Event description
In today’s competitive hiring landscape, a strong quant finance resume is more than a summary of experience, it is a key tool for opening doors to the right opportunities.
Whether you are aiming for your first role in quant finance, looking to move into a more senior position, or exploring opportunities in a new market, knowing how to position your background effectively can make a significant difference.
Join Rainy Gill for this online talk, where she will share practical guidance on how to optimize your quant finance resume for today’s market. Rainy will discuss common pitfalls to avoid, ways to present your skills and experience more effectively, and how to create a resume that stands out in a crowded field.
Event Description
Modern deep learning delivers strong accuracy but says little about how much to trust any single prediction – a real obstacle in risk-sensitive, regulated settings. Classical kernel methods, by contrast, come with a mature theory of error, but have not, until recently, scaled to or plugged into deep architectures.
This talk presents a way to close that gap: kernel components that slot into standard deep-learning pipelines – from a classification head to a transformer sub-block – while carrying a computable, geometry-aware error estimate for each prediction, one that propagates through the full model. The result is a kernel-based counterpart to conformal prediction: a step toward deep models whose outputs are auditable, prediction by prediction, rather than a black box.
Across vision, reinforcement learning and tabular data, these kernel components match the accuracy of their neural counterparts – error-awareness need not cost accuracy. I will discuss what this opens up for finance and insurance, where quantifying and auditing model error is increasingly a requirement, not a luxury.
Event Description
This talk will present a framework for valuing a specific type of structured product: equity investment certificates. It will introduce an innovative time-dependent extension of the Heston model, designed to improve calibration to market data by replicating not only the usual short-term quoted range, but also a long-term target volatility level.
The talk will also explore how the Oztukel-Wilmott empirical historical volatility analysis model can be used to estimate this long-term target volatility. Finally, it will demonstrate the framework through a real-life case study of a Twin Win Autocallable on the Euro Stoxx Banks Index.
Event Description
Environmental, social, and governance (ESG) considerations are playing an increasingly important role in investment decision-making. But for many investors, particularly pension fiduciaries, the central challenge remains the same: how to align responsible investing objectives with the financial interests of beneficiaries.
In this talk, Dr. John Guerard examines the relationship between ESG screening and portfolio performance through a statistical review of the KLD database. The session explores how robust regression techniques can be applied in stock selection modelling to address the presence of outliers in financial data and improve portfolio construction using Sharpe and Information Ratios.
What You’ll Gain
- Insight into how ESG criteria can influence portfolio construction and investment outcomes
- Understanding of how robust regression can improve stock selection modelling in the presence of outliers
- Perspective on the trade-offs between social responsibility objectives and financial performance
- Knowledge of how individual ESG screens compare with composite ESG approaches in risk-adjusted portfolio performance
- Awareness of the limitations and evolution of investment databases such as KLD and the implications for research
Who Should Attend
This session is ideal for:
- Portfolio managers and asset allocators
- Quantitative analysts and investment researchers
- ESG and sustainable investment professionals
- Pension trustees and fiduciaries
- Students and professionals interested in portfolio construction and responsible investing
Event Description
Join us for an unfiltered conversation with CQF alumni on what it really takes to break into quant finance – and how AI is transforming the work of professionals in the industry. From first roles and pivotal projects to real-world AI use cases and how quant roles are changing, this panel will share practical lessons, honest challenges, and actionable advice for anyone exploring or building a career in quantitative finance.
Learning Outcomes:
- Understand the critical expertise and knowledge for quantitative finance professionals.
- Appreciate how AI may reshape future workflows, and career opportunities over the next 12-24 months.
- Apply alumni insight to audience’s own learning and development.
Event Description
Crypto assets represent a new financial primitive whose behavior cannot be fully explained by classical asset pricing theory. Unlike traditional securities, they operate at the intersection of stochastic processes, network theory, game theory, cryptography, and mechanism design, within an open, continuously evolving market microstructure.
