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Abstract:
We find that turnover rises on n-day highs and lows and is an increasing function of n. We offer several explanations from the technical and behavioral finance literature for why traders might use these signals. Turnover is persistent following these events, and new lows provide abnormal returns for up to 6 trading days.

behavioral finance, technical analysis, turnover, n-day high/low, abnormal returns

Abstract:
We analyze the trading activity in an Internet chat room over a four-year period. The data set contains nearly 9,000 trades from 676 traders. We find these traders are more skilled than retail investors analyzed in other studies. 55% make profits after transaction costs, and they have statistically significant alphas of 0.17% per day after controlling for the Fama-French factors and momentum. Traders hold their winners 25% longer than their losers. 42% trade both long and short, with equal success rates, and almost double the profit per trade when short. The estimates show a strong influence from other traders, with a buy (sell) order 40.7% more likely to be of the same sign if there has been a recent post. Traders improve their skill over time, earning an extra $189 per month for each year of trading experience. They also gain expertise in trading particular stocks. Traders who raise their Herfindahl index by 0.1 raise their profitability by $46 per trade.

behavioral finance, day trading, familiarity bias, disposition effect, experts