World Business StrategiesServing the Global Financial Community since 2000

Conference Stream

08.15 – 09.00

Registration and Welcome Coffee

09.00 – 09.45: Doing more with tick data: a Machine Learning approach

Edith Mandel:

Principal, Greenwich Street Advisors, LLC

09.45 – 10.30: Smartly Managing Risk for Complex Payoffs

Risk managing exotic derivatives in today’s financial markets is challenging due to their intricate structures. Our approach enhances traditional Greek-based hedging by incorporating dynamic risk factors, crucial for managing the variable Vega profiles of exotic payoffs. Further, we employ a data-driven strategy using a Value Function Neural Network (VNN) to identify risk factors that drive PnL, with feature engineering playing a vital role in building an effective exotics learning model. This method uses a componentized approach, integrating a Differentiable Linear Constraint Layer, Gradient Surgery, and the VNN for scalability. This innovative strategy boosts efficiency and effectiveness, offering a strategic edge and demonstrating potential for broad application in complex derivatives.

JPMorganChase logo

Nina Wu:

Quantitative Research Associate at J.P. Morgan

Mengdi Wang:

Quantitative Research Vice President, JPMorganChase

10.30 – 11.00: Morning Break and Networking Opportunities

11.00 – 11.45: “This is the Real World, Not Barbie World”

Inflation is not a trade or a macro call about what is going to happen in the future. Inflation is a risk to all investors, especially savers as they move closer to retirement. How to measure and invest in inflation and rate volatility markets will be the topic of this discussion.

Nancy Davis:

CIO and Managing Partner, Quadratic Capital

11.45 – 12.30: PANEL: Talent Attraction & Retention:

Recruiting/Retaining talent

  • What are QR Financial Services currently doing and what should they be doing to attract more female talent?
  • What strategies are financial companies using to retain talent? Is there anything else that could be done?

Career progression

  • At more senior levels the number of women is even lower than at entry level which means that the female population retention rate is low or/and women are not being promoted. Discuss
  • Are quantitative positions too specialised which prevents women (and men) to move horizontally to different (and possibly more senior) roles?
  • Hybrid working model-does it benefit for retaining/advancing women careers?
  • Mentoring vs sponsorship programmes that could specifically help Diversity & Inclusion.
  • Limitations for progression in challenging times when there is less opportunities available
  • Is there difference in diversity approach/success between US vs Euro banks?
  • Company diversity targets-good idea?
  • Do junior female employees face unique barriers?
  • How to overcome unconscious bias:
    • Have you personally experienced instances of gender bias in the workplace?
    • Has it gotten better over the years?

Moderator:

Christina Qi:

CEO, Databento

Victoria Averbukh:

Professor of Practice & Director of Cornell Financial Engineering Manhattan

Lily Gu:

Quantitative Researcher, Bloomberg LP

Mante ZB:

Quantitative Research Executive Director, JPMorganChase

Shulin Liu:

Director Markets Quantitative Analytics, Barclays

12.30 – 13.30: Lunch Break

13.30 – 14.15: Assess how a combination of the right model, causal feature discovery, and conformal prediction can strengthen market prediction.

  • Provide a technical overview of how different models including GLM / GAM / ML are applied for stock market prediction
  • Highlight the model challenges present without incorporating causality into research process
  • Process and train models to mitigate these inherent risks and maximize prediction accuracy with causality
  • Understand the role of conformal prediction in advancing methods of quantitative trading

Judith Gu:

Managing Director, Head of Equities & eFX Quant Strategist, Scotiabank

14.15 – 15.00: “Introduction to Generative AI managed services on AWS”

Mojgan Ahmadi:

Head of Markets Data Science Platform Architecture, Barclays

15.00 – 15.45: Towards High Performance Large Generative AI Models for Domain-specific Code Generation

Abstract: In recent years, significant advancements in artificial intelligence have been driven by the development of Deep Neural Networks (DNNs) and Transformer-based models, including BERT, GPT-3, and other Large Language Models (LLMs). These technologies have catalyzed innovations in various fields such as autonomous driving, recommendation systems, and chatbot applications. DNNs are increasingly designed with deeper, more complex structures and require larger computational resources. As computational demands escalate, model sparsification has emerged as a promising method to reduce model size and computational load during execution. Given the evolution of high performance computing platforms, particularly advanced GPUs, end-to-end DNNs runtime speedup with model sparsification is an ideal but difficult goal due to the intricacies involved in sparsity which may need the change of matrix and kernel settings.

In this talk, I will present our recent efforts in domain-specific code generation and system optimizations. It mainly focuses on the following innovative aspects: (1) our recent works on using generative AI models for high-quality domain specific code generation and the cooperative competitive (coopetitive) framework design for code generation in general domains; (2) an advanced sparse progressive pruning method which show for the first time that reducing the risk of overfitting can help the effectiveness of pruning; (3) an novel self attention architecture design for Transformer-based models inference acceleration.

Shaoyi Huang:

Assistant Professor at Stevens Institute of Technology

15.45 – 16.15: Afternoon Break and Networking Opportunities

16.15 – 17.00: Lessons Learned from Starting a Hedge Fund

Christina Qi:

CEO, Databento

17.00 – 17.45: “Measuring Performance of AI-Based Strategies: Advances in Optimization”

So, you have distinct AI strategies. Now what? How do you compare their performance and usability? This talk focuses on the latest techniques for measuring and evaluating AI-based output.
Computer Scientists have made significant inroads in evaluating performance of AI strategies. We will review:

  • The state-of-the-art performance measurement of AI models
  • Irene Aldridge’s latest research in this space
  • Implementation with specific Quant Finance examples

Irene Aldridge:

CEO and Founder, AbleBlox and AbleMarkets

17.45 – 18.30: PANEL: Career Progression:

1. How has the idea of a quant woman changed over time?

2. What were the most memorable times you can think of when you think of being a woman in quant finance?

3. How do you balance family and work?

4. How does raising children factor in with your career?

5. What were the hardest or most interesting career lessons you had to learn?

6. Did your academic experience prepare you for the work life in quant finance? If so, how?

Moderator:

Irene Aldridge:

CEO and Founder, AbleBlox and AbleMarkets

Nancy Davis:

CIO and Managing Partner, Quadratic Capital

Joanna Brard:

Executive Director, JPMorgan Chase & Co.

Shilpa Akella:

Shilpa Akella: Managing Director, Head of Equities Structuring Americas, Barclays

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