Quant Insights Conference:
Portfolio Management in Quant Finance
23rd March 2023
10:30 - 17:35 GMT
Brought to you by
CQF Institute, Fitch Learning, and Wilmott
About the Conference
The CQF Institute, Fitch Learning, and Wilmott are excited to announce that registrations are now open for the March 2023 Portfolio Management in Quant Finance Conference. Join your fellow quants for an exclusive, online conference packed with world-leading experts and discussions, virtual networking opportunities, and more.
Book your free ticket now to make sure you don't miss a minute of it.
Confirmed speakers and panelists. Click on the images below to explore abstracts and biographies.
Dr. Alexandre Antonov
Quantitative Research & Development Lead
Dr. Alexandre Antonov, Quantitative Research & Development Lead, ADIA
Dr. Alexandre Antonov received his PhD degree from the Landau Institute for Theoretical Physics in 1997. He worked for Numerix, Standard Chartered and Danske Bank. Currently, Alexandre is a Quantitative Research & Development Lead at ADIA in Abu-Dhabi.
His activity is concentrated on modeling and numerical methods for portfolio optimization, interest rates, cross currency, credit and XVA, as well as Machine Learning and its applications. AA is an author for multiple publications in mathematical finance and a frequent speaker at financial conferences.
He has received a Quant of Year Award of Risk magazine in 2016.
Dr. Natalie Packham
Professor of Mathematics and Statistics
Berlin School of Economics and Law
Risk Factor Detection with Methods from Explainable ML
The importance of risk management in the financial industry has increased rapidly since the financial crisis, in particular with regard to financial market stability. A particular focus is on stress testing methods, which captures portfolio risk under adverse conditions. Advances in statistical learning and the availability of large, granular data sets offer new methodological possibilities for stress testing. Financial risk management applications such as hedging, scenario analysis and stress testing rely on portfolio models based on risk factors. In addition to observable risk factors, factor models with non-observable, data-based factors offer interesting alternatives. However, the lack of interpretability of the output is limiting. We develop time-dynamic methods for the interpretability of principal components (PCA), which allow to generate aggregated risk factors from existing risk factors. This aggregation makes it possible to plausibly implement less granular and even global stress scenarios.
Dr. Natalie Packham, Professor of Mathematics and Statistics, Berlin School of Economics and Law
Dr. Natalie Packham is Professor of Mathematics and Statistics at Berlin School of Economics and Law and Principal Researcher within the International Research Training Group “High Dimensional Nonstationary Time Series” (IRTG 1792) at Humboldt University Berlin. Natalie has several years of industry experience as a front office software engineer at an investment bank, and is frequently involved in industry-related research and consulting projects. Her research expertise includes Mathematical Finance, Financial Risk Management and Computational Finance, and her academic work has been published in Mathematical Finance, Finance & Stochastics, Quantitative Finance, Journal of Applied Probability and many other academic journals. She is associate editor of “Methodology and Computing in Applied Probability” and “Digital Finance” and co-chair of the GARP Research Fellowship Advisory Board. Natalie holds an M.Sc. in Computer Science from the University of Bonn, a Master’s degree in Banking & Finance from Frankfurt School, and a Ph.D. in Quantitative Finance from Frankfurt School.
Dr. Claus Huber
Head of Quantitative Modelling & Analytics
Building a Tool for Strategic Asset Allocation at a Swiss Insurance Company
One aspect of Helvetia Asset Management currently revamping its processes is to build a quantitative tool to support Strategic Asset Allocation. We have implemented an SAA model suggested by Black/Litterman (1992) and tailored it to our needs. The implementation path was not clear from the outset and it took a few detours to arrive at a productive tool. This includes, for example, specifying a range of parameters of the Black/Litterman model, modelling illiquid asset classes, like Real Estate, Private Equity, or incorporating insurance-specific constraints, like Solvency II and Swiss Solvency Test. Typical Use Cases are balance sheet optimisation, adding new Asset Classes (e.g., High Yield or Swiss Mortgages) to an existing portfolio or suggesting an allocation for a new investment strategy. This talk summarises our experience building an SAA tool and shares a few insights of our journey from the beginnings to a production-ready tool.
