Effects on stock investments of information about short versus long price series

Purpose - The purpose of this paper is to investigate whether stock price predictions and investment decisions improve by exposure to increasing price series. Design/methodology/approach - The authors conducted three laboratory experiments in which undergraduates were asked to role‐play being investors buying and selling stock shares. Their task was to predict an unknown closing price from an opening price and to choose the number of stocks to purchase to the opening price (risk aversion) or the closing price (risk taking). In Experiment 1 stock prices differed in volatility for increasing, decreasing or no price trend. Prices were in different conditions provided numerically for 15 trading days, for the last 10 trading days, or for the last five trading days. In Experiment 2 the price series were also visually displayed as scatter plots. In Experiment 3 the stock prices were presented for the preceding 15 days, only for each third day (five days) of the preceding 15 days, or as five prices, each aggregated for three consecutive days of the preceding 15 days. Only numerical price information was provided. Findings - The results of Experiments 1 and 2 showed that predictions were not markedly worse for shorter than longer price series. Possibly because longer price series increase information processing load, visual information had some influence to reduce prediction errors for the longer price series. The results of Experiment 3 showed that accuracy of predictions increased for less price volatility due to aggregation, whereas again there was no difference between five and 15 trading days. Purchase decisions resulted in better outcomes for the aggregated prices. Research limitations/implications - Investorś performance in stock markets may not improve by increasing the length of evaluation intervals unless the quality of the information is also increased. The results need to be verified in actual stock markets. Practical implications - The results have bearings on the design of bonus systems. Originality/value - The paper shows how stock price predictions and buying and selling decisions depend on amount and quality of information about historical prices.