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World Business StrategiesServing the Global Financial Community since 2000

Wednesday 16th June: Day 3 WQF

Deep Hedging under Rough Volatility

EDT: 09.00
BST: 14.00
CEST: 15.00

We investigate the performance of the Deep Hedging framework under training paths beyond the (finite dimensional) Markovian setup. In particular we analyse the hedging performance of the original architecture under rough volatility models with view to existing theoretical results for those. Furthermore, we suggest parsimonious but suitable network architectures capable of capturing the non-Markoviantity of time-series. Secondly, we analyse the hedging behaviour in these models in terms of P&L distributions and draw comparisons to jump diffusion models if the the rebalancing frequency is realistically small.

Blanka Horvath:

Lecturer, King’s College London and Researcher, The Alan Turing Institute

Blanka Horvath: Lecturer, King’s College London and Researcher, The Alan Turing Institute

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.

Reinforcement Learning for Finance Applications

EDT: 10.00
BST: 15.00
CEST: 16.00

Francesca Lazzeri:

Principal Manager, Cloud & AI & Machine Learning, Microsoft

Francesca Lazzeri: Principal Manager, Cloud & AI & Machine Learning, Microsoft

Francesca Lazzeri is a machine learning scientist on the cloud advocacy team at Microsoft. An expert in big data technology innovations and the applications of machine learning-based solutions to real-world problems, she has worked with these issues in a wide range of industries, including energy, oil and gas, retail, aerospace, healthcare, and professional services. Previously, she was a research fellow in business economics at Harvard Business School, where she performed statistical and econometric analysis within the Technology and Operations Management Unit and worked on multiple patent data-driven projects to investigate and measure the impact of external knowledge networks on companies’ competitiveness and innovation. Francesca periodically teaches applied analytics and machine learning classes at universities in USA and Europe. and is a mentor for PhD and postdoc students at the Massachusetts Institute of Technology. She enjoys speaking at academic and industry conferences to share her knowledge and passion for AI, machine learning, and coding. Francesca holds a PhD in innovation management.

Topic and Presenter to be Confirmed

EDT: 11.00
BST: 16.00
CEST: 17.00

Machine Learning Models & Fixed Income Quant Trading

ESDT: 12.00
BST: 17.00
CEST: 18.00

Abstract:

Fixed Income trading is slow to evolve.  We see a lot of innovation in algorithmic execution & TCA, but changes are less dramatic in risk-taking parts of the business.  In this talk I will describe several practical applications of ML to signal-driven trading in Fixed Income.  We will focus on bonds, and work through examples of logistic models used for sizing of positions, non-linear patterns in the data, model stacking & how ML approach can produce forecasts for instruments with limited historical data (i.e new issues).

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

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