Program

Program

Program 2018

Day One - July 10, 2018

 

 

 

08:20

Registration and refreshments

08:50

WELCOME ADDRESS:  Mauro Cesa, Quant Finance Editor, RISK.NET

09:00

OPENING KEYNOTE ADDRESS: Rough volatility: An overview

Jim Gatheral, Presidential Professor of Mathematics, Baruch College, CUNY

09:35

PRESENTATION: How to develop machine learning capabilities, while avoiding pitfalls?

Suresh Baral, Managing Director, PROTIVITI

10:10

GUEST ADDRESS: Quantum artificial intelligence

Vasil Denchev, Chief Quantum Software Architect of Quantum Artificial Intelligence Lab, GOOGLE

10:45

Morning break and opportunity to network

KNOWLEDGE CAFÉ: Grab a coffee and join a table of your choice to share ideas and network with fellow industry professionals.

  • How do you use or plan to use Machine Learning -  Led by: Igor Halperin, Research Professor of Financial Machine Learning,  NYU TANDON SCHOOL OF ENGINEERING
  • The growing potential of quantum computing: Why you should keep an eye on developments in this area - Led by:  Vasil Denchev, Chief Quantum Software Architect of Quantum Artificial Intelligence Lab, GOOGLE

  • "Quantamental" investing: The best of both worlds - Led by: Ken Perry, Former Chief Risk Officer, OCH-ZIFF CAPITAL MANAGEMENT

Portfolio Optimization & Risk Management

Chair’s opening remarks: Christos Koutsoyannis, CEO and Founder, ATLAS RIDGE CAPITAL

11:20

Imperfect foresight: A framework for incorporating various forecast horizons into alpha models 

  • Given a simple analytic model, we show how the framework

    - improves  IR
    - reduces turnover
    - and can be used in a Fama-MacBeth regression
  • Empirical results including a custom method for determining horizon

Jonathan Briggs, Senior Portfolio Manager, Quantitative Equities, Public Market Investments, CANADA PENSION PLAN INVESTMENT BOARD

11.50

Implied returns with leverage constraints and target returns

  • To calculate implied returns assuming optimal allocation is an alternative and robust approach for portfolio optimization
  • Propose a new model to calculate implied returns with leverage constraint
  • The proposed model not only has parametric solution, but also can be used with any risk models

Leon Xin, Head of Risk and Portfolio Construction and Hedge Fund Strategist, JP MORGAN ASSET MANAGEMENT

12.20

Zero covariation portfolio theory that applies methods from machine learning to the portfolio construction

Dilip Madan, Professor of Mathematical Finance, Robert H. Smith School of Business, UNIVERSITY OF MARYLAND 
12.50 Lunch and opportunity to network
1.50

CALL FOR PAPER WINNER: Optimal mean reversion: A probabilistic framework for deriving market entry and exit

Donny Lee, Associate, Quantitative Trader, BNP PARIBAS

2.20

Foster-Hart analytical risk contributions: A New method to construct risk parity portfolios

  • Derive analytical formulae for the risk parity contributions under the generalized Foster-Hart risk measure
  • Application of Foster-Hart to risk-parity portfolios
  • Empirical analysis with other risk measures (e.g. VaR)
Pietro Toscano, Senior Risk Manager, OPPENHEIMERFUNDS
2.50

Quantitative strategies in a low volatility environment

  • Portfolio construction is a critical, and often overlooked, source of alpha
  • Ideas for reducing unintended exposures in your portfolio construction and alpha model building that ensure greater pass-through of alpha into strategy outcome
  • Pitfalls and dangers in the current low-vol environment with many quant players
  • How to build a low volatility strategy that can also keep up in rising markets?
Peg DiOrio, Head of Quantitative Equity, VOYA INVESTMENT MANAGEMENT

Volatility Modeling & Pricing

 

Chair’s opening remarks:  Andrey Itkin, Director, Senior Quant Research Associate, BANK OF AMERICA

 

11:20

Quantum pricing – Application of group representations theory in quantitative finance

  • Symmetry groups and their infinite dimensional representations in quantum mechanics
  • Using  similar techniques  in quantitative finance
  • Producing tractable and parsimonious derivative pricing models  by utilizing  methodologies applied in quantum mechanics and quantum field theory

Greg Pelts, Quant, WELLS FARGO

 

11:50

The Group Quantization methods in finance

  • Theoretical methods to show that the quantum phase invariance, analytically continued to the real line, gives rise to the Black Scholes theory
  • This continuation is the limit in which the quantum particle acquires an imaginary mass inversely proportional to the Black-Scholes variance, and phase invariance is now re-interpreted as invariance under the choice of numeraire
  •  The Group Quantization formalism allows us to construct the operators and constrained functional space that fully describe the theory

