Annual Quant Insights Conference

Classifying Alternative Investments Using Self-Organizing Maps

The title says it all.

Wilmott Magazine at 20

On a summer afternoon at the beginning of this millennium, Paul Wilmott sat down to explain what an option is to Dan Tudball. Paul explained the difference between Rocket Scientists and Plodders. Explained how some mathematicians can get hung up on the beauty of a formula over its practicality. Explained that the Black-Scholes formula’s assumptions were not realistic, but an entire industry was based on that formula. Explained that this wasn’t necessarily a bad thing since the faults with Black-Scholes were very clear. It probably wasn’t all in one afternoon, but whatever period of time it occurred over it was very quick, because the first issue of Wilmott Magazine had to be put together!

Two decades later Paul Wilmott will again sit down with Dan Tudball to reflect on the life and times of the publication that continues to provide the quantitative finance community with cutting-edge research, innovative models, new products and in-depth analysis. It’ll probably be quite quick, though because the 123rd issue of Wilmott Magazine has to be put together!

Dr. Paul Wilmott, Founder, Certificate in Quantitative Finance (CQF)

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.

Excess Out-of-Sample Risk and Fleeting Modes

Using Random Matrix Theory, we propose a universal and versatile tool to reveal the existence of "fleeting modes", i.e. portfolios that carry statistically significant excess risk, signalling ex-post a change in the correlation structure in the underlying asset space. Our proposed test is furthermore independent of the "true" (but unknown) underlying correlation structure. We show empirically that such fleeting modes exist both in futures markets and in equity markets. We proposed a metric to quantify the alignment between known factors and fleeting modes and identify momentum as a source of excess risk in the equity space.

Dr. Jean-Philippe Bouchaud, President & Head of Research, Capital Fund Management

Dr. Jean-Philippe Bouchaud was born in France in 1962. After studying at the French Lycée of London, he graduated from the Ecole Normale Supérieure in Paris, where he also obtained his PhD in physics. He was then appointed by the CNRS until 1992. After a year spent in the Cavendish Laboratory (Cambridge), he joined the Service de Physique de l’Etat Condensé (CEA-Saclay), where he worked on the dynamics of glassy systems and on granular media. He became interested in economics and theoretical finance in 1991. His work in finance includes extreme risk models, agent-based simulations, market microstructure and price formation. He has been very critical about the standard concepts and models used in economics and in the financial industry (market efficiency, Black-Scholes models, etc.). He founded the company Science & Finance in 1994 that merged with Capital Fund Management (CFM) in 2000. He is the President and Head of Research at CFM and professor at Ecole Polytechnique since 2008. He was awarded the IBM young scientist prize in 1990 and the C.N.R.S. Silver Medal in 1996. He has published over 300 scientific papers and several books in physics and in finance.

Blockchains, Decentralized Financial Market Infrastructure and Decentralized Finance

This talk discusses some of the most recent developments in the cryptocurrency ecosystem. Specifically, we review stable coins, their classification, potential applications, and related topics. We also address the emerging field of Decentralized Financial Market Infrastructure (dFMI) and Decentralized Finance (DeFi), including Automated Market Makers (AMM). We explain the corresponding mathematics, economics, and technology behind and elaborate on the pros and cons of these developments. Finally, we argue that, despite obvious teething problems, which are both severe and numerous, dFMI has a bright future.

Is crypto the next frontier of opportunities for quants?

A burgeoning derivatives market, the increasing presence of High Frequency Traders and big institutions moving into crypto all point to a bright future for the space. Meanwhile, blockchain-based technologies have the potential to radically disrupt traditional models for securities trading. This panel will discuss where quants should look for research and professional opportunities in the crypto markets. Will crypto markets become increasingly intertwined with traditional finance or does the space hold the potential to go its own way? What should quants interested in crypto be thinking in terms of the next step in their careers?

