08.15 – 09.00
Registration and Welcome Coffee
09.00 – 09.45: Topic to be confirmed
Prof. of Mathematical Finance, Bayes Business School (formerly Cass)
Laura Ballotta: Prof. of Mathematical Finance, Bayes Business School (formerly Cass)
Dr Ballotta works in the areas of quantitative finance and risk management. She has written on topics including stochastic modelling for financial valuation and risk management, numerical methods aimed at supporting financial applications, and the interplay between finance and insurance.
Recent major contributions have appeared in Journal of Financial and Quantitative Analysis, European Journal of Operational Research and Quantitative Finance among others.
She serves as associate editor and referee for a number of international journals in the field.
Laura Ballotta obtained her PhD in Mathematical and Computational Methods for Economics and Finance from the Università degli Studi di Bergamo (Italy), following her BSc in Economics from Università Cattolica del Sacro Cuore, Piacenza (Italy), and MSc in Financial Mathematics from the University of Edinburgh – jointly awarded with Heriot-Watt University (UK). Laura has previously held positions at Università Cattolica del Sacro Cuore, Piacenza (Italy), and Department of Actuarial Science and Statistics, City University London (UK).
09.45 – 10.30: Deep Hedging
Traditional risk management is based on the Greeks provided by classical valuation models. These models typically have simplified dynamics and assume perfect hedge-ability.
As a result, decisions on when and how to hedge are based on traders’ intuition, experience, and view on market dynamics.
With Deep Hedging , we go beyond Greek-based hedging and take a new approach to exotics risk management.
Deep Hedging formulates the hedging problem as a reinforcement learning problem and shifts towards the machine learning paradigm.
We solve for the optimal hedging in incomplete markets using a periodic policy search.
The model-based policy search approximates the hedging actions, the policy, using deep neural networks.
Executive Director, JP Morgan
Amira Akkari: Executive Director, JP Morgan
Amira is an Executive Director at JP Morgan CIB. She is one of the leads of the Quantitative Research team for Equity Derivatives Exotics. She has 15 years’ experience in the quant industry and has worked with industry leaders in this space.
The Front Office quant team works closely with traders to enhance and expand Equity models for Exotic products’ risk management. Amira has expanded her focus in the last years to cover AI models and data-driven solutions’ development and adoption for financial applications in Markets.
Models include classic supervised learning as well as reinforcement learning models for derivatives risk management, such as Deep Hedging. JP Morgan was elected Equity House of the Year by Risk Magazine, twice in the last three years; quant innovative models were cited as key factors in this success
10.30 – 11.00: Morning Break and Networking Opportunities
11.00 – 11.45: Large Language Models and how they can be applied in finance
Head of Quantitative Modelling, Probability & Partners. Associate Prof, Vrije Universiteit Amsterdam
Svetlana Borovkova: Head of Quantitative Modelling, Probability & Partners and Associate Professor, Vrije Universiteit Amsterdam
Dr Svetlana Borovkova is the partner and Head of Quant Modelling of risk management consulting firm Probability and Partners and an Associate Professor of Quantitative Finance and Risk Management at the Vrije Universiteit Amsterdam. She is the author of over 60 academic and professional publications and a frequent speaker at conferences such as RiskMinds and QuantMinds. Her work encompasses a wide range of topics, ranging from derivatives pricing and risk modelling to sentiment analysis for quant investing and machine learning in quant finance. Find her work at SSRN and her columns on various finance topics in Financial Investigator.
11.45 – 12.30: PANEL: Talent Attraction & Retention:
- 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?
- 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?
- How to overcome unconscious bias
VP, Fixed Income Quantitative Trading: Jefferies International Ltd
Burcu Karabork: Vice President, Fixed Income Quantitative Trading: Jefferies International Ltd
Burcu is a Vice President in the Fixed Income Quantitative Trading team at Jefferies International Ltd. Previously she worked at NWM from 2012 on the Technology Graduate Scheme as a quant developer. She holds an MEng (Hons) in Aeronautical Engineering from the University of Bristol. She has spent the last few years working on the bank’s unified risk engine and has more recently returned to her more maths-centric roots in the eFI space.
Quantitative Analyst, UBS
Leila Korbosli: Quantitative Analyst, UBS
Leila is currently a quantitative analyst at UBS where she is part of the firm’s Advanced Cloud-based Quantitative Analytics ACQA Platform, in charge of building and delivering cutting edge trading tools. She started her career in Quantitative Research at Lehman Brothers in 2007 focusing on IR exotics and hybrids and then built an extensive cross-asset modelling experience on the sell-side across different asset classes as a quant and a trader in Rates/FX, Credit and XVA. Leila holds an engineering degree in Applied Mathematics and Computer Science from ENSIMAG (2006) and a masters in Probability and Finance from Paris VI-Ecole Polytechnique (2007). She is the co-author of the book “Global Derivatives: Products, Theory and Practice”, World Scientific.
