Boosting Agnostic Fundamental Analysis: Using Machine Learning to Identify Mispricing in European Stock Markets

2021 ◽  
Author(s):  
Matthias Xaver Hanauer ◽  
Marina Kononova ◽  
Marc Steffen Rapp
2018 ◽  
Vol 53 (4) ◽  
pp. 1615-1651 ◽  
Author(s):  
Guido Baltussen ◽  
Sjoerd van Bekkum ◽  
Bart van der Grient

Stocks with high uncertainty about risk, as measured by the volatility of expected volatility (vol-of-vol), robustly underperform stocks with low uncertainty about risk by 8% per year. This vol-of-vol effect is distinct from (combinations of) at least 20 previously documented return predictors, survives many robustness checks, and holds in the United States and across European stock markets. We empirically explore the pricing mechanism behind the vol-of-vol effect. The evidence points toward preference-based explanations and away from alternative explanations. Collectively, our results show that uncertainty about risk is highly relevant for stock prices.


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