Professor Alexander Lipton, Global Head, Research & Development, Abu Dhabi Investment Authority

Professor Alexander Lipton is Global Head, Research & Development at Abu Dhabi Investment Authority, Professor of Practice at Khalifa University, Visiting Professor and Dean’s Fellow at the Jerusalem Business School of the Hebrew University of Jerusalem, and Connection Science Fellow at MIT. Alex is a Co-Founder and Advisor at Sila – a company providing banking, digital wallet & ACH payments API for software teams, and an advisory board member of several fintech companies worldwide. In 2006–2016, Alex was Co-Head of the Global Quantitative Group and Quantitative Solutions Executive at Bank of America. Earlier, he was a senior manager at Citadel, Credit Suisse, Deutsche Bank, and Bankers Trust. At the same time, Alex held visiting professorships at EPFL, NYU, Oxford University, Imperial College, and the University of Illinois. Prior to becoming a quant, Alex was a Full Professor of Mathematics at the University of Illinois, and a Consultant at the Los Alamos National Laboratory. In 2000 he was awarded the Inaugural Quant of the Year Award and in 2021 the Buy-side Quant of the Year Award by Risk Magazine. Alex authored/edited eleven books and more than a hundred scientific papers on thermonuclear physics, astrophysics, applied mathematics, financial engineering, and distributed ledgers. He frequently gives keynote presentations on Quantitative Finance and FinTech at conferences and forums worldwide. In 2021, Alex published three books Blockchain and Distributed Ledgers: Mathematics, Technology, and Economics (with A. Treccani), Building the New Economy (with A. Pentland and T. Hardjono), and Generalized Integral Transforms in Mathematical Finance (with A. Itkin and D. Muravey).

Rarity Metrics for Profile Pictures

As Web 3 developments expand to virtual reality metaverses, personal profile (PFP) non-fungible tokens are emerging as the digital profile of choice. Many of these collections plan for images to be made into 3D avatars that function in virtual gaming and/or business environments. At the time of writing the utility value of a collection depends mostly on the real products, merchandise and events to which owners have exclusive access.

PFPs are traded in numerous marketplaces where the relative price of a PFP within its collection should be somehow linked the rarity of the individual PFP's attributes. However, there is no consensus on even the proper definition of rarity, let alone on how it should be measured. Descriptions of the various methods currently employed by the industry are mired in confusion because mathematical representations are poorly presented. Worse, the rarity measures produced by different metrics are converted into a rank which throws away valuable information and makes the relationship between price and rarity difficult to analyse. Worse still, the blurring of the price-rarity relationship is further exacerbated by tokens being ranked completely differently depending on the metric applied.

We address all these issues -- and many more -- by providing a coherent mathematical framework which encompasses the ALL rarity metrics currently in the public domain including OpenRarity and NFTGo in one simple formula also giving conditions and tests for validity — and much more besides.

Is crypto the next frontier of opportunities for quants?

A burgeoning derivatives market, the increasing presence of High Frequency Traders and big institutions moving into crypto all point to a bright future for the space. Meanwhile, blockchain-based technologies have the potential to radically disrupt traditional models for securities trading. This panel will discuss where quants should look for research and professional opportunities in the crypto markets. Will crypto markets become increasingly intertwined with traditional finance or does the space hold the potential to go its own way? What should quants interested in crypto be thinking in terms of the next step in their careers?

Professor Carol Alexander, Professor of Finance, University of Sussex

Carol Alexander is an expert in crypto asset and derivatives markets, financial risk analysis, high-frequency data analysis, blockchains, pricing and hedging financial instruments, volatility analysis, investment strategies, benchmarking and portfolio management. She has a dual career in both industry and as an academic and is currently Professor of Finance at the University of Sussex and Visiting Professor at Peking University Business School. She has also edited the Journal of Banking and Finance since 2013. Throughout her corporate and academic careers Carol has designed and implemented mathematical models for pricing, trading, hedging and risk assessment for a wide range of asset management and investment banking clients, including some of the largest global exchanges such as the New York Stock Exchange, the Intercontinental Exchange and the FTX.US Exchange. She is the author of the best-selling textbook “Market Models” and of the four-volume textbook series Market Risk Analysis. Her latest textbook “Corruption and Fraud in Financial Markets”, edited with Douglas Cumming. She has held corporate roles as a Director and Head of Market Risk Modelling for Nikko Securities; as a Director of Algorithmics Inc., the Toronto-based firm which provided risk modelling software to financial institutions and banks globally; and as a Bond Analyst for Phillips & Drew, City of London. She is consulting expert witness for Richards Butler, Fideres Partners and White and Case. She holds a BSc in Mathematics with Experimental Psychology (First Class) and a PhD in Algebraic Number Theory from the University of Sussex, and an MSc in Mathematical Economics and Econometrics from the London School of Economics and Political Science.

