World Business StrategiesServing the Global Financial Community since 2000

Friday 27th March 2020

08.30 - 09.00
Morning Welcome Coffee
09.00 - 09.45
Opening Talk: Both Streams
Challenges faced when dealing with alternative data: an efficient time series and data proxy analysis
  • Machine Learning on time series, global approach for market data and numerical alternative data
  • Innovation in risk management: An effective approach to enterprise data quality management
  • How to use data to build effective models?
  • Exploring survivorship bias, non-stationarity, and noise to signal ratio and fixes

Andrés Berenguer Alonso:

Market Risk Director, Derivative Valuations Area, Santander

Andrés Berenguer Alonso: Market Risk Director, Derivative Valuations Area, Santander

Andrés Berenguer is currently team director within the derivative valuations area of the Market Risk department in Banco Santander. Since 2009 he has been working on derivative valuations including besides other things, advising on the pricing models of exotic trades, XVA calculation or interest rate curves modelling (basis spreads, collateral, OIS discounting,…). Before working in banking, his experience was in Space and Communications Engineering. He hold a M.Eng. (Laurea) in Telecommunications Engineering from the Miguel Hernández University of Elche, a MBA from the University of Valencia, a M.Sc.  in Technologies, Systems and Communications Networks Engineering from the Polytechnic University of Valencia and he is currently working on his PhD in Telecommunications Engineering from the Miguel Hernández University of Elche.

09.45 - 10.30
Opening Talk: Both Streams
Topic to be confirmed

Presenter to be confirmed

10.30 - 11.00
Morning Break and Networking Opportunities
Stream Chair:

To be confirmed

11.00 - 11.45
Stream One: Reinforcement Learning
“Reinforcement Learning for xVA hedging”

Ivan Zhdankin:

Associate, Quantitative Analyst, JPMorgan Chase & Co

Ivan Zhdankin: Associate, Quantitative Analyst, JPMorgan Chase & Co

Ivan Zhdankin is a quantitative researcher with experience in diverse areas of quantitative finance, including risk modelling, XVA, and electronic trading across asset classes, including commodity futures and G10 and emerging market currencies. Ivan was consulting various banks in quantitative modeling and has recently joined JP Morgan as a quantitative analyst. He has become one of the first researchers to generate convincing results in electronic alpha with neural nets. He has a solid mathematical background from New Economic School and Moscow State University, where he studied under the celebrated Albert Shiryaev, one of the developers of modern probability theory.

11.45 - 12.30
Stream One: Reinforcement Learning
Topic to be confirmed

Presenter to be confirmed

12.30 - 13.30
Lunch
13.30 - 14.15
Stream One: Reinforcement Learning
Deep Execution – Reinforcement Learning and Generative Models in Algo Trading

Presenter to be confirmed

14.15 - 15.00
Stream One: Reinforcement Learning
Breakthroughs in Reinforcement Learning on Quantitative Trading

Daniel Rosengarten:

Head of ALM Quantitative Development, Barclays Investment Bank

Daniel Rosengarten: Head of ALM Quantitative Development, Barclays Investment Bank

Daniel Rosengarten is the Head of ALM Quantitative Development at Barclays Investment Bank. Daniel’s previous career history includes time at Morgan Stanley as an ED – Global Quantitative and Structured Solutions Technology, and Citigroup as Global Structured Credit Derivatives IT.

Daniel holds an MBA gained from the University of Arizona, as well as an MIM from Thunderbird School of Global Management.

15.00 - 15.15
Afternoon Break and Networking Opportunities
15.15 - 16.00
Closing Talk: Both Streams
AI Risks in Finance – Is it too Early to Be Concerned?

Alexander Denev:

Head of AI, Financial Services Advisory, Deloitte

Alexander Denev: Head of AI, Financial Services Advisory, Deloitte

Alexander has more than 15 years of experience in finance, financial modelling and machine learning and he is currently Head of AI – Financial Services Advisory in Deloitte. Prior to joining Deloitte, he led the Quantitative Research & Advanced Analytics at IHS Markit where he created and maintained a center of excellence.

He has written several papers and two books on topics ranging from stress testing and scenario analysis to asset allocation. He has provided thought leadership engagements for conferences, journals and global forums. He also worked as a senior advisor to Risk Dynamics, an arm of McKinsey & Company. Previously he was Director of Risk Models at the Royal Bank of Scotland, where his responsibilities included development of the stress testing methodologies and credit models, and a Fixed Income Structurer for a front office desk. He has also held roles at the European Investment Bank and the European Investment Fund and has participated in the engineering of both the European Financial Stability Facility and the European Stability Mechanism.

Alexander Denev attained his Master of Science degree in Physics with a focus on Artificial Intelligence from the University of Rome, Italy, and he holds a degree in Mathematical Finance from the University of Oxford, UK, where he continues as a visiting lecturer.

