March 15 - 17, 2021
| Metropolitan Pavilion, New York
Conference Day One: June 30 2020
8:00 am - 8:40 am
Welcoming tea, coffee and registration
KEYNOTES & OPENING PLENARY SESSIONS
8:40 am - 8:50 am
Chair's opening remarks
William Kelly -
Chief Executive Officer,
CAIA Association
Chair’s welcome and start of conference
8:50 am - 9:20 am
AI and capital markets – where are we now?
Jeff Wecker -
Advisor Director and Retired Partner,
Goldman Sachs
After the excitement of alt data, new ML techniques and cost-effective GPU availability, what’s actually been achieved in using AI in asset management? A global consultancy shares current research that’s mapped out what’s worked, what hasn’t and who’s now leading the pack
9:20 am - 10:00 am
Panel: The reality of implementing AI within financial markets
Ingrid Tierens -
Managing Director,
Goldman Sachs
Richard Craib - Founder & CEO, Numerai
Jonathan Larkin - Managing Director, Columbia Investment Management company
Mike Lock - Vice President, AQR Capital
Al Yazdani - VP Machine Learning Research Manager, State Street
Panel discussion on the realistic use cases of ML processes within financial markets – how to separate fad from reality and utilise Machine Learning effectively.
10:00 am - 10:30 am
AI based macro models
AI’s approach to macroeconomic modelling
10:30 am - 11:00 am
Networking refreshment break in the exhibition area
MORNING SESSIONS
11:00 am - 11:30 am
Keynote interview
Matthew Granade -
Chief Market Intelligence Officer & Managing Director,
Point72
Gregory Zuckerman - Special Writer, Wall Street Journal
Matt Granade is an experienced business leader using the intersection of advanced analytics, finance and technology to remain at the forefront of the industry. Previously building teams at Bridgewater Associates and now directing the central portfolio at Point 72, he is interviewed by Gregory Zuckerman on how they are revolutionizing finance and using data to shape their competitive investment philosophy.
11:30 am - 11:50 am
Moving beyond the hype of AI & ML: Practical examples from other industries
Michael Beal -
CEO,
Data Capital Management
AI and ML have become the frontier for digital transformation. However, many companies are struggling with getting real business value and many ML projects are getting stalled. Learn how AI and ML processes are applied in other industries and key elements that can be translated within trading to achieve a competitive edge while managing five new AI business risks.
11:50 am - 12:10 pm
Keynote: Quantum computing and future of finance
Michael Brett -
SVP of Applications,
Rigetti Computing
- The journey to achieving ‘Quantum readiness’ within financial market
- Use cases from within the industry and the obstacles needed to overcome to be fully integrated
- Potential impact of quantum computing on risk management and asset management
12:10 pm - 12:30 pm
Machine learning and NLP for long term investors
Peter Hafez -
Chief Data Scientist,
RavenPack
NLP can provide a great advantage to a trader, but can be more of an art rather than a science and as a result, outcomes can dramatically vary. Ravenpack’s chief data scientist outlines how to develop effective trading strategies based on machine learning algorithms and an NLP engine to demonstrate predictive power within capital markets
12:30 pm - 1:30 pm
Lunch and learn: Transforming your unstructured data into a strategic asset
James Viega -
Business Development Manager,
Ravenpack
AFTERNOON STREAMS
STREAM A
1:30 pm - 1:35 pm Stream A: Quant for fundamentalSTREAM A
1:35 pm - 2:15 pm Panel: Fundamental vs quantitative – comparing and blending strategies within the shifting market Miles Adkins - Customer Facing Data Scientist, DataRobotSheedsa Ali - Managing Director, Pinebridge Investments
Adam Braff - Founder, Braff & Company
Robert Morse - Head of Data Strategy and Sourcing, PDT Partners
- Successfully integrating AI into the quant trading workflow
- Assessing collaborative approaches that do and don’t work
STREAM A
