The Hong Kong Society invites you to an exclusive evening gathering featuring leading experts in quantitative research, investment technology, and financial markets. This networking event brings together industry professionals to explore cutting-edge developments shaping the future of finance in Asia and beyond.
This session will delve into the critical role of granular market data and advanced analytical techniques for optimizing algorithmic trading strategies and ensuring best execution. It will touch upon the relevance of these concepts in traditional and emerging markets.
This session will delve into the critical role of granular market data and advanced analytical techniques for optimizing algorithmic trading strategies and ensuring best execution. It will touch upon the relevance of these concepts in traditional and emerging markets.
Financial crises, even at their worst, are familiar, episodic, and reversible. We know the tools: liquidity injections, recapitalizations, emergency legislation. Physical risks—climate change, demographic shifts, geopolitical disruptions, and the longer-term implications of AI—are different. They propagate through supply chains, cascade across industries and nations, and resist rapid remedy. A shuttered factory cannot be bailed out over a weekend; a water shortage or rising sea level reshapes entire economies and societies.
This talk discusses the framework for modeling physical and supply chain risk. The goal is not risk management in the narrow of employing statistical tools based on past prices. Rather, it is to build a structural understanding: to see where the real economy is most exposed, to map how shocks might spread, and to frame the constraints of adaptation and control. Compared to the familiar shocks of markets, the risks in view are longer-lived, harder to measure, and without precedent, and potentially existential. Modeling them requires rethinking the foundations of risk analysis.
This presentation explores the distinctions between AI and traditional quantitative modeling, which has been a staple in the industry for many years. We’ll delve into various use cases in equity research and fund management, highlighting how AI is addressing today’s diverse needs. Additionally, we will examine the implementation of Generative AI in asset management firms and share insights from pilot use cases. Finally, we’ll discuss the evolving roles and new skills required in the AI-driven landscape, particularly within asset management firms.
