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.
Tony Guida: Executive Director – Senior Quant Research, RAM Active Investments
Tony Guida is a Quantitative Portfolio Manager and researcher. Tony’s work is focused primarily on extracting market inefficiencies from different sources from traditional fundamentals, market signals, alternative data, and machine learning. His expertise is in mid to low frequency in equities.
Tony started his career at Unigestion in 2006 where he joined the quantitative equity low volatility team to work as a research analyst. He evolved into a member of the research and investment committee for Minimum Variance Strategies, where he led the factor investing research group for institutional clients. In 2015, he moved to Edhec Risk Scientific Beta as a Senior Consultant for Risk allocation and factor strategies before going to a major UK pension fund in 2016 to build the in-house systematic equity, co-managing 6 billion GBP as a senior quantitative portfolio manager. He joined RAM-Active Investments in January 2019.
Tony holds a Bachelor and Master degrees in Econometry and Finance from the University of Savoy France.
Tony is editor-in-chief for the Journal of Machine Learning in Finance and he is chair of the EMEA machineByte Think Tank. Tony co-wrote and edited the book “Big Data and Machine Learning in Quantitative Investment” Wiley 2018 and is an advisory board member for the Financial Data Professional Institute and a lecturer for Machine Learning at the CQF Institute.
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.
MD, Head of Quantitative Analytics and Quantitative Development, NatWest Markets
Vladimir Piterbarg: MD, Head of Quantitative Analytics and Quantitative Development at NatWest Markets
Managing Director, Head of Credit Derivatives, CITI
Youssef Elouerkhaoui, Managing Director, Head of Credit Derivatives, CITI
Youssed Elouerkhaoui is the global Head of Credit Quantitive Analysis at Citi. His group supports all aspects of modelling and product development across desks, thais includes: Flow Credit Trading, Correlation Trading, CDOs, Exotics and Emering Markets.
He also supports CVA, Funding and Regulatory Capital for Credit Markets. Prior to this, he was a Director in the Fixed Income Derivatives Quantitative Research Group at UBS, where he was in charge of developing and implementing models for the Structured Credit Desk. Before joining UBS, Youssef was a Quantitative Research Analyst at Credit Lyonnais supporting the Interest Rates Exotics business. He has also worked as a Senior Consultant in the Risk Analytics and Research Group at Ernst & Young. He is a graduate of Ecole Centrale Paris and he holds a PhD in Mathematics from Paris-Dauphine University.
David Jessop: Global Head of Quantitative Research, UBS Investment Bank
Until recently David Jessop was the Global Head of Equities Quantitative Research at UBS. His areas of research include portfolio analysis and construction, style analysis and risk modelling. He also helps clients understand, use and implement the quantitative tools available from UBS. David joined UBS in 2002. Prior to this, he spent seven years at Citigroup as Head of Global Quantitative Marketing. Before moving to the sell side he spent six years at Morgan Grenfell Asset Management, where he managed index funds, asset allocation funds and also an option overwriting fund.
David graduated from Trinity College, Cambridge with an MA in Mathematics.
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.
Partner, Head of Quant, Sarasin & Partners
Andrea Nardon: Partner, Head of Quant, Sarasin & Partners
Andrea has just under 20 years of experience as a Quantitative Analyst, and joined Sarasin & Partners in 2006 to manage and develop the systematic franchise. He is passionate about quantitative research and is currently leading a variety of projects related to factor investing, artificial intelligence and market structures.
Prior to joining Sarasin & Partners, Andrea worked as a portfolio manager for Deka Investment in Frankfurt, and before that as a quantitative analyst for Commerzbank. He holds a degree in Economics from the University of Venice, and upon graduation spent a year in the Department of Mathematics to study the application of neural networks and fuzzy logic to equity time series. Andrea codes in multiple languages and uses MATLAB extensively.
