Conference Day Two: March 18 2020
8:00 am - 8:40 am Registration and coffee in the exhibition area
KEYNOTES & OPENING PLENARY SESSIONS
8:40 am - 8:50 am Chair's opening remarks
Chair's welcome and start of conference
8:50 am - 9:20 am Black box vs Explainable AI
- Mixing AI with human expertise and knowing when to intervene
- Solving the interpretability problem and understanding what is driving performance
- Enabling users to interpret, understand and explain machine generates predictions
9:20 am - 9:50 am Trends in utilization of machine learning and big data in finance
- How the availability of novel datasets and advanced analytical techniques has changed the financial landscape
- Specific use cases around alternative data and quantitative signal development to posit a framework for future application of AI within finance
- Impact of AI across different lines of business
9:50 am - 10:30 am Panel: Keeping a competitive edge past the use of alt data
- Now the value of alt data is understood, where do we go from here?
- Leveraging data from multiple sources and expert research networks
- Using analysis surrounding people and connectivity to gain deeper insights
10:30 am - 11:00 am Networking refreshment break in the exhibition area
11:00 am - 11:20 am Alpha, risk and customer satisfaction: Advances in AI for natural language
Exciting progress in AI for natural language has been made in the past year. Models that work with language in context are demonstrating human or better level ability to respond to questions and process language. NVIDIA will cover the key moment that spurred this progress, and talk about how it can be applied across the industry to provide richer information to discretionary or systematic trading. We will talk about how these advances can be used to provide new information for risk analytics, and how firms are starting to leverage these models to improve the customer service experience.
11:20 am - 11:50 am Building data teams and data engineering at Point 72
- Mapping the recruitment landscape and how to ensure you remain competitive in hiring and retaining data professionals
- Where to find the best talent in the industry
- Outlining the infrastructural data strategy and a leading fund
11:50 am - 12:30 pm Panel: Portfolio managers’ panel
The introduction of data science teams came with promises of significant new alpha. A panel of leading PMs debate whether they have delivered
12:30 pm - 1:30 pm Lunch and learn: Mathworks
AFTERNOON STREAMS
STREAM A
1:30 pm - 1:35 pm Stream A: Alt data case studiesSTREAM A
1:35 pm - 1:55 pm In and out: The making of an alternative dataset- Case study covering the life-cycle of a single alternative dataset, covering every stage of the data pipeline
- Aggregating and anonymizing data while retaining its information content
- Using ML and human-in-the-loop techniques to process incomplete or ambiguous input data
STREAM A
1:55 pm - 2:40 pm Panel: Determining the right combination of datasets to manipulate to gain an edge- Ensuring your datasets are easy to manipulate, visualize and model
- Assessing and eliminating bias from alt data sets
- Understanding the data for dataset prioritization and alpha capture
STREAM A
2:40 pm - 3:25 pm Panel: The future of alt data – unlocking the full potential of non-market data
Moderator:
Michael Marrale Chief Executive Officer M Science LLC
Speakers:
Konstantin Korobkov Data Technologies Leader Carlson Capital
Chris Petrescu Former Head of Data Strategy ExodusPoint
Todd Schmucker Former Director, Data Sourcing & Strategy Balyasny Asset Management
Scott Solomon Global Head UBS Evidence Lab
Michael Marrale Chief Executive Officer M Science LLC
Speakers:
Konstantin Korobkov Data Technologies Leader Carlson Capital
Chris Petrescu Former Head of Data Strategy ExodusPoint
Todd Schmucker Former Director, Data Sourcing & Strategy Balyasny Asset Management
Scott Solomon Global Head UBS Evidence Lab
- Using new data and combined datasets not just to find alpha
- As acquisition and analysis of alt data is now commonplace, how can we use it for the next big thing?
- Recapturing alpha – is alt data the only way?
STREAM B
1:30 pm - 1:35 pm Stream B: Quant and risk methodsSTREAM B
1:35 pm - 1:55 pm Developing understanding of non-linear drivers that occur during severe market events- Building better economic models from explainable AI
- Utilizing different operational risk modelling frameworks
STREAM B
1:55 pm - 2:15 pm How to stimulate research and innovation in finance- Articulating a new strategy – testing new alternative datasets, new open-source techniques and machine learning processes
- Importance of organisations to allow for the development of creativity and innovation
STREAM B
2:15 pm - 2:55 pm Panel: Assessing risk factors of a pure quant strategy
Moderator:
Sanne de Boer Director of Quantitative Equity Research Voya
Speakers:
Anjelika Klamp Managing Director CITE Investments
Mikhail Samonov CEO Two Centuries Investments
Judith Gu Director US Equity Sales and Trading Scotia Bank
Marc Antonio Awada Chief Risk & Data Analytics Officer Alpha Innovations
Sanne de Boer Director of Quantitative Equity Research Voya
Speakers:
Anjelika Klamp Managing Director CITE Investments
Mikhail Samonov CEO Two Centuries Investments
Judith Gu Director US Equity Sales and Trading Scotia Bank
Marc Antonio Awada Chief Risk & Data Analytics Officer Alpha Innovations
- Choosing, combining and validating data to reduce risk
- Remaining competitive
- Adapting and reacting to structural breaks
STREAM B
2:55 pm - 3:25 pm Data linkage to produce a new, richer dataset with value- Linking datasets from different data sources for a clearer, more accurate outcome
- Process of data linkage as applied to financial market
STREAM C
1:30 pm - 1:35 pm Stream C: Data analysisSTREAM C
1:35 pm - 1:55 pm Finding signal from noisy corporate filings, management presentations and news/social media – quantifying the value of competitive data sets- Incremental information from corporate regulatory filings conferences calls and news/social media
- Using NLP, psychology research and machine learning to extract signals from textual information
STREAM C
1:55 pm - 2:15 pm Intersection of AI and blockchain for trading•Understanding the trading concepts and processes of emerging digital assets
•Manoeuvring the lack of regulation of stocks and commodities within block chain
•Buy-side and sell-side applications of blockchain
STREAM C
2:15 pm - 2:55 pm Open forum: Navigating data challenges with latest ML/AI applicationsOpportunity to bring your challenges and put them to our expert Machine Learning panel.
