World Business StrategiesServing the Global Financial Community since 2000

Women in Quantitative Finance Conference (WQF)

08.00 - 08.55
Registration and Morning Welcome Coffee
08.55 - 09.00
Women in Quantitative Finance Chair:

To be confirmed

09.00 - 09.40
Keynote: To be confirmed
09.40 - 10.20
Topic to be confirmed

Christoph Burgard:

Head of Risk Analytics For Global Markets, Bank of America Merrill Lynch

Christoph Burgard: Head of Risk Analytics For Global Markets, Bank of America Merrill Lynch

Christoph Burgard heads the Risk Analytics team for Global Markets at Bank of America Merrill Lynch, which he joined in November 2015. Prior to this he spent 16 years at Barclays, where he was leading the Equity Derivatives and XVA front office Quantitative Analytics teams for the investment bank as well as the ALM modelling area for the bank’s treasury department. Christoph was named Risk Magazine’s Quant of the Year 2015 for his pioneering work on FVA. He has a PhD in Particle Physics from Hamburg University and was a research fellow at CERN and DESY.

10.20 - 11.00
Deep Learning for Automatic Feature Generation for Time Series Forecasting

Abstract:

There is an attempt to construct a DeepNN architecture that enables to automatically extract relevant features at relevant timestamps in the past for prediction of future price movement. The approach is based on the paper “DeepLOB: Deep convolutional Neural Networks for Limit Order Books” by Zhihao Zhang, Stefan Zohren and Stephen Roberts. Using the proposed techniques we try to automatically generate features from Limit Order Book for different asset classes and compare the generated features with those that are hand-crafted and give good results in prediction.

Presenter to be confirmed

11.00 - 11.30
Morning Break and Networking Opportunities
11.30 - 12.30
PANEL: Talent Attraction & Retention

Topics:

  • What are QR Financial Services currently doing and what should they be doing to attract more female talent?
  • What can Universities and Recruitment companies do to help?
  • What strategies are financial companies using at present if any?
  • What are QR Financial Services currently doing and what should they be doing to retain female talent?
  • What top positions besides Asset Management can QF- profiled women occupy?
  • For each position open, the percentage of female CVs submitted is very small (if not none). Why is this happening and how can universities/headhunters/companies work together to improve the numbers?
  • 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.
  • Mentoring programmes that could specifically help Diversity & Inclusion.
  • Are quantitative positions too specialised which prevents women (and men) to move horizontally to different (and possibly more senior) roles?

Moderator:

  • Helyette Geman: PhD, PhD: Professor of Mathematical Finance, Birkbeck – University of London & Johns Hopkins

Panellist:

Helyette Geman:

Professor of Mathematical Finance, Birkbeck – University of London & Johns Hopkins

Helyette Geman, PhD, PhD: Professor of Mathematical Finance, Birkbeck – University of London & Johns Hopkins

Helyette GEMAN is a Professor of Mathematical Finance at Birkbeck – University of London and at Johns Hopkins University. She is a Graduate of Ecole Normale Supérieure in Mathematics, holds a Masters degree in Theoretical Physics, a PhD in Probability from the University Pierre et Marie Curie and a PhD in Finance from the University Pantheon Sorbonne.
She has been a scientific advisor to a number of major energy and mining companies for the last 20 years, covering the trading of crude oil, natural gas, electricity as well as metals in companies such as EDF Trading, Louis Dreyfus or BHP Billiton and was named in 2004 in the Hall of Fame of Energy Risk.
Prof Geman was previously the head of Research and Development at Caisse des Depots. She has published more than 140 papers in major finance journals including the Journal of Finance, Mathematical Finance, Journal of Financial Economics, Journal of Banking and Finance and Journal of Business. She has also written the book entitled Insurance and Weather Derivatives and is a Member of Honor of the French Society of Actuaries.
Her research includes exotic option pricing for which she got the first prize of the Merrill Lynch awards, asset price modeling through the introduction of transaction time (JOF, 2000); she is one of the authors of the CGMY pure jump Levy model (2002). Prof Geman had organized in 2000 at College de France the first meeting of the Bachelier Finance Society, with Paul Samuelson, Robert Merton and Henry McKean as keynote speakers.
Her book, ‘Commodities and Commodity Derivatives’ is the reference in the field. She was a Scientific Expert on Agriculture for the European Commission and is on the Board of the Bloomberg Commodity Index.
She counts among her numerous PhD students Nassim Taleb, author of the Black Swan

Iuliia Shpak:

Quant Strategies Specialist at Sarasin & Partners LLP

Iuliia Shpak: Quant Strategies Specialist at Sarasin & Partners LLP

In her multifaceted role, Iuliia extensively focuses on quant investment solutions for institutional asset owners, in particular SWFs and large pension funds and contributes to internal research and selection of external quant managers.

Iuliia’s research experience covers market anomalies, speculative bubbles, volatility modelling and systematic risk factors in equities and commodity futures.