Don Quixote on Wall Street

In this work -- perhaps the most significant we've ever engaged with -- and after saying how unpardonable the omissions and additions perpetrated by Bachelier, we will show that the future should really be written and not merely predicted; equivalently, that the pricing function of the market models is forward-looking, and not backward-looking like the usual statistical models underlying it. We hope this is not, as Borges would put it, "one of those parasitic works which situate Christ on a boulevard, Hamlet on La Cannebière, or don Quixote on Wall Street." Indeed, we think the final term of a theological or metaphysical proof is no more final, no more uncommon, than ours. The sole difference is that philosophers publish the intermediate stages of their work, while we are resolved (for now) to suppress those stages of our own.

Elie Ayache, CEO, ITO 33

Elie Ayache is a former option market-maker on MATIF (1987-1990) and LIFFE (1990-1995). He is the co-founder (1999) and currently the CEO of ITO 33, a software company specializing in convertible bond pricing, and more generally equity index and equity-to-credit single name derivative pricing. Elie is the author of The Blank Swan: The End of Probability (Wiley 2010) and The Medium of Contingency: An Inverse View of the Market (Palgrave 2015).

New Financial Decision Theory Objectives Applied to Stock Trading in a High Dimensional Markovian Model

OU processes with long term drifts that are Tempered Fractional Lévy Processes reduce to a d + 1 dimensional Markovian system when the parameter d is an integer. Markovian optimization problems are formulated for stock investment. New financial objectives maximize a conservative financial valuation seen as a nonlinear expectation. Trading policies are solutions of nonlinear partial integro-differential equations. The policies are evaluated on a high dimensional quantized set of representative Markovian states. Gaussian Process Regression then delivers policies as general functions of the state. The nonlinear policy functions deliver good trading outcomes on simulated data. The policy functions are then applied to trading SPY from 2008 through 2020 and to trade 874 stocks over a four year period. The underlying dynamics may be further enriched by allowing for a Markov chain of states coding movements in parameters for the driving Lévy process.

Professor Dilip Madan, Professor Emeritus of Mathematical Finance, Robert H. Smith School of Business

Dilip Madan is Professor Emeritus of Mathematical Finance at the Robert H. Smith School of Business. Currently he serves as a consultant to Morgan Stanley, and Norges Bank Investment Management. He is a founding member and Past President of the Bachelier Finance Society. He received the 2006 von Humboldt award in applied mathematics, was the 2007 Risk Magazine Quant of the year, received the 2008 Medal for Science from the University of Bologna, held the 2010 Eurandom Chair and is the IAQF Financial Engineer of the Year 2021. He has published over 200 papers and serves on the Advisory Board of Frontiers of Mathematical Finance and as a Director of the Scientic Association of Mathematical Finance.

Market Lessons from the Work of William T Ziemba

In this talk, Rachel Ziemba, a key macro strategist, will draw from the work of her late father, William T Ziemba and their work together on capital markets to share some lessons relevant to investing in today’s volatile markets. Bill Ziemba, well-known to the CQF family as Dr Z, was a prolific contributor to Wilmott magazine from the start, sharing his takeaways on seasonalities, options-based investment strategies and a wide range of sports betting approaches. Rachel will share some of his latest work on seasonalities, including the turn of the year effect and map some of Dr Z’s investing strategies to the current macro and market risks. She will also draw on her own macro and political economy expertise to share some risks to watch for in 2023 and how to mitigate them.

Rachel Ziemba, Founder, Ziemba Insights

Rachel Ziemba is a geo-economic and country risk expert. She runs Ziemba Insights, an advisory firm that engages in macroeconomic scenario analysis and policy due diligence for public and private sector clients. She is particularly focused on the role of economic sanctions, the energy transition and the role of state-owned investors, but also tracks the market impact of key global macro issues including trade, global imbalances and sovereign debt.