2:15 pm - 2:35 pm Elements of Quantamental investing Brian Chingono - Partner, Verdad Advisers- Improving predictive accuracy by employing multiple models in your security selection process
- Choosing the right tool for the right job; how to apply ML in a way that supplements linear models
- Applying the principals of comparative advantage to identify task best handled by humans vs machines
STREAM A
2:35 pm - 3:25 pm Panel: Journey of embedding quant methods within your fundamental approach effectively Jess Stauth - Mananging Director, Fidelity LabsVenk Kidambi - Quantitative Analyst and Founder, Gyon
Vlad Andrei - Founder, Albaron Ventures
Iuliia Shpak - Quantitative Strategies Specialist, Sarasin & Partners LLP
Nico Smuts - Investment Data Scientist, Investec Asset Management
- Instigating the integration of new technology into a traditional structure
- Building internal capabilities through investment in people and technology
- Remaining competitive in a saturated market
STREAM B
1:30 pm - 1:35 pm Stream B: Data engineering and infrastructureSTREAM B
1:35 pm - 2:15 pm Data-informed insights: In-house vs outsourced Ganesh Mani - Adjunct Faculty, Carnegie Mellon; ex-SSgAFrancesco Filia - CEO, Fasanara
Cindy Mallory - Emerging Technologies Strategist, Worldwide TechServices
Bin Ren - Founder and CEO, SIG Technologies
- Identifying when to use in-house AI services vs outsourced options
-Determining how to get better insights, reduce costs and improve security and transparency
- Considerations necessary when deciding on a provider
STREAM B
2:15 pm - 2:55 pm Panel: Building an infrastructural data strategyDrake Bushnell - VP, Director, Data & Solutions, FactSet
Jesus Rodriguez - Chief Technology Officer, Into The Block
Tom Taylor - Head of Alpha Technology, Man Numeric
Ravi Trivedi - Assistant VP, Innovation and Decision Sciences, Nuveen
Mackenzie Hargrave - Specialist, FactSet Content Strategy
- How to reliably build a data strategy from scratch
- Defining your data strategy and investing in the infrastructural elements to support it
- Building models to optimize and predict investment outcomes
STREAM B
2:55 pm - 3:25 pm Commoditization of data engineering Tom Taylor - Head of Alpha Technology, Man Numeric- The future for the commoditization of data engineering
- Utilising cloud providers and open source tools to streamline your optimise your investment workflow
- Defining key aspects from whole investment workflow
STREAM C
1:30 pm - 1:35 pm Stream C: AI/ML case studies Miquel Noguer i Alonso - Co-founder, Artificial Intelligence Finance Institute - AIFI
STREAM C
1:35 pm - 2:05 pm Transfer learning for machine learning and NLP: adapting models to changing markets Andrew Arnold - Adjunct Professor, NYU- Challenges of transfer learning within financial markets
- Identifying how to use transfer learning to your advantage
- Techniques and case studies to adapt models across new instruments and markets
STREAM C
2:05 pm - 2:50 pm How are financial decisions made? Naftali Cohen - VP and AI research lead, JP Morgan Chase & Co- Outlining the process of making impactful decisions
- Using attention-tracking hardware and intuition-capturing techniques to quantify and model the financial decision-making process
- Assessing the dependency of decisions and their corresponding previous sequential activity
STREAM C
2:25 pm - 3:05 pm Panel: Building the optimal data/ML teams Caroline Sherman - Chief Product Officer and Managing Director, QuantopianAndrew Arnold - Adjunct Professor, NYU
Drew Conway - Senior Vice President, Two Sigma
Madison Kraus - Principal, Heidrick and Struggles
- Hiring and retaining the perfect data team
- The war for talent and where to find the best data professionals
- Identifying the skills needed for the best data professional in the industry and where to find them
STREAM C
3:05 pm - 3:25 pm Issues and solution building an AI-driven fund from scratch Jimmy Carlsson - Co-founder and CTO, Century Analytics AB- Bumps in the road in terms of biases, methodology, technology and data
