Research award 2020
IQAM Research, DekaBank’s private institute for quantitative capital market research, has awarded a research prize for innovative research in the field of capital markets for the third time as part of its science promotion program.
The first prize was awarded to the scientific paper “The effect of innovation similarity on asset prices and M&A deals: Evidence from patents’ Big Data” by Ron Bekkerman, Eliezer M. Fich and Natalya Khimicha from Drexel University, Philadelphia. The researchers use machine text analysis to identify similarities between companies. These are used both to explain dependencies in returns and to estimate probabilities of mergers and acquisitions.
Second prize was awarded to the paper “Estimating The Anomaly Base Rate” by Alex Chinco, Andreas Neuhierl and Michael Weber from the Universities of Chicago and Illinois. The authors critically review the variety of factors that have been proposed in asset pricing and discuss whether researchers are using the correct significance tests in their asset pricing studies. A procedure for estimating the “anomaly base rate” is developed to avoid possible fallacies in interpreting the results.
Third prize was awarded to Doron Avramov, Si Cheng, and Lior Metzker from IDC Herzliya in Israel for their paper “Machine Learning versus Economic Restrictions: Evidence from Stock Return Predictability.” The authors analyze stock selection with Neural Networks (NN) and Generative Adversarial Networks (GAN) with realistic investment restrictions (transaction costs, exclusion of “distressed firms” and “microcaps”) . They find that realistic investment restrictions strongly reduce the profitability of machine learning strategies.
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