Using experimental asset markets, we study the situation of a financial analyst who is trying to infer the fundamental value of an asset by observing the market's history. We find that such capacity requires both standard cognitive skills (IQ) as well as social and emotional skills. However,...

We compare the performance of financial professionals (CFAs) with university students in four financial forecasting tasks ranging from simple lab prediction tasks to longitudinal field tasks. Although students and professionals performed similarly in the artificial forecasting tasks, their...

We examine whether forecasters of earnings can be “nudged” into changing their forecasting behavior without altering their economic incentives or limiting their choices. We use a natural experiment on Estimize.com to quantify the effects of a nudge promoting a social norm of exerting one’s...

We investigate how individuals use measures of apparent predictability from price charts to predict future market prices. Subjects in our experiment predict both random walk times series, as in the seminal work by Bloomfield & Hales (2002) (BH), and stock price time series. We successfully...

In this study, we examine how information provision affects the degree of overconfidence using an online experiment. The 4,210 experimental participants engaged in stock market prediction exercises were asked to evaluate their absolute and relative performance. We conducted a randomized...

Technological progress in recent years has made new methods available for making forecasts in a variety of areas. We examine the success of ex-ante stock market forecasts of three major stock market indices, i.e., the German Stock Market Index (DAX), the Dow Jones Industrial Index (DJI), and the...

We compare the performance of financial professionals (CFAs) with university students in four financial forecasting tasks ranging from simple lab prediction tasks to longitudinal field tasks. Although students and professionals performed similarly in the artificial forecasting tasks, their...

We investigate how individuals use measures of apparent predictability from price charts to predict future market prices. Subjects in our experiment predict both random walk times series, as in the seminal work by Bloomfied and Hales (2002) (BH), and stock price time series. We successfully...

Although algorithms make more accurate forecasts than humans in many applications, decision-makers often refuse to resort to their use. In an economic experiment, we examine whether the extent of this phenomenon known as algorithm aversion can be reduced by granting decision-makers the...

We distill sentiment from a huge assortment of NASDAQ news articles by means of machine learning methods and examine its predictive power in single-stock option markets and equity markets. We provide evidence that single-stock options react to contemporaneous sentiment. Next, examining return...