She is Adjunct Senior Fellow at the Center for a New American Security (CNAS), a Washington DC based think tank. She is also on the advisory board of Enquire.ai, the Harriman Foreign Service Fellows and the Middle East Energy and Growth program at the Middle East Institute. She is contributor to EM Views and a non-resident fellow at the Gulf International Forum. She previously was an Adjunct Lecturer at New York University’s Center for Global Affairs, teaching international political economy.

Before founding Ziemba Insights, Rachel served as the head of emerging markets research at Roubini Global Economics, a global macro strategy and country risk firm. In that capacity she co-led the research team, overseeing the firm’s quarterly global economic outlook and scenario production and implementing many of its customized research projects and due diligence exercises for private equity firms. The work leveraged the firm’s systematic country risk model, global economic forecasting model and a variety of financial tools to generate actionable ideas.

Rachel regularly serves as an expert commentator in key media outlets including CNBC, Bloomberg, New York Times, Financial Times, and her research has been cited by a range of international institutions including the International Monetary Fund, World Bank and European Central Bank as well as many academic Institutions. She has served on a range of taskforces aimed to generate policy ideas on Egypt, Middle East policy and economic sanctions. She is the co-author of “Scenarios for Risk Management and Global Investment Strategies” and “Investing in the Modern Age” both with William Ziemba.

Rachel started her career in international development, working for the Canadian International Development Agency in Egypt, and the International Development Research Centre (Canada) on development economic issues. She also spent time as a US State Department intern at the Embassy in Paris (where she was an inaugural recipient of the Pamela Harriman Foreign Service Fellowship) and the Consulate in Toronto.

She holds a bachelor’s degree from the University of Chicago with honors, and a Master of Philosophy degree in international relations with a specialization in international political economy from St. Antony’s College, Oxford University (with distinction).

The Predictability of Stock Prices and Stock Returns: Is it Τhere and How to Find It

We examine the predictability of two of the major indices of stock market performance and valuation, the Dow Jones Industrial Average (DJIA) and the Standard and Poor’s 500 (S&P500). Our data span the full history of the two indices and, importantly for the DJIA cover the whole period even from before 1900’s. We can thus examine the difference in the predictability of the stock market under a broad range of economic and financial conditions. We focus on the predictability of both returns and prices and consider the use of (lags of) causal variables as possible predictors – these are the index of Leading Economic Indicators (LEI) of the Conference Board and the realized volatility of returns; the latter aggregated and computed from the daily data. Furthermore, we expand on the use of rolling window averaging (RWA), the combination of different segments of a time series to produce the forecast, suggesting different weighting schemes and empirically showing that the method performs extremely well. That is, the RWA models’ mean absolute forecasting errors (MAE) reductions are statistically significant at the 1% level during much of the 1990-2022 period. This is an important result as it takes away some of the a priori uncertainty as to which part of the time series to use in generating a forecast. We find that prices and returns are, at least locally in time, predictable, that the use of the causal variables is improving forecasting performance and that a set of models of limited complexity has very robust performance under many different time periods. While we have not, yet, used the insights of our results to evaluate their trading performance, we do make a provisional claim that forecasting prices and returns is doable with simpler models, provides realistic performance for the properties that these financial time series has and can be used in conjunction with any other inferential procedure that can offer recommendations about the future path of financial markets.

Co-Authors: Dr. John Guerard, Dr. Dimitrios Thomakos, Foteini Kyriazi and Konstantinos Mamais

