2026 Zurich–Shenzhen Quantitative Finance and Risk Summer School

Quantitative Finance in the AI Era

Shenzhen & Zurich, July 9–17, 2026

The 2026 Zurich–Shenzhen Quantitative Finance and Risk Summer School is jointly organized by the Institute of Risk Analysis, Prediction and Management (Risks-X) at the Southern University of Science and Technology (SUSTech) and the UZH–ETH MSc in Quantitative Finance Program (MScQF).

Launched in 2023, the program connects Shenzhen and Zurich through a unique combination of academic training, industry practice, institutional visits, and international exchange. In 2026, the summer school will focus on Quantitative Finance in the AI Era.

Why Join?

AI is rapidly changing how quantitative research, trading, portfolio management, and risk analysis are done. This program helps participants understand not only how to use new tools, but also how to evaluate outputs, identify model limitations, and develop sound financial judgment.

Participants will:

• Learn from professors and practitioners from SUSTech, ETH Zurich, UZH, and leading financial institutions.

• Understand AI-assisted quantitative research workflows, including research automation, coding, debugging, and strategy prototyping.

• Gain exposure to China’s quant industry and Zurich’s international financial ecosystem.

• Visit financial institutions and interact with academics, practitioners, and MScQF-related resources.

• Build a broader view of quantitative finance, risk management, AI in finance, and global career paths.

Shenzhen Section

Dates: July 9–12, 2026
Location: Shenzhen, China
Language: Chinese
Focus: China quant industry, equity multi-factor research, AI-assisted quantitative research workflows

The Shenzhen section is designed as a compact four-day program focused on practical learning. It introduces students to the current landscape of China’s quantitative finance industry, the process of developing equity multi-factor strategies, and the new generation of AI-assisted quantitative research workflows.

Zurich Section

Dates: July 13–17, 2026
Location: Zurich, Switzerland
Language: English
Focus: Financial engineering, model failure, institutional practice, algorithmic trading, private banking, insurance regulation, and international finance exposure

The Zurich section is designed to complement the practical AI workflow training in Shenzhen. It emphasizes conceptual depth, financial judgment, institutional exposure, and international perspectives.

Rather than focusing only on AI tools, the Zurich section asks deeper questions:

• What should financial engineering programs train in the AI era?

• Why do traditional financial models fail under real market conditions?

• How should students evaluate AI-generated analysis?

• How do financial institutions use quantitative methods and AI in practice?

• What should not be automated in finance?

The Zurich program includes lectures, dialogues, institutional visits, project presentations, and career networking.

Key Faculty and Steering Committee

Prof. Didier Sornette

Professor Emeritus, ETH Zurich
Chair Professor, SUSTech Risks-X

Prof. Didier Sornette is a world-renowned scholar in complex systems, financial bubbles, systemic risk, and extreme events. He is known for his “Dragon King” theory and has made major contributions to financial crisis prediction, risk management, and the study of complex systems.

Prof. Erich Walter Farkas

Program Director, UZH–ETH MSc in Quantitative Finance
Professor of Quantitative Finance, University of Zurich

Prof. Farkas is the Program Director of the UZH–ETH MScQF program and a professor of quantitative finance at the University of Zurich. His research and teaching cover quantitative finance, mathematical finance, risk management, and financial engineering.

Prof. Ke Wu

Research Associate Professor and Assistant to Dean, SUSTech Risks-X

Prof. Ke Wu works on financial bubbles, quantitative trading, complex systems, data mining, and risk management. He is also one of the key organizers of the summer school and leads the Shenzhen section’s industry and AI-assisted quant research components. He founded Gaia-Qingke Fund Management LLC, one of the top quantitative hedge fund managers in China.

Selected Instructors and Industry Speakers

Prof. Josef Teichmann

Professor, ETH Zurich

Prof. Teichmann works at the intersection of mathematical finance, machine learning, and stochastic analysis. His lecture will introduce mathematical methods for new technologies in finance.

Dr. Vladimir Filimonov

Industry Expert in Algorithmic Trading

Dr. Filimonov has deep expertise in market microstructure, reflexivity, algorithmic trading, and real-world trading systems. His session will bring an institutional perspective on algorithmic trading and execution in the AI era.

Mr. Xiaoyou Chen

Founder of VeighNa Open-Source Quantitative Trading Platform

Mr. Chen is the founder of VeighNa, one of the leading open-source quantitative trading platforms. He will lead the Shenzhen hands-on module on AI-assisted quantitative research infrastructure and workflow.

Dr. Sihang Liang

Former Quant Researcher at Citadel

Dr. Liang will introduce the equity multi-factor research process, helping students understand the development chain from factor ideas to portfolio construction.

Mrs. Ruxandra Farkas

Insurance and Risk Management Expert

Mrs. Farkas specializes in insurance regulation, quantitative risk modeling, solvency, and model validation. Her session will broaden students’ understanding of quantitative risk beyond investment and trading.

Who Should Apply?

The program is suitable for:

• Undergraduate, master’s, and doctoral students interested in quantitative finance, financial engineering, AI, data science, risk management, and investment.

• Students planning to apply for international programs in quantitative finance, financial engineering, or related fields.

• Young practitioners in securities, asset management, fintech, banking, risk management, or quantitative investment.

• Participants who want to understand AI-driven quantitative research and international financial practice.

A strong interest in finance, data, models, AI, or markets is expected. Prior experience in quantitative finance is helpful but not required.

What You Will Gain

• A systematic understanding of quantitative finance and risk management in the AI era.

• Exposure to AI-assisted research workflows and practical quant research methods.

• Direct interaction with leading professors and industry practitioners.

• Institutional visits and international finance exposure in Zurich.

• Certificate of participation and credit certificate.

• Internship and career recommendation opportunities for outstanding full-program participants, subject to program arrangements.

Participation Options

Applicants may choose:

• Option 1: Full Program

Shenzhen + Zurich

Participants joining the full program will have access to the complete curriculum, including Shenzhen hands-on training, Zurich lectures and visits, project work, project presentations, awards selection, and internship / career recommendation opportunities.

• Option 2: Zurich Section Only

Participants may apply to join only the Zurich section. Zurich-only participants will attend Zurich lectures, visits, and networking activities. However, they will not participate in the full-program project, project presentation, awards selection, or project-based evaluation.

Application

Applicants are expected to submit:

• English CV

• Transcript in Chinese or English (for current students)

• Certificate of enrollment for current students (for current students)

• Optional materials showing quantitative ability, such as papers, reports, code, projects, or competition experience

Registration

Please apply through the official registration form: https://docs.google.com/forms/d/e/1FAIpQLSef1_A5A1LIRl8Gq14dOEmvt0ED1saWDZ06gc-31CwGrkjgrw/viewform?usp=dialog

Applications will be reviewed on a rolling basis. Early application is encouraged.