Santiago Garcia,  Director, Quantitative Analyst, WELLS FARGO

 
12.20

An expanded local variance gamma model and ultrafast calibration of volatility smile

  • An expansion of the LVG model that allows for a non-zero drift in the underlying process
  • Calibration of the model to the market smiles doesn’t require solving any optimization problem
  • In contrast, it can be done term-by-term by solving a system of non-linear algebraic equations for each maturity, and thus is ultrafast
Andrey Itkin, Director, Senior Quant Research Associate, BANK OF AMERICA
 
12.50 Lunch and opportunity to network  
1.50

Deep learning and computational graph techniques for generic derivatives pricing

Bernhard Hientzsch, Director, Head of Model, Library, and Tools Development for Corporate Model Risk, WELLS FARGO  

 
2.20

Probabilistic interpretation of an arbitrage - Free implied volatility smile

Peter Carr, Chair of the Finance and Risk Engineering Department, NYU TANDON SCHOOL OF ENGINEERING

 
2.50

SOFR so far

Fabio Mercurio, Head of Quant Analytics, BLOOMBERG

 

3.20

Afternoon break and opportunity to network

*BOOK SIGNING: Join Marcos Lopez de Prado at the exhibition area and get a copy of his book “Advances in Financial Machine Learning”!*

 

3.50

GUEST ADDRESS: Intraday price formation: Insights from deep learning

Rama Cont, Mathematical Institute, UNIVERSITY OF OXFORD
 

4:20

SPOTLIGHT ON QUANTUM COMPUTING IN FINANCE

I. PROVIDER’S VIEW: The promise of quantum computing applications in finance

Vern Brownell, Chief Executive Officer, D-WAVE SYSTEMS
 

II. PRACTITIONER’S VIEW: The reality of quantum computing applications in finance

Marcos Lopez de Prado, Chief Executive Officer, TRUE POSITIVE TECHNOLOGIES

5.20

Chairman’s closing remarks: Mauro Cesa, Quant Finance Editor, RISK.NET

5.30

Cocktail reception. End of day one

 
 

Day Two - July 11, 2018

08:30

Registration and refreshments

08:50

WELCOME ADDRESS:  Mauro Cesa, Quant Finance Editor, RISK.NET

09:00

OPENING KEYNOTE ADDRESS ON BEHAVIOURAL FINANCE: Equity valuation, dopamine pathways, and limits to nudges

Hersh Shefrin, Mario L. Belotti Professor of Finance, Leavey School of Business, SANTA CLARA UNIVERSITY 

09.35

PANEL DISCUSSION: New research fields in modern quantitative finance: What are they and what skills a new generation of quants need have to navigate them?

  • What new market developments have been driving quant research?
  • Are we in a machine learning era? Or a temporary hype?
  • What are the opportunities for quants in the buy-side sector?
  • What skill set employers are looking for: Are we moving form math and physics to computer science?


Moderator: Amit Kaushik, Head of Quantitative Research and Portfolio Management, BLOCKSEED INVESTMENTS
Ronnie Shah, Head of US Quantitative Research, DEUTSCHE BANK
Arik Ben Dor, Head of Quantitative Equity Research, BARCLAYS
Vasily Strela, Global Head of FICC Quantitative Strategies, RBC CAPITAL MARKETS

10.20

KEYNOTE ADDRESS: Hannibal ad Portas: Impact of Fintech on incumbent financial institutions

Alexander Lipton, Founder, Chief Executive Officer, STRONGHOLD LABS

10.55

Morning break and opportunity to network

KNOWLEDGE CAFÉ: Grab a coffee and join a table of your choice to share ideas and network with fellow industry professionals.

  • The benefits of socially responsible investing: An active manager’s perspective Led by: Indrani De, Managing Director, Macro and Country Risk, TIAA

  • Blockchain and cryptocurrencies: What’s in it for quants? -  Led by: Amit Kaushik, Head of Quantitative Research and Portfolio Management, BLOCKSEED INVESTMENTS

  • Low-volatility portfolio construction methods: Why today’s low-volatility environment is different and what strategies to consider? - Led by: Peg DiOrio, Head of Quantitative Equity, VOYA INVESTMENT MANAGEMENT

Quant Investing, Trading & Market Making

Chair’s opening remarks: Christos Koutsoyannis, CEO and Founder, ATLAS RIDGE CAPITAL

11.25

A quantitative framework for macroeconomic and multi-asset risk assessment

  • Drivers of different asset classes: macroeconomic and financial markets analysis
  • Asset class linkages due to common macro drivers
  • Cross-country and global linkages.
  • Feedback loops: Simultaneous equation system
  • Quantitative model building: Balancing structural market changes with sample period selection
  • Examples with some key asset classes