Dr. John Guerard, McKinley Capital Management Scientific Advisory Board

John B. Guerard, Jr., Ph.D. is a member of the McKinley Capital Management Scientific Advisory Board. He served almost 15 years as Director of Quantitative Research at McKinley Capital Management, in Anchorage, Alaska. John is an Affiliate Instructor in the Department of Applied Mathematics, the Computational Finance and Risk Management Program, The University of Washington, Seattle, WA. He earned his AB in Economics from Duke University, MA in Economics from the University of Virginia, MSIM from the Georgia Institute of Technology, and Ph.D. in Finance from the University of Texas, Austin. Mr. Guerard took three of his doctoral seminars at Texas from Jan Mossin, a co-developer of the Capital Asset Pricing model. John taught at the McIntire School of Commerce, the University of Virginia, Lehigh University, and Rutgers University. John taught as an adjunct faculty member at New York University, and the University of Pennsylvania. He worked with the DAIS Group at Drexel, Burnham, Lambert, Daiwa Securities Trust Company, where he co-managed the Japanese Equity Fund portfolio with Harry Markowitz. While serving as Director of Quantitative Research at Vantage Global Advisors, Mr. Guerard was awarded the first Moskowitz Prize for research in socially responsible investing. John has published several monographs, including Corporate Financial Policy and R&D Management (Wiley, 2006), Quantitative Corporate Finance (Kluwer, now Springer, 2007, with Eli Schwartz, the third edition is at press, 2021), The Handbook of Portfolio Construction: Contemporary Applications of Markowitz Techniques (Springer, 2010), Introduction to Financial Forecasting in Investment Analysis (Springer, 2013), and The Handbook of Applied Investment Research (World Scientific Publishing, 2020, with William T. Ziemba). John serves an Associate Editor of the Journal of Investing and The International Journal of Forecasting and has published research in The International Journal of Forecasting, Management Science, the IBM Journal of Research and Development, Annals of Operations Research, Journal of Forecasting, Journal of Investing, Journal of Portfolio Management, The Financial Analysts Journal, Research in Finance, Research Policy, and the Journal of the Operational Research Society.

The Predictability of Stock Prices and Stock Returns: Is it Τhere and How to Find It

We examine the predictability of two of the major indices of stock market performance and valuation, the Dow Jones Industrial Average (DJIA) and the Standard and Poor’s 500 (S&P500). Our data span the full history of the two indices and, importantly for the DJIA cover the whole period even from before 1900’s. We can thus examine the difference in the predictability of the stock market under a broad range of economic and financial conditions. We focus on the predictability of both returns and prices and consider the use of (lags of) causal variables as possible predictors – these are the index of Leading Economic Indicators (LEI) of the Conference Board and the realized volatility of returns; the latter aggregated and computed from the daily data. Furthermore, we expand on the use of rolling window averaging (RWA), the combination of different segments of a time series to produce the forecast, suggesting different weighting schemes and empirically showing that the method performs extremely well. That is, the RWA models’ mean absolute forecasting errors (MAE) reductions are statistically significant at the 1% level during much of the 1990-2022 period. This is an important result as it takes away some of the a priori uncertainty as to which part of the time series to use in generating a forecast. We find that prices and returns are, at least locally in time, predictable, that the use of the causal variables is improving forecasting performance and that a set of models of limited complexity has very robust performance under many different time periods. While we have not, yet, used the insights of our results to evaluate their trading performance, we do make a provisional claim that forecasting prices and returns is doable with simpler models, provides realistic performance for the properties that these financial time series has and can be used in conjunction with any other inferential procedure that can offer recommendations about the future path of financial markets.

Co-Authors: Dr. John Guerard, Dr. Dimitrios Thomakos, Foteini Kyriazi and Konstantinos Mamais

Dr. Dimitrios Thomakos, Professor of Applied Econometrics, National and Kapodistrian University of Athens

Dr. Dimitrios Thomakos is Professor of Applied Econometrics and the Head of the Department of Business Administration at the National and Kapodistrian University of Athens, Greece. He is the Deputy Director of the International Centre of Economic Analysis and Co-Editor for the Review of Economic Analysis. He holds an M.A., M.Phil., and Ph.D. degrees in Economics from Columbia University and a B.A. degree in Economics from the National and Kapodistrian University of Athens. He is currently member in the Board of Directors of Eurobank Asset Management MFMC, Athens and Luxemburg. Dr. Thomakos has extensive industry experience, having previously worked as an expert advisor with Merrill Lynch in New York City, UBS and CQS in London, FengHe F&H Fund Management in Singapore and elsewhere, providing scientific, programming, and computational advice and expertise in forecasting, trading strategies and portfolio construction. His main area of current research is novel methodological contributions in forecasting, including forecasting random walks and short time series, and examining the use of simpler methods and models for successful forecasting. He has worked and published extensively in top field and general interest journals, such as the British Journal of Management, the International Journal of Forecasting, the European Journal of Operations Research, the Review of Economics and Statistics, and others, in forecasting, time series analysis, trading strategies, empirical finance, theoretical and applied econometrics and other areas in economics and finance. Dr. Thomakos is the co-author of the Forecasting with the Theta Method: Theory and Applications monograph and co-editor on other collective works.

