Machine learning is very powerful, allowing you to organise data sets and identify relationships that the human eye can't see. But how can investors get the best from it?
Join Andrea Nardon, Head of Quant, as he discusses:
* The difference between AI and machine learning
* Examples of the main types of algorithms and models used
* Whether there's any predictive power in the daily historical returns of a stock
* If outperformance can be generated by examining candlesticks of how a security moves throughout the day
Quantitative Analyst Ben Human discusses whether traditional indices really capture the benefits of investing in commodities, and if the risk premia often used in equities can also be applied successfully here.