“IQ, Trading Behavior, and Performance”, Mark Grinblatt, Matti Keloharju, Juhani T. Linnainmaa2012-05 (, ; backlinks; similar)⁠:

We analyze whether IQ influences trading behavior, performance, and transaction costs. The analysis combines equity return, trade, and limit order book data with two decades of scores from an intelligence (IQ) test administered to nearly every Finnish male of draft age. Controlling for a variety of factors, we find that high-IQ investors are less subject to the disposition effect, more aggressive about tax-loss trading, and more likely to supply liquidity when stocks experience a one-month high. High-IQ investors also exhibit superior market timing, stock-picking skill, and trade execution.

Figure 1: Cumulative distribution of the cross-section of investors’ annualized portfolio returns. This figure plots the cumulative distribution (CDF) of the cross-section of investors’ annualized returns for subgroups of investors sorted by IQ (stanines 1–4 or stanine 9). The sample excludes investors who held stocks for fewer than 252 trading days in the sample period. Returns for each investor are annualized from the average daily portfolio returns computed over days the investor held stocks. The daily portfolio return is the portfolio-weighted average of the portfolio’s daily stock returns. The latter are close-to-close returns unless a trade takes place in the stock, in which case execution prices replace closing prices in the calculation. The returns are adjusted for dividends, stock splits, and mergers. IQ data [n = 87,914] are from 1982-01–19y2001-1223ya. Remaining data are from 1995-01–7y2002-1122ya.

[High-IQ investors timed the dot-com bubble better than low-IQ bagholders:]

Figure 2: Entries into technology stocks as a function of time and IQ stanine. This figure analyzes investors’ entry into technology stocks as a function of time and IQ. We calculate for each IQ group and week the proportional entry rate, and the ratio of number of entrants into technology stocks to the number of investors already holding technology stocks. The ratios are ranked within each week 1–6 among the IQ groups. The figure calculates the 12-week average of the ranks and plots these smoothed entry rates. Green (red) color indicates high (low) propensity to enter the market. Technology stocks are defined as stocks that belong to the “Technology” industry according to the official HEX classification. Entry must happen by means of an open market buy (IPOs, seasoned offerings, and exercise of options are excluded). An investor can enter the market at most once in these computations and counts at most as one technology-stock owner regardless of the number of technology stocks owned. The black solid line is the log of the 12-week average of the HEX tech stock index. IQ data are from 1982-01 to 2001-12.
Figure 2: Entries into technology stocks as a function of time and IQ stanine. This figure analyzes investors’ entry into technology stocks as a function of time and IQ. We calculate for each IQ group and week the proportional entry rate, and the ratio of number of entrants into technology stocks to the number of investors already holding technology stocks. The ratios are ranked within each week 1–6 among the IQ groups. The figure calculates the 12-week average of the ranks and plots these smoothed entry rates. Green (red) color indicates high (low) propensity to enter the market. Technology stocks are defined as stocks that belong to the “Technology” industry according to the official HEX classification. Entry must happen by means of an open market buy (IPOs, seasoned offerings, and exercise of options are excluded). An investor can enter the market at most once in these computations and counts at most as one technology-stock owner regardless of the number of technology stocks owned. The black solid line is the log of the 12-week average of the HEX tech stock index. IQ data are from 1982-0119y2001-1223ya.