Abstract: Economic decisions are often made after human interactions. This paper proposes an empirical approach to process and quantify features of micro-level human interactions, documents their connections to financial investment decisions, and investigates the underlying economic mechanisms. Using machine learning (ML)-based algorithms with videos as data input, we quantify human interactions in three-V dimensions—visual, vocal, and verbal—and construct interpretable metrics along these dimensions. We apply our method to videos of entrepreneurs pitching investors for funding. We find that venture investors are more likely to invest in startup teams that show more positivity (i.e., happy, warm, passionate), and the penalty of deviating from these features is larger for women. This relation does not appear to be driven by investors correctly calibrating startup quality using pitch features. Instead, through pitch data analysis and an experiment, we show that interaction features affect economic decisions through both the taste-based channel (18 percent) and the inaccurate beliefs channel (82 percent). Overall, the evidence is consistent with interaction-induced biases.
Abstract: Due to their complex features, structured financial products harm the average investor. But, can some investors benefit from this complexity? Using account-level transaction data of retail structured funds, we show that the rich (sophisticated) benefit from complexity at the expense of the poor (naive). The poor-to-rich wealth transfer that results from trading structured funds is an order of magnitude greater than the wealth transfer from trading simple, non-structured funds. In an event study, we further confirm that the wealth transfer can be partially attributed to investors' differing responses to complexity. In particular, when a market crash triggers funds into a restructuring process and their prices are expected to shrink by half on a given day, the poor and naive subset of investors fail to respond effectively.
Work in Progress
Self-Selected or Designated: Which SIC Code is True?
Real Life Experience and Financial Risk Taking: Evidence from Automobile Traffic Accidents