Dr Maurizio Luisi is a quantitative strategist at AD-IRS in London. Previously he worked as Senior Portfolio Manager at Unigestion, focusing on research, development and trading of quantitative investment strategies. Prior to this he worked at Bloomberg, where he was responsible for research and development of the quantitative platform. Beforehand, he worked for six years at RBS, focusing on quantitative and proprietary trading within the Delta One desk. His career started off in the area of quantitative macro research, working for Bank of International Settlements and Goldman Sachs. Maurizio held teaching and research positions at different academic institutions including the Amsterdam Business School, Duisenberg School of Finance and University of Lugano. His research has appeared in leading academic journals, including the Journal of Financial Economics. He holds a Ph.D. in Finance from the Swiss Finance Institute and a master’s degree in Finance from the University of Warwick’s Business School.
From Nowcasting to Newscasting – Exploring the link between news sentiment, the economy and asset prices fluctuations
Established nowcasting techniques generally use as inputs two types of economic data: directly quantifiable variables, mostly referred to as hard data, and survey-based measures of the economy, or soft data. In this presentation, we increase the dimensionality of the nowcasting input data set by introducing a third type of data: machine-readable news analytics based on textual analysis. We propose to exploit the quantitative information conveyed by machine-readable news, transforming these analytics into proxies for macro-driven sentiment values. To retain tractability and facilitate the interpretation of this novel type of data, we aggregate the high–dimensionality of this information set into an established taxonomy of economically identifiable sentiment proxies; through this, we are able to map them into the same categories in which we group hard and soft data. We concentrate on U.S. economy as the focus of our analysis. The wider objective here is to extract and incorporate additional information relevant for tracking current and future economic conditions, but also and foremost to provide an empirical method to shed light on the interaction between macro news-flow sentiment, the real economy and asset prices fluctuations.