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Conference Program - July 11 & 12, 2017

Conference Day 1, July 11 2017

08.00

Registration and breakfast

08.50

RISK welcome address:

Mauro Cesa, Quant Finance Editor, RISK.NET

09.00

OPENING KEYNOTE ADDRESS: Lessons from the Mortician: Volatility modulation

Santhanam Nagarajan, Portfolio Oversight Manager, TUDOR INVESTMENT CORPORATION (Risk.net 2016 Buy-side quants of the year)

09.30

PANEL DISCUSSION: New trends in quant finance

  • What new market developments have been driving quant research?
  • What are the most exciting areas to explore?
  • How can they be applied in financial markets?
  • Overrated and underrated developments and why
  • Game changing trends in capital markets (Shadow banking, peer to peer lending, direct debt issuance, etc.) - What is the quants' role in the changing market structure?
  • Have current political developments resulted in any interesting research in the industry?

Moderator: Isaac Lieberman, Founder and Chief Executive Officer, ASTON CAPITAL MANAGEMENT
Ashish Dev,
Principal Economist, FEDERAL RESERVE BOARD
Miquel Noguer Alonso, Executive Director, UBS & Adjunct Assistant Professor, COLUMBIA UNIVERSITY
Dilip Madan, ‎Professor at Robert H. Smith School of Business, UNIVERSITY OF MARYLAND

10.10

KEYNOTE ADDRESS: Vol, Skew, and Smile Trading

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

10.40

Morning break

STREAM ONE: Bank Risk Management

11:10

Chair's opening remarks

11:20

Submodular risk allocation

  • Changes in the over-the-counter derivatives markets leave dealers some flexibility in whether to trade bilaterally or through central counterparties (CCP) and which CCP to choose
  • Analyzing the problem of optimal allocation of trades to portfolios to minimize risk-based margin and capital requirements
  • Deriving conditions under which standard deviation and other risk measures are submodular functions of sets of trades
  • Comparing systemwide optimality with individually optimal allocations

Samim Ghamami, Senior Economist, U.S. DEPARTMENT OF THE TREASURY

11.50

CALL FOR PAPER WINNER: How to improve hedging without increasing costs. Delta hedging of options

Alexander Skabelin, Vice President. Volatility Strategies, GOLDMAN SACHS

12.20

Optimal management of quant and technology teams as a single organization in an investment bank

  • The traditional organizational split between Technology and Quants
  • What we've learned by placing a Quant Team within Technology at TDS
  • Can a Quant team operate successfully as a part of an IT Department?

Vladimir Sankovich, Managing Director, Head of Quantitative Modeling and Analytics, TD SECURITIES
Mikhail Dron, Managing Director, Balance Sheet Management Technology, TD SECURITIES

12.50

Lunch and opportunity to network

1.50

Behavioral modelling in anti-money laundering transaction monitoring

Gordon Liu, Head of Global Risk Analytics, HSBC NORTH AMERICA

2.20

A model of repo haircuts

  • The model incorporates asset risk, borrower credit risk, wrong way risk, and market liquidity risk
  • Double exponential jump-diffusion processes are used to model single asset or portfolio price dynamics
  • Borrower credit is captured by a log-Ornstein-Uhlenbeck default intensity model
  • Economic capital (EC) defined either as unexpected loss from CVaR or expected shortfall. EC forms the basis for repo KVA
  • Maximum likelihood estimation of the jump-diffusion model are applied to compute haircuts of SPX500 index, US corporate bond and CMBS indices

Wujiang Lou, Adjunct Professor, The Courant Institute of Mathematical Sciences, NEW YORK UNIVERSITY & Director, Global Fixed-Income Trading, HSBC

2.50

Predicting bank closures

  • Bank closures vs corporate defaults - similarities and differences
  • FDIC data
  • Predicting bank closures with classifiers 
  • Predictions with recurrent neural networks and reinforcement learning

Igor Halperin, Executive Director of Model Risk and Development, JP MORGAN

STREAM TWO : Machine Learning & Trading

11.10

Chair's opening remarks

11.20

Advanced machine learning models in finance: Opportunities and challenges

Miquel Noguer Alonso, Executive Director, UBS & Adjunct Assistant Professor, COLUMBIA UNIVERSITY

11.50

Boosting the value of alternative datasets via machine learning

  • John Henry and the modern day analyst
  • Why deep learning is like an analyst in a box
  • Leveraging all your data using bagging, boosting and stacking

Elliot Noma, Managing Director, GARRETT ASSET MANAGEMENT

12.20

Big data in financial markets: Opportunities and challenges

  • Financial modeling and big data
  • Some history of credit models
  • Expert systems
  • Big data in credit modeling
  • Expert systems and sentiment models
  • Opportunities, challenges and critiques

