World Business StrategiesServing the Global Financial Community since 2000

Women in Quantitative Finance Conference (WQF)

08.00 - 08.50
Registration and Morning Welcome Coffee
08.50 - 09.00
Women in Quantitative Finance Chair:

To be confirmed

09.00 - 09.45
Keynote: 'From Changes of Numeraire and Changes of Measure to Bitcoins and Blockchains'

Abstract:

The first part of the talk will review the way the economic assumption of No Arbitrage combined to powerful results established in probability theory in a fairly recent past lead to a number of beautiful results in Quantitative Finance, in particular i) the existence of ‘pricing measures’ under which the prices of primitive securities – in the right numeraire – are martingales; ii) remaining under the physical measure P – the one under which big data are accumulated –, No Arbitrage implies that normality of asset returns can be recovered through a stochastic time change where the clock is driven by the order flow.
The second part of the talk will discuss some key features of cryptocurrencies observed so far, and which methodology can be proposed to analyze this particular asset class stored in a new type of inventory called Blockchain.

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

09.45 - 10.30
Quantum Machine Learning
  • Training strong classifiers with quantum annealing
  • Quantum Boltzmann Machine

Presenter to be confirmed

10.30 - 11.00
Morning Break and Networking Opportunities
11.00 - 12.00
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

Panellists:

Other panellists to be confirmed

Edith Mandel:

Principal, Greenwich Street Advisors, LLC

Edith Mandel: Principal at Greenwich Street Advisors, LLC
Edith Mandel is a seasoned finance professional with 20 years of experience.   She held a number of senior roles both on the sell and buy sides of the Fixed Income business.
Edith has extensive hands-on experience in developing quantitative trading models, and building systematic risk-taking businesses from the ground up.
As a principal at Greenwich Street Advisors, LLC, Edith advises both established participants in the Fixed Income market and those companies considering opportunities for expansion.   As an expert in the Fixed Income market, Edith evaluates the opportunity cost, advises on trading infrastructure build-out, electronic and quantitative trading, risk management, alpha research and algorithmic execution.
In the last two-and-a-half years, Edith Mandel was the head of Fixed Income Mid-Frequency Trading at KCG (formerly GETCO).   While there, she spearheaded a development of a new quantitative and systematic business within the Global Fixed Income group.
Edith started her professional career at Goldman Sachs, where she held a number of positions in the Fixed Income division.   As a Managing Director, Edith ran a team of quantitative strategists responsible for algorithmic trading in US Treasuries and Swaps, for risk management of a broad set of interest rate products, including vanilla and exotic options, and for the development of a toolkit for systematic risk-taking.
Prior to joining KCG, Edith Mandel worked at Citadel as a Managing Director, Head of Fixed Income Quantitative Research. There she was instrumental to a significant revamp and expansion of the Fixed-Income Asset Management business and a development of new profitable systematic trading strategies in liquid rates.
Edith Mandel is a seasoned finance professional with over 18 years of experience.   She held a number of senior roles both on the sell and buy sides of the Fixed Income business.
Edith has extensive hands-on experience in developing quantitative trading models, and building systematic risk-taking businesses from the ground up.
As a principal at Greenwich Street Advisors, LLC, Edith advises both established participants in the Fixed Income market and those companies considering opportunities for expansion.   As an expert in the Fixed Income market, Edith evaluates the opportunity cost, advises on trading infrastructure build-out, electronic and quantitative trading, risk management, alpha research and algorithmic execution.
In the last two-and-a-half years, Edith Mandel was the head of Fixed Income Mid-Frequency Trading at KCG (formerly GETCO).   While there, she spearheaded a development of a new quantitative and systematic business within the Global Fixed Income group.
Edith started her professional career at Goldman Sachs, where she held a number of positions in the Fixed Income division.   As a Managing Director, Edith ran a team of quantitative strategists responsible for algorithmic trading in US Treasuries and Swaps, for risk management of a broad set of interest rate products, including vanilla and exotic options, and for the development of a toolkit for systematic risk-taking.
Prior to joining KCG, Edith Mandel worked at Citadel as a Managing Director, Head of Fixed Income Quantitative Research. There she was instrumental to a significant revamp and expansion of the Fixed-Income Asset Management business and a development of new profitable systematic trading strategies in liquid rates

