Finance Seminar with Anton Lines, Columbia Business School
The Department of Finance is proud to announce the upcoming seminar with Anton Lines, Columbia Business School.
Anton Lines will present: What Drives Trading in Financial Markets? A Big Data Perspective
We use deep Bayesian neural networks to investigate the determinants of trading activity in a large sample of institutional equity portfolios. Our methodology allows us to evaluate hundreds of potentially relevant explanatory variables, estimate arbitrary nonlinear interactions among them, and aggregate them into interpretable categories. Deep learning models predict trading decisions with up to 86% accuracy out-of-sample, with market liquidity and macroeconomic conditions together accounting for most (66 − 91%) of the explained variance. Stock fundamentals, firm-specific corporate news, and analyst forecasts have comparatively low explanatory power. Our results suggest that market microstructure considerations and macroeconomic risk are the most crucial factors in understanding financial trading patterns.
Solbjerg Plads 3
More information will follow.