STREAM C
2:55 pm - 3:25 pm Quantitative valuation and trading strategies in crypto assets- Overview of existing categories of crypto assets and valuation of each
- Analysis of crypto data sources, such as onchain transactions and sentiment
- Trading strategies specific to crypto assets and how they differ from traditional strategies
3:25 pm - 3:55 pm Networking refreshment break in the exhibition area
STREAM A
3:55 pm - 4:00 pm Stream A: Market microstructure and HFTSTREAM A
4:00 pm - 4:20 pm The importance of clean-up cost in algorithmic trading- Stochastic control model for calculating magnitude of clean up cost analytically
- Using ML and dynamic programming to solve the high dimensional problem
STREAM A
4:20 pm - 5:00 pm Panel: Large scale application of ML for microstructure analysis- Understanding what systematic signals or information is contained in microstructure data
- Assessing preliminary microstructure analysis and liquidity
Michael Steliaros
Global Head of Quantitative Execution Services at Goldman SachsGoldman Sachs
STREAM A
5:00 pm - 5:20 pm Extracting signal from HFT microstructure data to build effective predictive models- Applying ML to problems arising from HFT for trade execution and alpha generation
- Informationally efficient algorithms for inferring good predictive models from large datasets
- Problems arising in HFT with trade execution and alpha generation
Stefan Zohren
Academic Faculty MemberOxford-Man Institute of Quantitative Finance, University of Oxford
STREAM B
3:55 pm - 4:00 pm Stream B: ESG and sustainable investing
STREAM B
4:00 pm - 4:20 pm NLP meets Glassdoor and BofAML US equity fundamental analysts research reports- Extracting alpha from Glassdoor by applying NLP to reviews
- Discuss new proprietary BofAML Analyst Tone signal, applying NLP to US equity research reports for sector rotation trading strategy
- Detecting ‘deception’: Analyzing earnings calls transcripts as a management quality factor
STREAM B
4:20 pm - 4:40 pm Integrating alpha into your ESG portfolio- Using ESG metrics to capture the return and risk drivers that traditional financial metrics can’t
- Advantages of an ESG quant approach
- How ESG consideration can enhance both a portfolio’s economic performance and ESG profile
STREAM B
4:40 pm - 5:20 pm Panel: Sustainable investing for risk management vs alpha generation- Understanding how to incorporate ESG into your portfolios
- AI enabling the construction of new datasets for analysing sustainable investments
- Combining ESG metrics with other data sources and types to assess sustainability performance
STREAM C
3:55 pm - 4:00 pm Stream C: Data ethics and privacySTREAM C
4:00 pm - 4:40 pm Privacy vs Alpha- The moral hazard of alpha and privacy breach
- The risks of exposing personal data
- Finding privacy-friendly alpha
STREAM C
4:40 pm - 5:20 pm Panel: Challenges from data preparation to deployment – AI governance and privacy
Speakers:
Max Abend Vice President PDT Partners
Thierry Valat De Cordova General Counsel, Chief Compliance Officer and AML Compliance Officer Dominon Capital
Sharad Shandilya VP AI Practice Lead Fidelity Investments
Ishaan Nerurkar CEO LeapYear
Jonathan Chin Co-Founder & SVP, Product Management ARM Insight
Max Abend Vice President PDT Partners
Thierry Valat De Cordova General Counsel, Chief Compliance Officer and AML Compliance Officer Dominon Capital
Sharad Shandilya VP AI Practice Lead Fidelity Investments
Ishaan Nerurkar CEO LeapYear
Jonathan Chin Co-Founder & SVP, Product Management ARM Insight
- Trading data that is and isn’t in public domain
- How to uncover bias in underlying data types, data sets, ML models and processes
- Compliance (and capability) – wise can companies afford to stay in the cloud?
Thierry Valat De Cordova
General Counsel, Chief Compliance Officer and AML Compliance OfficerDominon Capital