Terry Benzschawel, Managing Director, Credit Quantitative Analysis, CITI

12.50

Lunch and opportunity to network

1.50

Application of machine learning to alpha management in Central Risk Book

Michael Sotiropoulos, Managing Director, Global Markets, DEUTSCHE BANK

2.20

Real-time risk in the context of big data

  • Facts & myths about Flash Crashes, and information dissemination
  • Strategies for managing real-time risk
  • Case studies: Commodities, rates, ETFs

Irene Aldridge, Managing Director, ABLE ALPHA TRADING

2.50

Trading illiquid goods: Market making as a sequence of sealed-bid auctions, with analytic results

Peter Cotton, Executive Director, JP MORGAN

3.20

Afternoon break

3.50

AFTERNOON KEYNOTE ADDRESS: Liquidity risk management framework and machine learning application

  • Market liquidity
  • Redemption forecast
  • Portfolio liquidity optimization

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

4.20

KEYNOTE ADDRESS: Conic option pricing

Dilip Madan, Professor at Robert H. Smith School of Business, UNIVERSITY OF MARYLAND

4.50

CLOSING ADDRESS: Eliminating time lag between reciprocal trade and margin payments through a minor change in CSA

  • With today's heightened awareness of the counterparty credit risk and margin requirements, the absurdity and the risk of sending a large sum of money to a counterparty only to receive the equivalent amount of collateral back a few days later - that is, if they do not default in the meantime - is finally coming into focus
  • We will discuss the CSA provisions that give rise to this risk, its surprisingly large magnitude, and how it can be mitigated by making a minor change in how portfolio is valued for the purposes of margin under CSA

Alexander Sokol, CEO and Head of Quant Research, COMPATIBL

5.20

Chairman's closing remarks:

Mauro Cesa, Quant Finance Editor, RISK.NET

5.30

Cocktail reception. End of day one

 

Conference Day 2, July 12 2017

08.00

Registration and breakfast

08.50

RISK welcome address:

Mauro Cesa, Quant Finance Editor, RISK.NET

09.00

REGULATORY KEYNOTE ADDRESS: The revised Basel CVA framework

Michael Pykhtin, Manager, Quantitative Risk, FEDERAL RESERVE BOARD

09.30

PANEL DISCUSSION: The melting pot of model risk management

  • Regulatory changes that are driving model methodologies in banking and trading books
  • How can trading book quants help banking book quants solve those problems and vice versa? 
  • What has the industry achieved across the model lifecycle?
  • What do the next five years in model risk management hold?

Moderator: Mauro Cesa, Quant Finance Editor, RISK.NET
Bernhard Hientzsch,
Director, Head of Model, Library, and Tools Development for Corporate Model Risk, WELLS FARGO
Julia Litvinova, Head of Model Validation and Analytics, Managing Director, STATE STREET
Nikolai Kukharkin, Senior Risk Manager, formerly Global Head of Model Risk Management & Control, UBS

 10.10

PRESENTATION: Applying machine learning to time series analysis

Kharen Musaelian, Founder and Chief Investment Officer, DUALITY ADVISORS

10.40

Morning break

STREAM ONE: Portfolio Construction, Factor Investing & Risk Premia

11.10

Chair's opening remarks

11.20

Strategic portfolio allocation through factors

  • Traditional asset allocation overlooks key underlying drivers of risk and returns
  • Factor-based approach to risk measurement and strategic allocation provides numerous benefits
  • Macro and style factors provide a simple framework for thinking about systemic risk
  • Tools and technology are critical for empowering strategic portfolio allocators in a factor-based process

Bob Bass, Managing Director, Head of Factor Allocation Platform, BLACKROCK 

11.50

Factor Based Investing - Smart Beta in fixed income

  • Factor based investing - the alternative to active or passive styles of investment
  • Identifying the right smart beta approaches
  • Innovative factor based strategies in fixed income
  • Discussion on what some of the key factors are particularly in fixed income

Ritirupa Samanta, Managing Director, Global Head of Systematic Fixed Income & Senior Portfolio Manager, STATE STREET GLOBAL ADVISORS

12.20

How machines learn to trade: Portfolio optimization meets reinforcement learning

Gordon Ritter, ‎Senior Portfolio Manager, GSA CAPITAL

12.50

Lunch and opportunity to network

1.50

CALL FOR PAPER WINNER: ‎Parallel processing for the pricing of financial derivatives: Examples with SPX and SPY options