Indrani De, Managing Director, Macro and Country Risk, TIAA

11.55

A quantamental approach to risk management

  • Integrating data, machine learning, and fundamental insights to holistically manage risk
  • Evolving beyond rules-based systems into the world of deep learning
  • Finding patterns in data to aid risk management
  • An interesting use case: Automatically relating relevant and impactful news to one's Portfolio, reflecting measures of risk

Gurraj Singh Sangha, Quantamental Global Macro Portfolio Manager, STATE STREET

  *5 minute intermission to change rooms*
 
12.30

SPECIAL ADDRESS: World Cup draw: Quantifying (un)fairness and (im)balance

Julien Guyon, Senior Quant, BLOOMBERG, Adjunct Professor, COLUMBIA UNIVERSITY, Courant Institute of Mathematical Sciences, NYU

1.00 Lunch and opportunity to network
2.00

Sourcing ESG commitment using natural language processing

Mauricio Bustos, Data Architect, Investment Platform Technology, AXA INVESTMENT MANAGERS – ROSENBERG EQUITIES

2.30

Model risk management for machine learning and trading strategies

  • Model Risk Management: What is it?
  • Challenges of using machine learning to build trading strategies
  • Strategy evaluation and ongoing monitoring of ML trading strategies

Ben Steiner, Head of Quantitative Strategies, CIT GROUP

3.00

Recent advances in using neural nets for intraday predictions in equities markets

Michael Sotiropoulos, Managing Director, Global Markets, DEUTSCHE BANK

Risk.net Quants of the Year 2018 & Model Risk

Chair’s opening remarks: Yadong Li, Managing Director, Head of Portfolio Central, Quantitative Analytics, BARCLAYS CAPITAL
 

11.25

NEW RESEARCH FROM 2018 RISK.NET QUANTS OF THE YEAR
 

I. Credit and funding risk for CCP trading

Andrew Dickinson, Director, BANK OF AMERICA MERRILL LYNCH (co-authored with Leif Andersen, Global Co-Head of The Quantitative Strategies Group, BANK OF AMERICA MERRILL LYNCH)

II.The impact of the margin requirements for uncleared derivatives on regulatory capital

Michael Pykhtin,  Manager, Quantitative Risk,  U.S. FEDERAL RESERVE BOARD

  *5 minute intermission to change rooms*
12.30

SPECIAL ADDRESS: World Cup draw: quantifying (un)fairness and (im)balance

Julien Guyon, Senior Quant, BLOOMBERG, Adjunct Professor, COLUMBIA UNIVERSITY, Courant Institute of Mathematical Sciences, NYU

1.00 Lunch and opportunity to network
2.00

Model interconnectedness

  • CCAR models network
  • Interaction and dependencies among models

Julia Litvinova, Head of Model Validation and Analytics, Managing Director, STATE STREET

2.30

CALL FOR PAPER WINNER: Methodologies for forward initial margin modelling

  • Definition of forward initial margin as collateral
  • Advantages of modelling forward initial margin
  • Modelling approaches and examples.
  • Benchmarking and backtesting ideas for the different models

Lucia Cipolina Kun, Vice President, Counterparty Risk, BANK OF AMERICA MERRILL LYNCH

3.00

Effective approximations of zero coupon bond/survival probabilities and Arrow Debreu Prices in short rate models

Luca Capriotti, Global Head Quantitative Strategies Credit and Financing, CREDIT SUISSE 

3.30

Afternoon break and networking

3.50

AFTERNOON KEYNOTE ADDRESS:  Machine learning: A practitioner view between myth and reality

Stefano Pasquali, Managing Director, Head of Liquidity Research, BLACKROCK

4.20

THE BIG DEBATE:

This house believes machine learning and artificial intelligence offer revolutionary set of tools and will fundamentally change investing strategies

Introduction and audience vote

Opening remarks

Referee's round-robin debate

Summing up and rebuttal

Final vote

For the motion:

George Lentzas,  Manager & Chief Data Scientist and Adjunct Associate Professor, SPRINGFIELD CAPITAL MANAGEMENT, COLUMBIA BUSINESS SCHOOL & NEW YORK UNIVERSITY
Dan Furstenberg, Managing Director, Head of Data Strategy, JEFFERIES
Gurraj Singh Sangha, Quantamental Global Macro Portfolio Manager, STATE STREET

Referee: Luca Capriotti, Global Head Quantitative Strategies Credit and Financing, CREDIT SUISSE

Against the motion:

Ben Steiner, Head of Quantitative Strategies, CIT GROUP
Ken Perry, Former Chief Risk Officer, OCH-ZIFF CAPITAL MANAGEMENT
Stefano Pasquali, Managing Director, Head of Liquidity Research, BLACKROCK

5.10

Chairman’s closing remarks: Mauro Cesa, Quant Finance Editor, RISK.NET

5.20

End of the conference.