Is crypto the next frontier of opportunities for quants?

A burgeoning derivatives market, the increasing presence of High Frequency Traders and big institutions moving into crypto all point to a bright future for the space. Meanwhile, blockchain-based technologies have the potential to radically disrupt traditional models for securities trading. This panel will discuss where quants should look for research and professional opportunities in the crypto markets. Will crypto markets become increasingly intertwined with traditional finance or does the space hold the potential to go its own way? What should quants interested in crypto be thinking in terms of the next step in their careers?

Dr. Artur Sepp, Head of Systematic Solutions and Portfolio Construction, Sygnum Bank

Artur Sepp is a Statistician who loves to connect financial applications with science and technology. He is Head of Systematic Solutions and Portfolio Construction at Sygnum Bank’s Asset Management in Zurich, specializing in systematic solutions for crypto assets and DeFi. Prior, Artur led quantitative research at a systematic hedge fund (Quantica Capital) focusing on data-driven investment strategies. Previous roles have been as front office Quant Strategist on the implementation of systematic solutions in private banking (Julius Baer), and on the full-cycle development of quantitative solutions and derivatives in investment banking (Merrill Lynch/BofA).

Artur has a PhD in Mathematical Statistics from University of Tartu, an MSc in Industrial Engineering and Management Sciences from Northwestern University, and a BA cum laude in Mathematical Economics from Tallinn University of Technology. His expertise covers quantitative investing and asset allocation, modeling of financial markets and instruments, statistical and Machine Learning methods, modern computational and programming tools. He is the author and co-author of several research articles on quantitative finance published in key journals.

Quantifying Geopolitical Risk: Data › Punditry

The presentation will explore systematically integrating geopolitical risk into asset and risk management decisions, contrasted against traditional pundit-based approaches. Mark Rosenberg, Ph.D. and Co-Head/Founder will introduce data-driven political risk assessment using the GeoQuant platform/application.

Dr. Mark Rosenberg, Founder, GeoQuant

Dr. Mark Rosenberg is a political economist and founder of GeoQuant. He received his PhD from UC Berkeley, where he was a National Science Foundation (NSF) Fellow and specialized in game theory and African politics. After Berkeley, he joined the political risk firm Eurasia Group (EG), where he was the Director of Africa, Comparative Analytics and Research Management. Mark also led product development at EG; he created the firm’s Political Trajectories and helped create its Political Risk Country Portfolio asset allocation model. Prior to this, Mark worked at the global human rights organization Freedom House, where he helped build their highly regarded democracy index and edited the flagship Freedom in the World publication. Mark teaches political risk analysis as an adjunct professor at Columbia University’s School of International and Public Affairs and UC Berkeley's Haas School of Business and has written and spoken widely on country and geopolitical risks. He was born in Johannesburg, South Africa and lives in Los Angeles with his wife and son.

Swap Rate fallback: unreasonable effectiveness of approximations and alternatives

Cash-settled swaptions with collateral discounting are impacted by the Swap Rate fallback mechanisms decided by working groups/ISDA. The legacy vanilla swaptions are becoming exotic products, as the mechanism is based on a non-linear transformation of the OIS swap rate, and generate convexity adjustments. It turns out that those two effects almost cancel each other and lead to almost vanilla products. We analyse those cancelling effects and the risk management impacts. Based on those insights, we propose an adjusted fallback mechanism that reduces further the exotic features and simplify further the risk management of the legacy book.

Dr. Marc Henrard, Managing Partner, muRisQ Advisory

Marc Henrard is a Managing Partner at muRisQ Advisory and visiting professor at University College London. Over the last 20 years, Marc has worked in various areas of quantitative finance including risk management, trading, software development, and quantitative research.

Marc's research focuses on interest rate modelling and risk management. He authored two books: The multi-curve framework: foundation, evolution, implementation and Algorithmic Differentiation in Finance Explained. Marc holds a PhD in mathematics from the University of Louvain, Belgium.