Vice President, Morgan Stanley
Harsh Prasad: Vice President, Morgan Stanley
Harsh started his career as a programmer working on various search and pattern recognition algorithms including AI techniques, across radio astrophysics, bioinformatics and speech recognition. He then transitioned to the financial risk domain and for the last decade has worked in many regulatory jurisdictions with banks and finance companies as well as consulting firms focussed on quant modelling. In this period he has applied Machine Learning techniques to behavioural modelling for ALM, mortgage risk modelling, derivatives pricing, time series outlier detection and risk data management. He has been a guest faculty with B schools and is currently authoring a book titled ‘Machine Learning for Finance’.
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).
Trading Strategist, Bank of America Merrill Lynch
Georgios Papaioannou: Trading Strategist, Bank of America Merrill Lynch
George Papaioannou, is a VP Trading Strategist within the Scientific Implementation Group of Bank of America Merrill Lynch. A Global quantitative team employing systematic, quantitative and scientifically informed methodologies around execution, portfolio management, and risk management, with emphasis on development of client solutions. George joined BAML in May 2018, following 12 years in energy major Shell, where he worked on a variety of functions. His latest role was in a team of computational science specialists, advising on machine learning, data, cloud, and high performance computing projects. He has previously worked in production operations, oil and gas forecasting, production optimization, reservoir management, development and project execution, for offshore fields in Brunei. The first 5 years of his industry career he worked in R&D as a scientific software developer focusing on scalable solvers and high performance computing. George holds a PhD in Computational Fluid Mechanics from the Massachusetts Institute of Technology, where he also completed two MSc degrees and worked as a post-doctoral associate for a year. He has authored academic articles and acted as referee for several scientific journals.
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.
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.
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.
Quantitative Analyst at ABN AMRO CLEARING Bank
Thiyagu Dhandapani: Quantitative Analyst at ABN AMRO CLEARING Bank
I am a Senior Quantitative Analyst at ABN AMRO CLEARING Bank, and have been developing financial risk models since 2013. ABN AMRO Clearing Bank is recognised as a leading provider for integrated solutions in the domain of execution, clearing, custody, financing and risk management across asset classes, on a wide range of markets globally. Part of ABN AMRO Group, ABN AMRO Clearing has 11 offices globally employing more than 800 staff. ABN AMRO Clearing services clients on 160+ exchanges, MTFs, dark pools and FX liquidity centres and consistently ranks as a top 3 clearer in most time zones. I am currently employing machine learning to do volatility prediction, liquidity forecast and anomaly detection in input data.
I have done my Bachelor’s in Electronics and Communication Engineering and Master’s in Quantitative Finance at Duisenberg school of finance / Vrije Universiteit.
Founder & CEO, MoCaX Intelligence
Ignacio Ruiz: Founder & CEO, MoCaX Intelligence
Ignacio Ruiz has been the head strategist for Counterparty Credit Risk, exposure measurement, for Credit Suisse, as well as the Head of Risk Methodology, equities, for BNP Paribas. In 2010, Ignacio set up iRuiz Consulting as an independent advisory business in this field. In 2014, Ignacio founded iRuiz Technologies to develop and commercialise MoCaX Intelligence.
He holds a PhD in nano-physics from Cambridge University.
Partner, Quaternion Risk Management
Jörg Kienitz: Partner, Quaternion Risk Management
Previously: Director FSI Assurance Deloitte GmbH and Co-Head of Quant Unit, Head of Quantitative Analytics, Dt. Postbank AG, Senior System Architect, Postbank Systems AG Financial Consultant, Reuters; Academic: Adj. Assoc. Prof. UCT, PD University of Wuppertal, PhD Math., Diploma Math. Books (Wiley): (A) Monte Carlo Frameworks in C++ (B) Financial Modelling – Theory, Implementation and Practice with Matlab Code, (Palgrave McMillan) (C) Interest Rate Derivatives Explained – Part I
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.
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.
Senior Consultant, Quaternion Risk Management
Nikolai Nowaczyk: Senior Consultant, Quaternion Risk Management