Peter Carr:

Professor and Dept. Chair of FRE Tandon, New York University

Peter Carr: Professor and Dept. Chair of FRE Tandon, New York University

Dr. Peter Carr is the Chair of the Finance and Risk Engineering Department at NYU Tandon School of Engineering. He has headed various quant groups in the financial industry for the last twenty years. He also presently serves as a trustee for the National Museum of Mathematics and WorldQuant University. Prior to joining the financial industry, Dr. Carr was a finance professor for 8 years at Cornell University, after obtaining his Ph.D. from UCLA in 1989. He has over 85 publications in academic and industry-oriented journals and serves as an associate editor for 8 journals related to mathematical finance. He was selected as Quant of the Year by Risk Magazine in 2003 and Financial Engineer of the Year by IAQF/Sungard in 2010. From 2011 to 2014, Dr. Carr was included in Institutional Investor’s Tech 50, an annual listing of the 50 most influential people in financial technology.

In the 2 years Dr. Carr been FRE dept. chair, applications increased from 1,300 per year to 1,900 per year. The number of FRE Masters students in residence was the highest in any 2-year period. For the incoming 2018 class, current verbal GRE is 169/170 and GPA is 3.82. FRE moved up in Quantnet rankings both years. An online summer course was initiated last summer and an on-campus bootcamp will be initiated this summer. Six electives on machine learning in finance were introduced. The distance learning room will become operational this summer.

Roza Galeeva:

Research Professor at NYU , Tandon School of Engineering

Roza Galeeva: Research Professor at NYU , Tandon School of Engineering, Commodity Derivatives, Risk Management

12.00 - 12.45
Using Artificial Intelligence to measure Sustainable Development Goals

Presenter to be confirmed

12.45 - 13.45
Lunch
13.45 - 14.30
Identification and Forecast of Market Regimes using Machine Learning
  • Applying Hidden Markov Models (HMM) to identify market regimes (bull/bear/range etc)
  • Specification and estimation of HMMs using Unsupervised Learning
  • Forecasting of likelihoods of regimes at different horizons
  • Applications to systematic trading strategies

Presenter to be confirmed

14.30 - 15.15
PANEL: Machine Learning, AI & Quantum Computing in Quantitative Finance 

Topics:

  • What is the current state of utilisation of machine learning in finance?
  • What are the distinct features of machine learning problems in finance compared to other industries?
  • What are the best practices to overcome these difficulties?
  • What’s the evolution of a team using machine learning in terms of day to day operations?
  • What is a typical front office ‘Quant’ skillset going to look like in three to five years time?
  • How do we deal with model risk in machine learning case?
  • How is machine learning expected to be regulated?
  • What applications can you list among its successes?
  • How much value is it adding over and above the “classical” techniques such as linear regression, convex optimisation, etc.?
  • Do you see high-performance computing (HPC) as a major enabler of machine learning?
  • What advances in HPC have caused the most progress?
  • What do you see as the most important machine learning techniques for the future?
  • What are the main pitfalls of using Machine Learning currently in trading strategies?
  • What new insights can Machine Learning offer into the analysis of financial time series?
  • Discuss the potential of Deep Learning in algorithmic trading?
  • Do you think machine learning and HPC will transform finance 5-10 years from now?
  • If so, how do you envisage this transformation?
  • Can you anticipate any pitfalls that we should watch out for.
  • Discuss quantum computing in quant finance:
    • Breakthroughs
    • Applications
    • Future uses

Moderator: To be confirmed

Panellists:

Other panellists to be confirmed

Ioana Boier (to be confirmed)

Quantitative Researcher Lead, Citadel LLC

Ioana Boier: Quantitative Researcher, Citadel LLC

Ioana is the Quantitative Research Lead at Citadel LLC in New York specializing in Interest Rate Options within the Global Fixed Income Fund.

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.