- Diversified team, specialized methodology and AI design to avoid common pitfalls
- Alpha using an orchestra of agenda and a conductor based on deep reinforcement learning
3:25 pm - 3:55 pm
Networking refreshment break in the exhibition area
STREAM A
3:55 pm - 4:00 pm Stream A: Quant and risk methods Arpit Narain - Global Headl of Financial Solutions, Mathworks
STREAM A
4:00 pm - 4:20 pm Extracting insights from earnings transcripts Andrew Chin - Chief Risk Officer and Head of Quantitative Research, AllianceBernsteinYuyu Fan - Data Scientist, Alliance Bernstein
STREAM A
4:20 pm - 5:00 pm Panel: ML applications in risk managements and portfolio optimization Irina Bogacheva - Head of Multi-Asset Research, QS InvestorsRobert Gingrich - Manager, Derivatives, Alternative Risk, Quantiative Investment Solutions Group, Western Asset Management Group
Colm O'Cinneide - Head of Portolio Construction, QS Investors
Alireza Javaheri - Head of Equity Derivatives Quantitative Research, Credit Suisse
- Identifying when to intervene with AI model, when to leave it alone and when to start again
- Overcoming difficulty in explaining ML in risk models to clients (little economic interpretability)
- Validation and testing of ML models to mitigate risk
Robert Gingrich
Manager, Derivatives, Alternative Risk, Quantiative Investment Solutions GroupWestern Asset Management Group
STREAM A
5:00 pm - 5:20 pm Managing and modelling risk using ML for portfolio optimization Marc Antonio Awada - Chief Risk & Data Analytics Officer, Alpha Innovations- Allocating a risk budget based on model’s prediction of equity market
- Using ML to predict a stable portfolio
STREAM B
3:55 pm - 4:00 pm Stream B: Data quality and linkageSTREAM B
4:00 pm - 4:20 pm Ending overfitting systematically through Numerai’s data science tournament Richard Craib - Founder & CEO, Numerai- Obfuscating data to prevent bias
- Learning from adversarial users
- Blind hold out test data with no feedback
STREAM B
4:20 pm - 5:00 pm Panel: Tools for combatting cognitive bias Iuliia Shpak - Quantitative Strategies Specialist, Sarasin & Partners LLPJimmy Carlsson - Co-founder and CTO, Century Analytics AB
Arka Banyopadhyay - Principal Data Scientist, Rocktop Partners
- Ensuring data is accurate, complete and sufficient to be able to extract statistical significance
- What steps can we take to minimise or control data bias?
STREAM B
5:00 pm - 5:20 pm Combining Quantamental with alt data in the context of LBO predictions Milind Sharma - CEO, QuantZ Capital and QMIT- How to use data to predict Leveraged Buyouts
- Ascertaining benefits of trading with a Quantamental signal
- Preserving investment banker/PE intuition in guiding variable selection
STREAM C
3:55 pm - 4:00 pm Stream C: AI/ML case studiesSTREAM C
4:00 pm - 4:20 pm Factor forecasting and rotation: Comparing Econometric and Machine Learning approaches Francesco Fabozzi - Managing Editor, Journal of Financial Data Science- Highlighting the difference between econometric and machine learning approaches in developing factor forecasting and rotation using a high macroeconomic dataset
- Exploring techniques which are key in preventing overfitting
- Identifying machine learning approaches that outperform on a risk-adjusted basis
STREAM C
4:20 pm - 5:00 pm Panel: How to recover when machine learning goes wrong Drew Conway - Senior Vice President, Two SigmaBrandon Da Silva - Associate Portfolio Manager, OPTrust
Sharad Shandilya - VP AI Practice Lead, Fidelity Investments
Stan Yakoff - Head of Americas Supervision, Citadel
Denis Vritov - Head of Machine Learning Research, 7 Chord
- Identifying at what point human intervention is necessary
- Avoiding building models on spurious relationships
STREAM C
5:00 pm - 5:20 pm Use and misuses of ML in investing (Dial-in) Francesco Filia - CEO, Fasanara- Overcoming structural challenges and training models differently
- Driving value through cost reduction
- How to organize institutional data to scale