This presentation explores the mathematical foundations of crypto assets, focusing on how value, risk, and dynamics emerge from protocol-level rules rather than centralized issuers.
Event Description
For the special, but important, case of American option pricing, practitioners often find that otherwise well-functioning finite difference methods yield results that are slower, less accurate, and less stable than expected. Perhaps as a consequence, simpler special-purpose methods (e.g., the binomial tree) are sometimes preferred for American options, despite various theoretical and practical drawbacks. In this talk we show how to remedy this situation, through a range of minimally invasive “tips and tricks” that significantly improve the speed and stability of the popular theta-method finite difference scheme when applied to American option values and greeks.
Event Description
False findings in financial research can lead to costly misallocations, flawed regulation, and misguided strategies. This event explores why these errors occur, focusing on the widespread assumption that financial time series are stationary and a-Holder continuous- an assumption at odds with markets shaped by regime shifts, stochastic volatility, and structural breaks.
Through case studies spanning AI-driven models and advanced quantitative techniques, Bloch argues for a fundamental shift toward methodologies that embrace non-stationary dynamics and recognize the limits of prediction in complex systems.
What You’ll Gain
- Critical insights into why false findings persist in financial research and their real-world impact
- Understanding of flawed assumptions in financial modeling, particularly around stationarity and continuity
- Exposure to case studies demonstrating failures in AI-driven models and quantitative techniques
- Alternative frameworks that embrace non-stationary dynamics and market complexity
- Practical perspective on the limits of prediction in complex financial systems
Who Should Attend
This session is ideal for:
- Quantitative analysts and financial researchers
- Risk managers and model validators
- Data scientists working in finance
- Anyone interested in the intersection of AI, finance, and model reliability
- Students and professionals concerned with research integrity and methodology
Event description
Breaking into quant finance is highly competitive, and interview success requires more than just technical expertise. This session will demystify the quant interview process, giving you practical tools and confidence to navigate even the most challenging questions.
Brian will walk you through real-world scenarios, share common pitfalls to avoid, and reveal what separates good candidates from exceptional ones. Whether you’re preparing for your first quant role or looking to advance your career, this session will equip you with actionable strategies to make a lasting impression.
What You’ll Gain
- Insider perspective on what top quant finance employers are really looking for
- Proven frameworks for tackling technical and analytical interview questions
- Practical techniques to demonstrate your quantitative skills and problem-solving prowess
- Expert preparation strategies and curated resources to give you a competitive edge
- Understanding of interviewer psychology and how to craft compelling, aligned responses
Who Should Attend
This session is ideal for:
- Students and graduates exploring careers in quantitative finance
- Early-career professionals preparing for quant interviews
- Anyone looking to transition into quantitative roles in finance
- Individuals seeking to sharpen their interview technique and market understanding
Event Description
This study investigates the market impact of the US-Mexico-Canada Trade Agreement (USMCA) on the stock market returns and volatility spillovers across the respective countries. We show that investors’ responses were significantly negative for each of the countries and most sectors around the critical event dates. The negative return impacts observed are consistent with multilateral wealth destruction for each party to the agreement and to the bloc as a whole. Volatility spillover effects are observed, with the US having largest impact. No significant evidence of a change in the volatility spillover effect is the period subsequent to USMCA official ratification. Since its inception, ongoing trade disputes as a consequence of USMCA led to speculation that the agreement’s future is dubious in the upcoming review in July 2026. This speculation has turned to almost a certainty with the inception of a Strategic Trade War between the parties on February 5, 2025.
Learning Outcomes
- Understand the impact of trade agreements on equity markets
Explain how the USMCA influenced stock returns and investor sentiment across the US, Mexico, and Canada.
- Analyze volatility spillover effects during geopolitical events
Identify how volatility transmission occurs between markets and why the US had the largest influence.
- Evaluate market risks arising from ongoing trade disputes
Discuss the implications of strategic trade wars and the uncertainty surrounding USMCA’s future.