Friday 27th March 2020

08.30 - 09.00
Morning Welcome Coffee
09.00 - 09.45
Opening Talk: Both Streams
Challenges faced when dealing with alternative data: an efficient time series and data proxy analysis
  • Machine Learning on time series, global approach for market data and numerical alternative data
  • Innovation in risk management: An effective approach to enterprise data quality management
  • How to use data to build effective models?
  • Exploring survivorship bias, non-stationarity, and noise to signal ratio and fixes

Andrés Berenguer Alonso:

Market Risk Director, Derivative Valuations Area, Santander

Andrés Berenguer Alonso: Market Risk Director, Derivative Valuations Area, Santander

Andrés Berenguer is currently team director within the derivative valuations area of the Market Risk department in Banco Santander. Since 2009 he has been working on derivative valuations including besides other things, advising on the pricing models of exotic trades, XVA calculation or interest rate curves modelling (basis spreads, collateral, OIS discounting,…). Before working in banking, his experience was in Space and Communications Engineering. He hold a M.Eng. (Laurea) in Telecommunications Engineering from the Miguel Hernández University of Elche, a MBA from the University of Valencia, a M.Sc.  in Technologies, Systems and Communications Networks Engineering from the Polytechnic University of Valencia and he is currently working on his PhD in Telecommunications Engineering from the Miguel Hernández University of Elche.

09.45 - 10.30
Opening Talk: Both Streams
Topic to be confirmed

Presenter to be confirmed

10.30 - 11.00
Morning Break and Networking Opportunities
Stream Chair:

Saeed Amen

Founder: Cuemacro

Saeed Amen: Founder: Cuemacro

Saeed has a decade of experience creating and successfully running systematic trading models at Lehman Brothers and Nomura. He is the founder of Cuemacro, Cuemacro is a company focused on understanding macro markets from a quantitative perspective. He is the author of ‘Trading Thalesians – What the ancient world can teach us about trading today’ (Palgrave Macmillan), and graduated with a first class honours master’s degree from Imperial College in Mathematics& Computer Science.

11.00 - 11.45
Stream Two: Alternative Data
The Book of Alternative Data

In this talk, we give a sneak peek of The Book of Alternative Data, which is to be published in early 2020.

We briefly discuss some of the challenges when using alternative such as structuring it and quantifying its value, as well as the risks involved.

We talk about some of the risks associated with alternative data and how to mitigate them

We’ll go through a few of the use cases from book.

These include satellite imagery to model retailers earnings per share and news data to understand FX volatility around central bank meetings.

Saeed Amen

Founder: Cuemacro

Saeed Amen: Founder: Cuemacro

Saeed has a decade of experience creating and successfully running systematic trading models at Lehman Brothers and Nomura. He is the founder of Cuemacro, Cuemacro is a company focused on understanding macro markets from a quantitative perspective. He is the author of ‘Trading Thalesians – What the ancient world can teach us about trading today’ (Palgrave Macmillan), and graduated with a first class honours master’s degree from Imperial College in Mathematics& Computer Science.

11.45 - 12.30
Stream Two: Alternative Data
Topic to be confirmed

Arun Verma:

Quantitative Research Solutions, Bloomberg, LP

Arun Verma: Quantitative Research Solutions, Bloomberg, LP

Dr. Arun Verma joined the Bloomberg Quantitative Research group in 2003. Prior to that, he earned his Ph.D from Cornell University in the areas of computer science & applied mathematics. At Bloomberg, Mr. Verma’s work initially focused on Stochastic Volatility Models for Derivatives & Exotics pricing and hedging. More recently, he has enjoyed working at the intersection of diverse areas such as data science (for structured & unstructured data), innovative quantitative & machine learning methods and finally interactive visualizations to help reveal embedded signals in financial data.

12.30 - 13.30
Lunch
13.30 - 14.15
Stream Two: Alternative Data
Modelling with alternative data: How to avoid propagation of uncertainty from the worst data to the best

Presenter to be confirmed

14.15 - 15.00
Stream Two: Alternative Data
Applying Unsupervised Learning to Trade Data

Presenter to be confirmed

15.00 - 15.15
Afternoon Break and Networking Opportunities
15.15 - 16.00
Closing Talk: Both Streams
AI Risks in Finance – Is it too Early to Be Concerned?

Alexander Denev:

Head of AI, Financial Services Advisory, Deloitte

Alexander Denev: Head of AI, Financial Services Advisory, Deloitte

Alexander has more than 15 years of experience in finance, financial modelling and machine learning and he is currently Head of AI – Financial Services Advisory in Deloitte. Prior to joining Deloitte, he led the Quantitative Research & Advanced Analytics at IHS Markit where he created and maintained a center of excellence.

He has written several papers and two books on topics ranging from stress testing and scenario analysis to asset allocation. He has provided thought leadership engagements for conferences, journals and global forums. He also worked as a senior advisor to Risk Dynamics, an arm of McKinsey & Company. Previously he was Director of Risk Models at the Royal Bank of Scotland, where his responsibilities included development of the stress testing methodologies and credit models, and a Fixed Income Structurer for a front office desk. He has also held roles at the European Investment Bank and the European Investment Fund and has participated in the engineering of both the European Financial Stability Facility and the European Stability Mechanism.

Alexander Denev attained his Master of Science degree in Physics with a focus on Artificial Intelligence from the University of Rome, Italy, and he holds a degree in Mathematical Finance from the University of Oxford, UK, where he continues as a visiting lecturer.

  • Discount Structure
  • Super early bird discount
    25% until 7th February 2020

  • Early bird discount
    15% until 6th March 2020

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

  • Conference + Workshop
    £300 Discount

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

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