Iuliia serves as an Adjunct Researcher at the World Pensions Council and Member of Scientific Council at the CBBA-Europe. Iuliia holds MSc in Operational Research and PhD in Finance.

Iuliia frequently delivers guest lectures at the London School of Economics (LSE) and other academic institutions.

Milena Imamovic-Tomasovic:

Head of Product-Aligned Valuation Methodology, Deutsche Bank

Milena Imamovic-Tomasovic: Head of Product-Aligned Valuation Methodology, Deutsche Bank

Milena Imamovic-Tomasovic is a quantitative finance professional with fifteen years of experience in banking. Her current role is Head of Business-Aligned Valuation Methodology within Global Valuation Group team in Deutsche Bank. Prior to that, she was Head of CVA and Funding Methodology within GVG Methodology and 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.

Joanne Chorley:

Quantitative Analyst, Citi

Joanne Chorley: Quantitative Analyst, Citi

Joanne works in Markets Quantitative Analysis and is part of Common Quant Development, specifically the Roots team at Citi. The Roots team works on all aspects of high performance computing in the derivatives world including hardware acceleration as well as algorithm design to leverage the parallelism of modern hardware. Joanne joined Citi and the Roots team after completing a PhD in Physics at Durham University, specializing in high performance computing techniques employed in the field of nuclear fusion energy.

12.30 - 13.30
Lunch
13.30 - 14.10
Valuation Risk Management
  • What is valuation risk
  • Different aspects of valuation risk, valuation risk drivers
  • Valuation risk control and monitoring

Milena Imamovic-Tomasovic:

Head of Product-Aligned Valuation Methodology, Deutsche Bank

Milena Imamovic-Tomasovic: Head of Product-Aligned Valuation Methodology, Deutsche Bank

Milena Imamovic-Tomasovic is a quantitative finance professional with fifteen years of experience in banking. Her current role is Head of Business-Aligned Valuation Methodology within Global Valuation Group team in Deutsche Bank. Prior to that, she was Head of CVA and Funding Methodology within GVG Methodology and 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.

14.10 - 14.50
Neural Networks – it’s application in front office/quantitative finance

Priti Sinha:

Head of SAF Analytics, NatWest Markets

Priti Sinha: Head of SAF Analytics, NatWest Markets

Dr Priti Sinha is a PhD in Pure Mathematics and Theoretical Computer Science. She has over 12 years’ experience as a Fixed Income and Hybrids Quant at NatWest Markets. Over the years, she has developed several models for these divisions and she now heads the SAF Analytics team at NWM. Priti is responsible for core analytics, the curves and algorithms used in pricing, hedging and risk management across all asset classes in NWM.

Automation is her big focus; she and her team are engaged in a range of automation initiatives across the Bank. She is making Quant skills available beyond the traditional trading floor, to other non-trading sections of the bank.

Outside her work Priti enjoys spending time with her 6 year old twins and brainstorming with her husband, who is a founder of an IOT & Tech start-up.

14.50 - 15.30
Deep Learning Volatility

Abstract

We present a consistent neural network based calibration method for a number of volatility models-including the rough volatility family-that performs the calibration task within a few milliseconds for the full implied volatility surface.

The aim of neural networks in this work is an off-line approximation of complex pricing functions, which are difficult to represent or time-consuming to evaluate by other means. We highlight how this perspective opens new horizons for quantitative modelling: The calibration bottleneck posed by a slow pricing of derivative contracts is lifted. This brings several model families (such as rough volatility models) within the scope of applicability in industry practice. As customary for machine learning, the form in which information from available data is extracted and stored is crucial for network performance. With this in mind we discuss how our approach addresses the usual challenges of machine learning solutions in a financial context (availability of training data, interpretability of results for regulators, control over generalisation errors). We present specific architectures for price approximation and calibration and optimize these with respect different objectives regarding accuracy, speed and robustness. We also find that including the intermediate step of learning pricing functions of (classical or rough) models before calibration significantly improves network performance compared to direct calibration to data.

Blanka Horvath:

Honorary Lecturer, Department of Mathematics, Imperial College London

Blanka Horvath: Honorary Lecturer, Department of Mathematics, Imperial College London

Blanka is a Honorary Lecturer in the Department of Mathematics at Imperial College London and a Lecturer at King’s College London. Her research interests are in the area of Stochastic Analysis and Mathematical Finance.

Her interests include 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.

15.30 - 16.00
Afternoon Break and Networking Opportunities
16.00 - 16.30
Hidden Correlations: A Self-Exciting Tale from the FX World

Abstract

The aim of this paper is to investigate the dependence between exchange rates and their volatility from the information synthesised into currency options quotes. To this purpose, we propose an affine stochastic volatility model with self-exciting structure under a time changed pure jump Lévy framework. In particular, we construct a mechanism inducing dependence effects via systematic jumps. The performance analysis shows that this factor construction improves the pricing of FX options in terms of calibration and fit of the implied volatility surface, indicating that this dependence is of moderate nature. Therefore, we have evidence to claim that there exists a mild correlation between exchange rates and their volatility. This is joint work with Alessandro Morico.

