EP20: Prof Rob Hyndman: Forecasting COVID, time-series, and why causality doesnt matter as much as you think.

In this episode, I explore some of the more direct applications of Generative AI, specifically ChatGPT within a quantitative investment process, starting with expansions to NLP signals, to product strategy and client communications. It is just me this time, but I hope you like it. 

I spoke with Professor Russell at the beginning of the pandemic about AI and humanity. He is a world famous thinker, researcher and name in this field. Its raw.. it is unedited. It is exactly what you need to hear. No intros, no outros, no marketing. Just the conversation. 

Prof Rob Hyndman discusses the interesting elements of his work as editor of the Internal Journal of Forecasting, his work on forecasting COVID for the Australian government, time-series and causality. 

Fantastic conversation with Igor Halperin around the application of reinforcement learning into forecasting problem, and the limits to data and understanding the world. 

Nick Wade from Northfield and the Curious Quant discuss the impact of COVID on risk modeling frameworks, assumptions, and how the recent movements in asset markets may or may not impact the short and long-term assumptions of asset owners. 

I speak to Matt about his wonderful collection of old (retro?) computers but also all about the challenges of defining an ethical framework for algorithms, and what we can do to understand this tricky area. 

I speak with my a great voice of independent research in London on the topics of using alternative data for FX and macro research for quantitative strategies. We talk a lot about Saeed's well known work in macro-economics, in FX research, as well as his well known and regarded book. 

I chat with Christina about her experiences starting her own firm dealing with high frequency trading strategies, and her observations about how high frequency strategies have evolved, where they are now, and where they may be going in the future.

I chat with Asif on his career journey, how the world changed after the GFC and what he sees for the future of machine learning assisting with rigorous testing of a hypothesis. Career, systems, how the world changed after GFC, data sets that are interesting, AI and machine learning, neural networks, testing a hypothesis and data. Nothing on this podcast is to be considered investment advice or a recommendation. No investment decision or activity should be undertaken without first seeking qualified and professional advice.

I chat with Alex on his experiences across a range of environments, the role of machine learning in Australia's future and how to best deploy data science in academia and industry. Nothing on this podcast is to be considered investment advice or a recommendation. No investment decision or activity should be undertaken without first seeking qualified and professional advice.