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 Keynote: Quantum computing and future of finance
- The journey to achieving ‘Quantum readiness’ within financial markets
- 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
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
- Progress in NLP models in responding to questions and processing language
- Applying this across the industry for richer information in both discretionary and systematic trading
- Leveraging NLP to improves customer service process
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 Networking lunch in the exhibition area
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 The future of alt data – unlocking the full potential of non-market data- 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- 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 applications
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
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 investingSTREAM 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- 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