Is crypto the next frontier of opportunities for quants?

A burgeoning derivatives market, the increasing presence of High Frequency Traders and big institutions moving into crypto all point to a bright future for the space. Meanwhile, blockchain-based technologies have the potential to radically disrupt traditional models for securities trading. This panel will discuss where quants should look for research and professional opportunities in the crypto markets. Will crypto markets become increasingly intertwined with traditional finance or does the space hold the potential to go its own way? What should quants interested in crypto be thinking in terms of the next step in their careers?

Aaron Brown, Columnist, Bloomberg & Wilmott Magazine

Aaron Brown is a columnist for Bloomberg and Wilmott Magazine, and teaches at New York University, University of California at San Diego and New Mexico State University. He worked for 35 years on Wall Street as a trader, portfolio manager, head of mortgage securities and risk manager for firms including Morgan Stanley and AQR Capital Management. He is the author of The Poker Face of Wall Street, Red-Blooded Risk, Financial Risk Management for Dummies and A World of Chance (with Reuven and Gabrielle Brenner). He won the 2011 Risk Manager of the Year award from the Global Association of Risk Professionals. He was a top professional poker player in the 1970s and 80s, and continues active poker, sports betting and other gambling activities. He splits his time between Manhattan, New Mexico and Coronado Island. He has degrees from Harvard (Applied Math) and the University of Chicago (Finance and Statistics). He has been actively involved in crypto trading, venture capital and start-ups since 2011.

Complementarity of Quantum and Classical Machine Learning Methods with Application Financial Fraud Detection

In this talk, Dr. Ibrahim will present a first end-to-end application of a Quantum Support Vector Machine (QSVM) algorithm for a classification problem in the financial payment industry. Based on real card payment data, a thorough comparison is performed to assess the complementary impact brought in by the current state-of-the-art Quantum Machine Learning algorithms with respect to the Classical Approach. A new method to search for best features is explored using the Quantum Support Vector Machine's feature map characteristics. The results are compared using fraud specific key performance indicators: Accuracy, Recall, and False Positive Rate, extracted from analyses based on human expertise (rule decisions), classical machine learning algorithms (Random Forest, XGBoost) and quantum based machine learning algorithms using QSVM. In addition, a hybrid classical-quantum approach is explored by using an ensemble model that combines classical and quantum algorithms to better improve the fraud prevention decision. We found, as expected, that the results highly depend on feature selections and algorithms that are used to select them. The QSVM provides a complementary exploration of the feature space which led to an improved accuracy of the mixed quantum-classical method for fraud detection, on a drastically reduced data set to fit current state of Quantum Hardware.

Dr. Noelle Ibrahim, Global Quantum Industry Consultant, IBM

Dr. Noelle Ibrahim is a global IBM Quantum Industry Consultant for the Banking and Financial Markets industries. She has worked across verticals within the financial services sector, leading major transformational risk initiatives including stress testing and IFS9.

She has also worked in derivatives pricing, including vanilla and exotic options and modelling of cash flows from structured investment vehicles. She also has experience in the Fintech industry where she worked for a start up applying AI to art as an asset class. She has a depth and breadth of experience in quantitative finance, including quantitative models for Value at Risk (VaR), CVaR, Black-Scholes, Exotic Options pricing and back-testing, credit risk models for PD,EAD,LGD and more.

Noelle has a Ph.D. in Applied Physics from Columbia University, specializing in Quantum Monte Carlo methods for modelling classical and quantum systems. She also holds an M.Sc. in Quantum Optics and Condensed Matter Physics from the University of Toronto and a Bachelor’s degree in Physics from the University of British Columbia.

Is crypto the next frontier of opportunities for quants?

A burgeoning derivatives market, the increasing presence of High Frequency Traders and big institutions moving into crypto all point to a bright future for the space. Meanwhile, blockchain-based technologies have the potential to radically disrupt traditional models for securities trading. This panel will discuss where quants should look for research and professional opportunities in the crypto markets. Will crypto markets become increasingly intertwined with traditional finance or does the space hold the potential to go its own way? What should quants interested in crypto be thinking in terms of the next step in their careers?

