credit Suisse First Boston, and Saxo Bank. Peter holds a Master's degree in Quantitative Finance from Sir John Cass Business School along with an undergraduate degree in Economics from Copenhagen University. Peter is a recognized speaker at quant finance conferences on alternative data and AI, and has given lectures at some of the world’s top academic institutions including London Business School, Courant Institute of Mathematics at NYU, and Imperial College London.

Dr. Randeep Gug

Dr. Randeep Gug, CQF Institute, Managing Director
Dr. Randeep Gug, CQF Institute, Managing Director

Dr. Randeep Gug is the Managing Director of the CQF Institute and a lecturer on the Certificate in Quantitative Finance (CQF). Prior to joining Fitch Learning, Randeep worked in a variety of roles. He spent five years working in the Equities division at Salomon Smith Barney and later traded futures and options on the Indian National Stock Exchange (NSE). More recently he has spent time teaching mathematics at all levels. He is a qualified teacher, holds a 1st class honours degree and a PhD for research in semiconductor physics. He is a CQF Alumnus, achieving a distinction on the programme and his current interests are based around improving and promoting the teaching and learning of Quant Finance.

Professor Sang Bin Lee

Professor Sang Bin Lee, Emeritus Professor of Finance, Hanyang University
Professor Sang Bin Lee, Emeritus Professor of Finance, Hanyang University

Sang Bin Lee is an Emeritus Professor of Finance at Hanyang University. He was a Visiting Professor at NYU Shanghai and a Professor of Finance at KAIST (Korea Advanced Institute of Science and Technology) in Korea. He was a commissioner of the Securities and Futures Commission, president of the Korean Securities Association, and an independent director and member of the risk management committee at Hana Holding Company, which owns Hana Bank as well as Korean Exchange Bank. He was also an editorial writer at one of the leading economic newspapers in Seoul. He was a member of the Presidential Economic Advisory Council in Korea. He is teaching Derivatives, Financial Engineering, Fixed Income Securities, and Risk Management. He is the co-author of the Ho-Lee Model, the first and a widely cited arbitrage-free interest rate model.
Sang Bin Lee has a Master's Degree in Economics from Cornell and a Ph.D. in Finance from New York University’s Stern School of Business. Hi research interests include Asset Pricing, Term Structure Movements, and Macro-Finance.

Thomas Ho

Dr. Thomas Ho, President, Thomas Ho Company (THC)
Dr. Thomas Ho, President, Thomas Ho Company (THC)

Thomas “Tom” Ho, Ph.D., revolutionized the financial services industry with groundbreaking research and development of interest rate, risk management, and complex securities valuation models. Named one of the most prolific authors in finance, Tom Ho literally wrote the book on financial modeling with his longtime collaborator, Sang Bin Lee, Ph.D. Their book, 'The Oxford Guide to Financial Modeling' (Oxford University Press, 2003) is one of four Tom has authored or co-authored. Tom is also the author of more than 80 articles that have appeared in major financial journals, including The Journal of Finance, The Journal of Derivatives, Journal of Fixed Income, and The Journal of Portfolio Management. In 2008, he was also in a featured Bloomberg Magazine article called 'Tom Ho on Bonds'.
Tom is also an elected member of the Financial Economists Roundtable; Member of the Board overseeing the Mathematics in Finance Program, Courant Institute of Mathematical Sciences, New York University; Consultant for federal regulators where he has provided over 50 regulatory and decision-support reports to date, including Enhanced Net Portfolio Value risk reports for OTS-regulated banks and onsite examiner systems in 2006.
Tom has also provided model validation, equity valuation, and asset/liability risk analysis for over 100 banks. In 1987, he founded Global Advanced Technology (GAT). GAT developed and provided cutting-edge technology to deliver fixed-income modeling solutions to 250 major global institutional clients, including 9 of the top 10 insurance companies. GAT merged with Barra, Inc., in 1997.

Uwe Wystup
Mixed Local Volatility Models for FX Derivatives

The FX Derivatives market has widened long since, beyond currency hedging solutions for international corporates, tailored hedging for institutions and the retail market. Yield enhancement strategies have reached the private banking industry. We will highlight the most recent developments including dual currency investments and target forwards. A market making bank distributing its FX derivatives through an electronic trading platform will have to ensure fast, robust and prices pricing of vanilla and exotic contracts. We will compare vanna volga , local volatility, stochastic volatility, stochastic local volatility and mixed local volatility, identify the pros and cons and shed some light on model risk. It turns out that the class of mixed local volatility (MLV) models can be considered at common market practice. At the end we combine the products and models and check which model is most suitable for which product class.

Professor Dr. Uwe Wystup, Founder and Managing Director of MathFinance AG
Professor Dr. Uwe Wystup, Founder and Managing Director of MathFinance AG

Prof. Dr. Uwe Wystup is the founder and Managing Director of MathFinance AG, an independent consulting and software company that specializes in FX derivatives pricing. Uwe got his PhD in Mathematical Finance with Steven E. Shreve at Carnegie Mellon University, he is the author of two books “Foreign Exchange Risk” and “FX Options and Structured Products”, writes the FX column for Wilmott magazine and published in many academic journals. Uwe is professor of Foreign Exchange Derivatives at University of Antwerp, and honorary professor of Quantitative Finance at Frankfurt School of Finance and Management, certified public expert for currency markets at Frankfurt’s Chamber of Commerce and the Expert Witness Institute. Ever since he started his FX options front-office role at Citibank in 1992 he has been a great fan of FX markets.

Conference Tickets

27th May 2021

Priority tickets are now available and are free for CQF Institute Members.
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Conference Organizers

Quant Insights is presented by the CQF Institute & Wilmott
CQF Instiute

Part of Fitch Learning, the CQF Institute is a global membership platform for educating and building the quant finance community.

Fitch Learning

Part of the Fitch Group, Fitch Learning partners with businesses to help develop the future leaders of the financial services industry. Alongside centers in established financial hubs, Fitch Learning utilizes a best-in-class technology platform to deliver blended learning solutions that maintain the personal element of development.


Wilmott is the leading resource for the quant finance community, comprised a website and discussion forum and Wilmott magazine.

Conference Sponsors

Platinum Sponsors
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