Dr. Claus Huber, Head of Quantitative Modelling & Analytics, Helvetia Insurance
Claus is the Head of Quantitative Modelling & Analytics at Helvetia Insurance in Basel, Switzerland, where his team develops digital tools for Strategic and Tactical Asset Allocation, risk budgeting, overlay management, manager selection, visual representation of complex data structures, and a few more. In previous roles he developed new investment products for Quantitative Multi Asset Funds and, as Head of Digital Transformation, drove the development of new tools and data products that allow smart data usage and sharing. As the founder of Rodex Risk Advisers LLC, based in Altendorf (Switzerland), he advised clients on risk management and quantitative investment solutions, for example, a Machine Learning approach to select hedge fund managers. He has extensive experience as entrepreneur, risk manager, credit strategist, hedge fund analyst, and government bond trader and worked for hedge funds, banks, and insurance companies.
Dr. Rick Bookstaber
Head of Risk & Co-Founder
Portfolio Management for People
Abstract coming soon.
Dr. Rick Bookstaber, Head of Risk & Co-Founder, Fabric
Dr. Rick Bookstaber is the Head of Risk and Co-Founder of Fabric (www.fabricrisk.com).
Rick is a noted expert in financial risk management, and is the author of The End of Theory (Princeton, 2017), and A Demon of Our Own Design (Wiley, 2007).
He has served in chief risk officer roles at Salomon, Morgan Stanley, Moore Capital, and Bridgewater Associates. From 2009 to 2015 he served at the SEC and the U.S. Treasury, drafting the Volcker Rule and modeling risk for the Financial Stability Oversight Council. Most recently he was the chief risk officer in the University of California Office of the CIO for the university’s $170 billion pension and endowment funds.
His roles have placed him at the center of financial crises of the last three decades – working with portfolio insurance during the 1987 Crash while at Morgan Stanley, overseeing risk at Salomon during the 1998 failure of Long-Term Capital Management (dubbed “Salomon North”), and with the aftermath of the 2008 Crisis while in the regulatory sphere.
A black belt in Brazilian jiu-jitsu, Rick can be found training at the Renzo Gracie Academy in his free time.
Rick received a Ph.D. in economics from MIT.
Dr. Thomas Barrau
Head of Indraday Research
AXA Investment Managers Chorus Ltd
Predicting Stock Market Drawdowns using Polymodels
We propose a Systematic Risk Indicator derived from a polymodel estimation. Polymodels allow us to measure the strength of the links that a stock market maintains with its economic environment. We show that these links tend to be more extreme before a market crisis, confirming the well-known increase of correlations while proposing a more subtle perspective. A fully automated and successful trading strategy is implemented to assess the interest of the signal, which is shown to be strongly significant, both from an economic and statistical point of view. Results are robust across different time-periods, for various sets of explanatory variables, and among 12 different stock markets.
Dr. Thomas Barrau, Head of Indraday Research, AXA Investment Managers Chorus Ltd
Dr. Thomas Barrau is Head of Intraday Research for the hedge fund AXA Investment Managers Chorus Ltd. He is leading the development of a portfolio of quantitative intraday trading strategies invested in various asset classes.
With Raphael Douady, he co-authored the book "Artificial Intelligence for Financial Markets: The Polymodel Approach", published by Springer.
He has been a Senior Quantitative Researcher at AXA IM Chorus, a role during which he developed a team of 4 researchers working on an Equity Market Neutral portfolio. Prior to this, he worked at Societe Generale as banker and financial advisor to small businesses, and as CFO in an aerospace company. He holds a PhD in Applied Mathematics from Paris 1 Pantheon-Sorbonne University. Previously, he validated with honors three different Masters of Science from Aix-Marseille School of Economics, Ca'Foscari University of Venice and Poitiers IAE.
