Graduated in Statistics and Economics at the University of Bologna, has a Quantitative Finance degree at Fitch CQF in London. He wrote a book as an author “Effective Technical Analysis Applied to Trading Systems” and other books as a co-author. He has published several papers: “Multivariate time series analysis” and “Uncertain volatility in options pricing” for Fitch-CQF and several other volatility papers. Lifelong private trader, he has been involved in several trading championship winning the first place in 2011. He has been working in London since 2008 as an investment manager for: Equity Line Solutions Ltd, Seven Mills ltd and Quantlab Ltd, applying quantitative algorithmic automated trading models on futures and options.
Artificial Intelligence and Trading Systems
The speech will begin with the general explanation of what artificial intelligence and neural networks are, then it will switch to their application to financial markets, specifically derivatives: futures and options. In particular, you will see how one can start from the formulation of a classic forecasting econometric models, such as VAR and VEC used in multivariate time series analysis, to build the skeleton of the model. Subsequently, this can be improved by introducing new generation neural networks. This will improve the model forecasting performance by allowing it to overcome the problem of non-linearity that is typical and present in all financial time series.