Joe Morgan, Senior PR Manager, Bitfinex

Joe Morgan is Senior PR Manager at Bitfinex, a major cryptocurrency exchange with the most liquidity in Bitcoin trading. He was formerly a personal finance reporter for the Times of London and the Germany stock market correspondent at Bloomberg News in Frankfurt. Joe is the co-author of Day One Trader.

From Open Source to Industry Standard – A Journey of Derivatives Pricing Modeling

What began as a small pricing engine in a bank has become the quantitative backbone of an industry-leading risk service. The Open Source Risk Engine supports a huge variety of trades from all asset classes, and its analytics include pricing, XVA calculations, market risk measures and capital calculations. We present some of the key challenges and milestones along the way.

Dr. Roland Stamm, Partner - Quantitative Services, Acadia

Dr. Roland Stamm is a senior IT and Risk Management professional with extensive experience in wholesale banking management positions. As a Head of IT development, Roland was responsible for the enhancement of the capital markets products system. As Head of Market Risk Products, later Risk Methods and Valuation, he focused on market and credit risk methodology as well as the pricing and risk management of complex financial products. As a partner at Quaternion, Acadia’s Quant Services division, he is responsible for delivering projects in the quantitative market and credit risk space. Roland complements this work with research in the Mathematical Finance area. Roland holds a Ph.D. in Mathematics from the University of Muenster and a primary degree in Mathematics from the University of Mainz. He is co-author of the books “Discounting, LIBOR, CVA and Funding” (with Chris Kenyon) and “Modern Derivatives Pricing and Credit Exposure Analysis” (with Roland Lichters and Donal Gallagher).

Breakout Session: Applying the Open-Source Risk Engine for pricing and risk analysis

Discover the application of the Open-Source Risk Engine after Acadia’s main session “From Open Source to Industry Standard – A Journey of Derivatives Pricing Modeling” has taken you through the journey of the Open-Source Risk Engine from a small pricing engine in a bank to the quantitative backbone of an industry-leading risk service. In this session we will discuss how it has been used across institutions for valuations, model validation, CSA pricing, XVA calculation and much more with case studies from global banks and asset managers.

Dr. Roland Lichters, Co-Head - Quantitative Services, Acadia

Dr. Roland Lichters is Co-Head of Acadia’s Quantitative Services division. Prior to Acadia’s acquisition in 2021, he was Co-Founder and CTO of Quaternion Risk Management. Roland has headed Risk and IT departments for over ten years in the banking industry – building teams, processes, pricing/risk methodologies and systems. Roland is responsible for R&D, he focusses on the company’s pricing and risk analytics products, the development of industry-wide risk services, the Open Source Risk project (www.opensourcerisk.org), and he propagates the application of Open Source Risk Engine in the industry as a standard model validation tool and core part of risk production systems. Roland holds a Ph.D. in Physics, has been lecturing part-time in Financial Engineering at Trinity College Dublin for five years and is co-author of various publications including the book “Modern Derivatives Pricing and Credit Exposure Analysis”, Palgrave Macmillan, 2015.

Wilmott Magazine at 20

On a summer afternoon at the beginning of this millennium, Paul Wilmott sat down to explain what an option is to Dan Tudball. Paul explained the difference between Rocket Scientists and Plodders. Explained how some mathematicians can get hung up on the beauty of a formula over its practicality. Explained that the Black-Scholes formula’s assumptions were not realistic, but an entire industry was based on that formula. Explained that this wasn’t necessarily a bad thing since the faults with Black-Scholes were very clear. It probably wasn’t all in one afternoon, but whatever period of time it occurred over it was very quick, because the first issue of Wilmott Magazine had to be put together!

Two decades later Paul Wilmott will again sit down with Dan Tudball to reflect on the life and times of the publication that continues to provide the quantitative finance community with cutting-edge research, innovative models, new products and in-depth analysis. It’ll probably be quite quick, though because the 123rd issue of Wilmott Magazine has to be put together!

Dan Tudball, Editor, Wilmott Magazine

Dan Tudball is the Editor of Wilmott Magazine, the respected publication serving quantitative finance practitioners in finance, industry, and academia. The magazine publishes new work from leading authors in the field alongside columns from industry greats, and editorial reflecting the lifestyles and interests of a qualitatively demanding readership.

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.