Miquel Noguer Alonso:

Co – Founder and Chief Science Officer, Artificial Intelligence Finance Institute – AIFI

Miquel Noguer Alonso: Co – Founder and Chief Science Officer, Artificial Intelligence Finance Institute – AIFI

Miquel Noguer is a financial markets practitioner with more than 20 years of experience in asset management, he is currently Head of Development at Global AI ( Big Data Artificial Intelligence in Finance company ) and Head on Innovation and Technology at IEF.

He worked for UBS AG (Switzerland) as Executive Director.for the last 10 years. He worked as a Chief Investment Office and CIO for Andbank from 2000 to 2006.

He is professor of Big Data in Finace at ESADE and Adjunct Professor at Columbia University teaching Asset Allocation, Big Data in Finance and Fintech. He received an MBA and a Degree in business administration and economics in ESADE in 1993. In 2010 he earned a PhD in quantitative finance with a Summa Cum Laude distinction (UNED – Madrid Spain).

15.15 - 15.45
Afternoon Break and Networking Opportunities
15.45 - 16.30
Machine Learning for Trade Strategies
  • Finding alpha – value investing
  • Factor investment
  • Reinforcement Learning
  • AI for ESG
  • Sentiment Analysis

Presenter to be confirmed

16.30 - 17.00
Can Machine Learning Predict Realized Variance?
  • Volatility index (VIX) construction and Realized Variance (RV) prediction.
  • Can machine learning improve the prediction of RV and thereby improve the construction of a volatility index?
  • Results
  • Conclusions and future research directions

Peter Carr:

Professor and Dept. Chair of FRE Tandon, New York University

Peter Carr: Professor and Dept. Chair of FRE Tandon, New York University

Dr. Peter Carr is the Chair of the Finance and Risk Engineering Department at NYU Tandon School of Engineering. He has headed various quant groups in the financial industry for the last twenty years. He also presently serves as a trustee for the National Museum of Mathematics and WorldQuant University. Prior to joining the financial industry, Dr. Carr was a finance professor for 8 years at Cornell University, after obtaining his Ph.D. from UCLA in 1989. He has over 85 publications in academic and industry-oriented journals and serves as an associate editor for 8 journals related to mathematical finance. He was selected as Quant of the Year by Risk Magazine in 2003 and Financial Engineer of the Year by IAQF/Sungard in 2010. From 2011 to 2014, Dr. Carr was included in Institutional Investor’s Tech 50, an annual listing of the 50 most influential people in financial technology.

In the 2 years Dr. Carr been FRE dept. chair, applications increased from 1,300 per year to 1,900 per year. The number of FRE Masters students in residence was the highest in any 2-year period. For the incoming 2018 class, current verbal GRE is 169/170 and GPA is 3.82. FRE moved up in Quantnet rankings both years. An online summer course was initiated last summer and an on-campus bootcamp will be initiated this summer. Six electives on machine learning in finance were introduced. The distance learning room will become operational this summer.

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 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
  • 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

Moderator: To be confirmed

Panellists:

Other panellists to be confirmed

Natalie Basiratpour:

Director, Octavius Finance

Natalie Basiratpour: Director, Octavius Finance

Sharon Sputz:

Executive Director of Strategic Programs, Data Science Institute, Columbia University

Sharon Sputz: Executive Director of Strategic Programs, Data Science Institute, Columbia University

Sharon has combined experience in business strategy and technical research.  Prior to joining the Institute, Sharon spent 11 years at BAE Systems identifying and pursuing new business opportunities in leading edge technology. Her expertise is establishing long term customer relationships to grow and develop new business.  Sharon is skilled in orchestrating research aligned to customer needs in order to promote the funding of new business. She began her career at Bell Laboratories managing and coordinating material characterization as well as developing new and innovative tools to control processing and provide profitable laser packages for the optical communications business. Sharon moved on to become the Strategic Marketing Manager at Lucent/Agere with a variety of responsibilities: from leading the technical evaluation of merger and acquisition candidates to defining product planning for the optical networking group and components. She holds multiple patents from both her time at BAE Systems as well as Lucent. Sharon received a Bachelor of Science in Physics from State University of NY at Binghamton and a Masters of Science in Physics from Stevens Institute of Technology.

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