Quant Insights Conference:
Volatility and Risk in Quant Finance

Fast Times, Slow Times and Timescale Separation in Financial Timeseries Data

Quantitative strategies rely on stationarity of the underlying processes. Parameter drift eventually kills all strategies, how ever brilliant they may be. This talk will explore some methods for unmixing financial timeseries using intrinsic relaxation timescales, recovering any stationary processes, but also allowing us to separate “slow” from “fast” processes. This has various interesting implications for trading and portfolio allocation, which we will briefly discuss.

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

Dr. Paul Wilmott 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.

Paul has extensive consulting experience in quantitative finance with leading US and European financial institutions. He has founded a volatility arbitrage hedge fund and a university degree course. Paul has lectured at all levels, to students and to practitioners.

How AI is Used to Generate Alpha in Investing

AI is widely used in many professions including medicine as AI can help in detecting patterns. How is AI used in a low signal to noise environment like investing to generate Apha?

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.

The Science and Practice of Trend-following Systems

We derive an exact relationship between the profit-and-loss (P&L) of a trend-following system with exponentially moving average (EWMA) filter and the auto-correlation function of returns generating stochastic process. This generic result appears to be new. Using this formula, we analyse the impact of the lookback span of EWMA filter on the P&L of the trend-following system when returns dynamics are driven by auto-regressive fractal processes with long memory. We show that the trend-following system is expected to perform well when autocorrelation of returns is positive over longer time scales, even if returns may exhibit mean-reversion over shorter time scales.

In the empirical part, we examine the autocorrelation observed in major futures markets and the performance of different trend-following systems applied to futures markets. We discuss and contrast the so-called American and European specifications of trend-following systems. Finally, we demonstrate the defensive profile of trend-following systems which provides diversification benefits to long-only portfolios.

Dr. Artur Sepp, Head Quant, LGT Bank

Dr. Artur Sepp is the head quant at LGT bank in Zurich focusing on quantitative asset allocation and systematic investment strategies. Artur has over 15 years of experience in financial markets including heading quant research and portfolio management at a systematic hedge fund and a family office as well as leading development of front-office quant strategies and derivatives at private (Julius Baer) and investment banks (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, quantitative modelling of derivative securities, machine learning and data science, and blockchain applications within decentralised finance. He is the author and co-author of several research articles on quantitative finance published in key journals. Artur won Risk Magazine’s Quant of the Year Award (2024).

How AI is Used to Generate Alpha in Investing

AI is widely used in many professions including medicine as AI can help in detecting patterns. How is AI used in a low signal to noise environment like investing to generate Apha?

Dr. Rick Bookstaber, Director of Risk Research, MSCI Inc.

Rick Bookstaber leads risk research at MSCI. He has held the role of chief risk officer at two of the world’s largest hedge funds, Moore Capital and Bridgewater, at the investment banks Morgan Stanley and Salomon and, most recently, at the pension and endowment of the University of California. During the 2008 global financial crisis Rick served at the U.S. Treasury Department and Securities and Exchange Commission to help reformulate the oversight of the financial system. He is the author of The End of Theory and A Demon of Our Own Design. Rick holds a doctorate in economics from the Massachusetts Institute of Technology.

Causal Asset and Factor Network Interfence under Treatment Effects

The focus is the application of scenario-causal asset and factor network interference to model and investigate the network effects of specific interventions or influences on the node level under potential outcomes. The underlying assumption is that the nodes in the network are not isolated; instead, the interactions between them define both the indirect, direct and combined impacts of the interventions, a principle referred to as causal network interference.

In the context of financial markets, such effects could be triggered actions such as central bank policies, regulatory activities affecting nodes, or "interventions" in the form of return predictions conducted within an investment process. Unlike actions that directly affect edges, these interventions impact nodes, which are interconnected via edges that may facilitate spillover effects to other nodes.

Dr. Gueorgui S. Konstantinov, Senior Portfolio Manager

Gueorgui S. Konstantinov, Ph.D, CAIA, FDP is a senior portfolio manager and has over 18+ years of experience. He managed global bond portfolios and currencies for institutional investors and pension funds. He is an editorial board member of The Journal of Portfolio Management, The Journal of Alternative Investments, and The Journal of Financial Data Science. He earned the designations of Chartered Alternative Investments Analyst (CAIA) and Financial Data Professional (FDP). He received his MA in economics in 2005 and received a doctoral degree in 2008 from Vienna University of Economics and Business Administration (WU).

U.S./Trump 2.0: Accelerating “EM-ification” Drives Systemic Risks to U.S. Treasuries, High Uncertainty Around Regulatory Reforms

Dr. Mark Rosenberg, Founder, GeoQuant

Mark Rosenberg, PhD, is Founder and Co-Head of GeoQuant, acquired by Fitch Group in 2022 and now part of BMI, a Fitch Solutions company. 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 family.

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

Dr. Randeep Gug is the Managing Director of the CQF Institute and 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.