Chief Data Scientist, Head of AI & Quant Research, Wyden Capital AG
Nicole Königstein: Chief Data Scientist, Head of AI & Quant Research, Wyden Capital AG
Nicole Königstein is a distinguished Data Scientist and Quantitative Researcher, currently working as Data Science and Technology Lead at impactvise, an ESG analytics company, and as Head of AI and Quantitative Research at Quantmate, an innovative FinTech startup focused on alternative data in predictive modeling. Alongside her roles in these organizations, she serves as an AI consultant across diverse industries, leading workshops and guiding companies from the conceptual stages of AI implementation through to final deployment.
As a guest lecturer, Nicole shares her expertise in Python, machine learning, and deep learning at various universities. She is a regular speaker at renowned AI and Data Science conferences, where she conducts workshops and educational sessions. In addition, she is an influential voice in the data science community, regularly reviewing books in her field and offering her insights and critiques. Nicole is also the author of the well-received online course, “Math for Machine Learning.
12.30 – 13.30: Lunch Break
13.30 – 14.15: Chatting with Markets using Retrieval Augmented Generation (RAG)
I have a Ph.D. in Computer Science from Purdue University. In addition, I have completed graduate coursework in Financial Mathematics at NYU and Big Data at Harvard University. Prior to joining Citadel, I was a Director in the Global Markets Division at BNP Paribas where I managed the Interest Rate Options & Inflation quantitative research team. Before transitioning into Finance, I was a research staff member at the IBM T. J. Watson Research Center.
14.15 – 15.00: Topic and Presenter to be Confirmed
15.00 – 15.45: Pairs Trading with Kalman Filter
Abstract: This talk is focused on the application of Kalman filter in pairs trading, along with comparison with other common techniques.
Quantitative Researcher, Bloomberg
Cindy Liu is a quantitative researcher at CTO Office in Bloomberg.
15.45 – 16.15: Afternoon Break and Networking Opportunities
16.15 – 17.00: Topic and Presenter to be confirmed
17.00 – 17.45: Topic and Presenter to be confirmed
17.45 – 18.30: PANEL: Career Progression:
- Do you think that being a woman is a significant factor in slowing down career progression in QR Financial Services? Is it still hard to make it to the top positions, if so why and what can be done to change the situation? If applicable, discuss about gender diversity issues (discuss numbers, policies, how to address it)
- Discuss female role models in finance and significant achievements
- Maternity leave
- Has Shared Parental Leave (SPL) helped equality in this area?
- How important are the following:
- Promotions/Career opportunities
- Pay gap elimination
- Agile/Flexible working
- Getting the feedback you need (even if you don’t really want it)
- Supporting each other
- Discuss the current career return to work strategies available
- Have you benefited from any such schemes?
- Discuss the Importance and value of mentorship and sponsorship
- What mentoring programs are available for juniors if any?
University of Oxford, Academic Visitor & Immersive Finance, co-Founder
Katia Babbar: University of Oxford, Academic Visitor & Immersive Finance, co-Founder
Associate Professor in Mathematical and Computational Finance, University of Oxford
Blanka Horvath: Associate Professor in Mathematical and Computational Finance, University of Oxford and Researcher, The Alan Turing Institute
Blanka research interests are in the area of Stochastic Analysis and Mathematical Finance.
Including asymptotic and numerical methods for option pricing, smile asymptotics for local- and stochastic volatility models (the SABR model and fractional volatility models in particular), Laplace methods on Wiener space and heat kernel expansions.
Blanka completed her PhD in Financial Mathematics at ETHZürich with Josef Teichmann and Johannes Muhle-Karbe. She holds a Diploma in Mathematics from the University of Bonn and an MSc in Economics from the University of Hong Kong.
Head – Credit/Repo Market and Counterparty Risk Methodologies, BNP Paribas
Mirela Predescu: Head – Credit/Repo Market and Counterparty Risk Methodologies, BNP Paribas
Mirela Predescu is a manager at BNP Paribas, London, heading a team responsible for market and counterparty risk models for credit and repo products. Prior to BNP Paribas, Mirela has held positions in the portfolio modelling team at Lloyds Banking Group and the quantitative analytics team at Fitch Solutions. Before moving to the financial industry, Mirela was a University Lecturer at Saïd Business School, University of Oxford. Mirela holds a PhD in Finance from Rotman School of Management, University of Toronto and an MA in Economics from University of Toronto.
Global Head of Product Valuation Methodologies and VCG Digital, Citi
Milena Imamovic-Tomasovic: Global Head of Product Valuation Methodologies and VCG Digital, Citi
Milena Imamovic-Tomasovic is a quantitative finance professional with over fifteen years of experience in banking. Her current role is Global Head of product valuation Methodologies and VCG Digital in Citi. Prior to that, she was Head of Business-Aligned Valuation Methodology within Global Valuation Group team and Head of CVA and Funding Methodology within GVG Methodology in Deutsche Bank. Before that Head of Analytics, EMEA at HSBC where she headed a cross-asset Valuation Control quant team. Before joining HSBC, Milena worked at TD Securities as a model validation and subsequently front office equity quant. She holds a Ph.D in theoretical physics from the University of Toronto.