Louis Scott, Officer, FEDERAL RESERVE BANK OF NEW YORK

2.20

Dynamic index tracking and exposure control

  • Controlling exposure to various market factors and indices is crucial for both institutional and individual investors, but it can be very challenging, especially if the factors are not directly tradable
  • Continuous-time framework for dynamically tracking an index and its factors using related derivatives, along with strategies for achieving any pre-specified exposure to given factors
  • Numerical and empirical examples to illustrate the effectiveness of tracking strategies, with examples using VIX, and related options, futures, and ETPs

Tim Leung, Associate Professor, Director of Computational Finance and Risk Management Program, UNIVERSITY OF WASHINGTON

STREAM TWO: Models & Volatility

11.10

Chair's opening remarks

11.20

Filling the gaps smoothly

  • Analyses a problem of calibration of local volatility models to a given set of option prices
  • Presents a new approach developed by:
    -Replacing a piecewise constant local variance construction with a piecewise linear one still preserving closed form solution
    - Allowing non-zero interest rates and dividend yields

Andrey Itkin, Director, Senior Quant Research Associate, BANK OF AMERICA

11.50

Unspanned stochastic volatility with jump diffusion

  • The phenomenon of short term and long term rates of major currencies behaviour
  • How such behavior adds an extra complexity to and how can we tackle it?
  • Applying jump diffusion and conformal geometry to successfully tackle such market behavior

Gregory Pelts, Quant, BLACKROCK

12.20

Theory and practice of arbitrage-free parametric volatility surface construction and real-time fitting

  • The construction of implied volatility curves/surfaces that can fit all the vanilla options of liquid underliers like the SPX or VIX indices, the SPY ETF, the E-mini futures, or stocks like AAPL in a robust and bias-free manner, is well-known to be a very hard problem
  • The problem gets even harder if this is supposed to be accomplished in real-time as required for a listed options market maker, and in a completely arbitrage-free manner for all strikes and terms, as required to be useful as input to the calibration of various "SLVJ" models for exotics
  • We describe how this can be accomplished, illustrating our results with real-world examples

Timothy Klassen, CEO and Founder, VOLAR

12.50

Lunch and opportunity to network

1.50

Total risk-based project valuation

  • Critique of the NPV framework: Unsupportable results
  • The argument for pricing on total risk rather than covariance risk
  • Derivation of a total risk pricing formula
  • Extensions of the methodology
  • Applications to derivatives
  • Applications to corporate finance: The capital structure and hedging decision

David Shimko, Adjunct Professor of Finance, NYU TANDON SCHOOL OF ENGINEERING

2.20

A jump on default approach to modeling multiple default contingent payoffs

  • Copula models are usually used in order to capture multiple default contingent payoffs
  • As such, this standard approach fails to capture credit curve gamma and cross-gamma impacts arising from non-linear dependency on CDS spreads
  • Neglecting these impacts lead to unexplained P&L swings for the delta hedged portfolios, as it had been demonstrated during crisis
  • Our approach retains systemic default feature while taking into account a joint dynamics of credit spreads

Alexander Veygman, Director, Senior Fixed Income Quantitative Analyst, HSBC

2.50

Afternoon break

3.20

GUEST KEYNOTE ADDRESS: Arbitraging the high cost of space on dealer balance sheets

  • Evidence from FX, swap, and repo markets that dealer balance sheet space has gotten much more expensive, mainly because of new bank regulations, especially the leverage ratio rule
  • Use corporate finance principles to estimate the shadow price of balance sheet space, and explain how market practices and infrastructure are responding to the higher cost of space 
  • Examples include funding value adjustments, compression trade, direct repo, repo CCPs, riskless-principal trades, and covered-interest-parity basis arbitrage

Darrell Duffie, Dean Witter Distinguished Professor of Finance at the Graduate School of Business, STANFORD UNIVERSITY

3.50

EXECUTIVE ADDRESS: FinTech education: Leveraging technology to understand quantitative finance: theory and practice

  • Say it: Yin & Yang - Hard-core math, made easy
  • See it: Visualization - Voiced-over simulations as opposed to lecture recording
  • Do it: Interactive computing- Live data, cloud-based computing, hosted editing for on-the-fly replication
  • Share it: Community - Slide neutralization, feedback looping
  • Frame it: Cross-linking- Multi-media interconnectivity, spoke-to-hub architecture

Attilio Meucci, Founder, ARPM (Advanced Risk and Portfolio Management)

4.20

CLOSING KEYNOTE ADDRESS: The present of futures

  • The convexity conundrum in the old world
  • The convexity conundrum in the new world
  • A multi-curve hybrid Cheyette-LMM model
  • Solving two specific tractable cases
  • Numerical examples

Fabio Mercurio, Head of Derivatives Research, BLOOMBERG 

4.50

Chairperson's closing remarks. End of the conference.