Dr. Jean-Marc Mercier
Head of Research & Development
Generative Models and Predictive Machines with Uncertainty Quantification for Financial Applications with Kernels
We consider generative and predictive methods based on kernels (RKHS theory). This approach allowed us to consider various Finance applications, ranging from time series prediction with model-free models to intradays, real time pricing / hedging methods with predictive machines, or valuation algorithms of large portfolios depending on many risk sources for XVA or pricing purposes. The proposed approach is not only fast and efficient, but also reliable and explainable, because it is sheltered by solid error estimates, allowing us to fully understand the results. We illustrate our approach with several reproducible numerical examples, relying on an open source project. This led us to a modern and competitive approach of Portfolio Management, coupling machine learning and quantitative analysis, through an original approach mixing RKHS and optimal transport theory.
Dr. Jean-Marc Mercier, Head of Research & Development, MPG Partners
Dr. Jean-Marc Mercier is head of Research & Development at MPG Partners, a consulting firm specializing in Risk Management. His main task is to develop an open-source kernel-based IA platform, named codpy, focusing on Finance applications for either prospective researches or clients projects. Jean-Marc is a former public researcher, PDE (Partial Differential Equation) specialized. He then turned to industry, and has several years of industry experience as a quantitative engineer and a business analyst. His research is involved in machine learning, artificial intelligence, computer sciences, with 30+ published papers. Jean-Marc holds a Ph-D in Applied Mathematics from Bordeaux University.
Co-Head - Systematic Macro
Tony Guida, Co-Head - Systematic Macro, RAM AI
Tony Guida joined RAM AI in 2019 as a Senior Quantitative Researcher and became Co-Head of Systematic Macro. His work focuses primarily on extracting market inefficiencies from different sources from traditional fundamentals, market signals, alternative data and machine learning. Tony started his career at Unigestion in the Quantitative Equity Low Volatility Team and later became a member of the Research and Investment Committee In 2015, he moved to Edhec Risk Scientific Beta as a Senior Consultant for Risk allocation and Factor Strategies before going to a major UK pension fund in 2016 to build the in-house systematic equity, co-managing 8 billion GBP as a Senior Quantitative Portfolio Manager.
Tony is a Lecturer and researcher in Quantitative Finance and Machine Learning. He is the co-author and editor of 'Big Data and Machine Learning in Quantitative Investments and Machine Learning for Factor Investing' (R and Python versions).
Neo Ivy Capital Management
Renee Yao, Founder, Neo Ivy Capital Management
Renee Yao began her career on Wall Street at Citadel, LLC. Later she left Citadel to join WorldQuant, a Millennium Management Portfolio Manager, as a Trader with discretionary trading authority for her own designated account. Subsequently she joined a prop trading firm where she managed multiple statistical arbitrage portfolios totaling several hundred millions USD in gross positions. In early 2015, Renee set up her own firm, Neo Ivy Capital Management, a quantitative hedge fund manager that focuses on trading liquid, publicly traded equity securities via artificial intelligence strategies.
Renee was named as “Tomorrow’s Titan” by The Hedge Fund Journal in 2019 and “100 People Transforming Business” by Business Insider in 2020. Renee holds a M.A in Statistics from Columbia University.
Dr. Jan Rosenzweig
Pine Tree Market Neutral
Dr. Jan Rosenzweig, Portfolio Manager, Pine Tree Market Neutral
Jan has been working in the financial markets since 2005, for Credit Suisse, Rabobank, HSH Nordbank, IV Capital, Brancherose and Pine Tree. He worked as a Quant, Structurer, Trader and Portfolio Manager.
He has a PhD from Cambridge University and a BSc from Zagreb University. Jan is based in London.
Dr. Randeep Gug
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.
23rd March 2023
10:30 - 17:35 GMT
Quant Insights is presented by the CQF Institute, Fitch Learning, & Wilmott
Promoting the highest standard in practical financial engineering, the CQF Institute, part of Fitch Learning, is a global membership organization dedicated to educating and building the quantitative finance community. The CQF Institute is also the awarding body for the Certificate in Quantitative Finance (CQF) the world’s largest professional qualification in quantitative finance.
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.