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08:30: Morning Welcome Coffee Image result for yves hilpisch

Chair: Yves Hilpisch: 

Founder and Managing Partner

The Python Quants


09.00 - 10.00: Keynote

Presenter: Vacslav Glukhov, PhD: Executive Director, Linear Quantitative Research, Global Equities, J.P. Morgan (to be confirmed)

Topics in Self-Learning Agents and Traditional Quantitative Models in Finance 

  • What can we draw from our experience of training and running an industry first self-learning agent for electronic order execution?
  • Will traditional hand-crafted heuristic- and quant-based execution algorithms go extinct within 10 years?
  • Does the success of ML and AI agents in finance indicate the eventual demise of traditional quantitative models?
  • Practical aspects of using feeder models and heuristics in AI agents for trading applications.
  • Do we have practical solutions for the equivalence puzzle in Neural Nets?

10.00 – 10.45"Applications & Challenges of using Deep Learning & Bayesian Inference Methods for High Frequency Market Making"

 

 

Presenters: Farhan Feroz: eFX Quantitative Trader & Pawel Chilinski: Quantitative Trader, UBS 


10.45 – 11.15: Morning Break and Networking Opportunities


11.15 - 12.00: Reliable Machine Learning 

  • Robustness
  • Awareness
  • Adaptation
  • Value learning
  • Monitoring

Presenter: Lawrence Edwards: Executive Director, Morgan Stanley (To be confirmed) 


12.00 - 12.45: From Artificial Intelligence to Machine Learning, from Logic to ProbabilityPaul Bilokon, PhD

Applications of Artificial Intelligence (AI) and Machine Learning (ML) are rapidly gaining steam in quantitative finace. These terms are often used interchangeably. However, the pioneering work on AI by participants of the Dartmouth Summer Research Project --- Marvin Minsky, Nathaniel Rochester, and Claude Shannon --- was more symbolic than numerical, and often used the language of logic. Recent advances in ML --- especially Deep Learning --- are more numerical than symbolic, and often use the language of probability. In this talk we shall show how to connect these two worldviews.

Presenter: Paul Bilokon: Founder, CEO,Thalesians, Senior Quantitative Consultant, BNP Paribas & Visiting Lecturer, Imperial College 


12.45- 13.45: Lunch


13.45 – 14.30: AI-First Finance and Algorithmic TradingImage result for yves hilpisch

  • This talk considers the consequences of recent advances in the field of Artificial Intelligence (AI) for finance in general and algorithmic trading in particular.
  • The talk is mainly based on practical examples, using Python as well as Machine & Deep Learning techniques to come up with algorithmic trading strategies.
  • The examples in turn are mainly based on (tick) data from FXCM Forex Capital Markets Ltd. and their new RESTful API for data retrieval and algorithmic trading. 

Presenter: Yves Hilpisch: Founder and Managing Partner, The Python Quants


14.30 – 15.15: Using Big Data to Trade FX (& Python for finance)  

  • Discussion of what Big Data is with financial examples
  • Brief overview of machine learning
  • Case study on using machine readable Bloomberg News to trade FX
  • Python for financial analysis with interactive demo

 Presenter: Saeed Amen: Quant strategist & trader, Cuemacro


15.15 - 15.20: Quick Afternoon Break


15.20 - 16.00: Big Data and AI Strategies: Machine Learning and Alternative Data Approach to Investing

Abstract: The past few years have witnessed widespread adoption of quantitative investment techniques including risk premia investing, algorithmic trading, utilization of differentiated types of data and adoption of new methods of analysis drawn from machine learning and artificial intelligence. We will provide an overview of big/alternative data – including sentiment signals from RavenPack – and illustrate their use for different investors. We will explain the use of machine learning techniques - covering both classical and deep learning methods - in design of systematic strategies across asset classes.

Presenter: To be confirmed 


16.00 – 16.45: “Can AI help FRTB?”

“Time Series Data & FRTB - time to get it right”

Presenter: John Barclay: Managing Director, RiskTensor