Laura Ballotta:

Reader, Financial Mathematics, Cass Business School

Laura Ballotta: Reader, Financial Mathematics, Cass Business School

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).

16.30 - 17.00
A Deep Learning Approach to Exotic Option Pricing under LSVol
  • The market standard for the pricing and risk management of complex derivatives within the Foreign Exchange markets uses a local-stochastic volatility (LSVol) model.
  • This type of model can better capture relevant market dynamics but is computationally very expensive.
  • We use a Deep learning approach to value path-dependent Exotic Options under LSVol, achieving high degree of accuracy (to production standard)
  • We’ll explore this innovative approach, which is a radical departure from the traditional quantitative finance methodology prevalent in banks

Katia Babbar:

AI Wealth Technologies Founder & Visiting Research Fellow, Oxford Mathematical Institute

Katia Babbar: AI Wealth Technologies Founder & Visiting Research Fellow, Oxford Mathematical Institute

17.00 - 18.00
PANEL: Career Progression

Topics:

  • Do you think that being a woman is a significant factor in slowing down career progression in QR Financial Services?
    • If so, could this be avoided and how?
  • 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?
  • Is it still hard to make it to the top positions, if so why and what can do done to change the situation?
  • Discuss female role models in finance and significant achievements
  • Tips from coaches on career progression (eg having your voice heard)
  • Actively managing your career; distribution of opportunity set
  • Gender diversity issues (discuss numbers, policies, how to address it)
  • 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

Katia Babbar:

AI Wealth Technologies Founder & Visiting Research Fellow, Oxford Mathematical Institute

Katia Babbar: AI Wealth Technologies Founder & Visiting Research Fellow, Oxford Mathematical Institute

Natalie Basiratpour:

Director, Octavius Finance

Natalie Basiratpour: Director, Octavius Finance

Priti Sinha:

Head of SAF Analytics, NatWest Markets

Priti Sinha: Head of SAF Analytics, NatWest Markets

Dr Priti Sinha is a PhD in Pure Mathematics and Theoretical Computer Science. She has over 12 years’ experience as a Fixed Income and Hybrids Quant at NatWest Markets. Over the years, she has developed several models for these divisions and she now heads the SAF Analytics team at NWM. Priti is responsible for core analytics, the curves and algorithms used in pricing, hedging and risk management across all asset classes in NWM.

Automation is her big focus; she and her team are engaged in a range of automation initiatives across the Bank. She is making Quant skills available beyond the traditional trading floor, to other non-trading sections of the bank.

Outside her work Priti enjoys spending time with her 6 year old twins and brainstorming with her husband, who is a founder of an IOT & Tech start-up.

Blanka Horvath:

Honorary Lecturer, Department of Mathematics, Imperial College London

Blanka Horvath: Honorary Lecturer, Department of Mathematics, Imperial College London

Blanka is a Honorary Lecturer in the Department of Mathematics at Imperial College London and a Lecturer at King’s College London. Her research interests are in the area of Stochastic Analysis and Mathematical Finance.

Her interests include 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.

Burcu Karabork:

Quantitative Developer, NatWest Markets

Burcu Karabork: Quantitative Developer, NatWest Markets

Ioana Savescu:

Co-head of the Global Credit and Commodities Quant Strategies Groups, Bank of America Merrill Lynch

Ioana Savescu: Co-head of the Global Credit and Commodities Quant, Strategies Groups, Bank of America Merrill Lynch

Ioana Savescu is Co-head of the Global Credit and Commodities Quantitative Strategies Groups as well as heading the Global Banking and Markets Pre-Provision Net Revenue (PPNR) Forecasting team. She is responsible for the model development and implementation in this space and is based in London.

Ioana first joined Merrill Lynch in April 2007 as a Credit Quant on the Credit Derivatives desk and has been with the firm ever since. She became co-head of the Global Credit Quantitative Strategies Group in 2014. She has worked on a variety of topics addressing both front office pricing and risk managing models for credit products as well as regulatory calculations. Since 2016 she is also leading the development effort for the models used in the CCAR process for forecasting revenues within the Global Markets and Banking business (PPNR). In 2018 she became the co-head of the Commodities Quantitative Strategies Group as well, continuing to expand her knowledge and expertise into a new area.

Prior to beginning her career in finance Ioana obtained and MSc in engineering from Ecole Polytechnique and an MSc in Applied Mathematics in Finance from Paris VI University. She then went on to obtain a PhD in Financial Mathematics from Imperial College with a thesis studying counterparty risks on credit derivatives.

  • Discount Structure
  • Early bird discount
    20% until 27th September 2019

  • Special Offer
    When two colleagues attend the 3rd goes free!

  • 70% Academic Discount
    (FULL-TIME Students Only)

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