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Institutional Stock Trading Expertise

| | Posted in: Investing Expertise, Mutual/Hedge Funds

Does trading by expert investors boost performance (profitably exploit information), or depress performance (unprofitably exploit information or wastefully churn on noise)? In their September 2016 paper entitled “Trading Frequency and Fund Performance”, Jeffrey Busse, Lin Tong, Qing Tong and Zhe Zhang investigate the relationship between trading frequency and performance among institutional investors (funds). They specify fund daily trading frequency as number of trades divided by the number of unique stocks traded. They calculate fund quarterly trading frequency as average daily trading frequency during the quarter. For each buy or sell, they calculate the return from execution date (at execution price) to end of the quarter, including stock splits, dividends and sometimes commissions. They estimate quarterly fund trading performance by aggregating performances of buys and sells separately, weighted either equally or by trade size, such that the average holding interval is about half a quarter. They subtract fund benchmark return over the same holding interval to calculate abnormal return. They then examine the relationship between abnormal return and fund size. Using daily common stock transaction details for 843 fund managers and 5,277 unique funds, along with associated stock return and firm data, during January 1999 through December 2009, they find that:

  • The average fund places 310 trades on 74 unique stocks per quarter in 1999, growing to 763 trades on 106 stocks per quarter in 2009. Dispersion of trading frequencies across funds is large.
  • Over the entire sample period, the equally weighted average abnormal holding interval return is 0.35% (0.03%) for buys (sells).
  • There is a strong positive relationship between quarterly trading frequency and average abnormal trading return across funds.
    • Average abnormal return increases systematically over fifths (quintiles) of funds ranked by increasing trading frequency.
    • The most (least) active quintile has average gross abnormal holding interval return 0.55% (-0.18%) based on equal weighting and 0.31% (-0.15%) based on trade size weighting.
    • Based on average one-way trading friction 0.135%, debited twice for each trade, trading activity is profitable only for the top two quintiles of trading frequency (barely so for trade size weighting).
    • Results are very similar with and without years 2008 and 2009, suggesting that extreme market conditions do not drive findings.
  • The fund trading frequency effect persists for at least a year, as active funds continue to trade frequently and outperform.
  • Performance of active traders relates negatively to fund size. In other words, small active funds significantly outperform large active funds because of the frictions associated with larger trades.
  • Active traders outperform both by supplying liquidity (exploiting reversals) and by trading aggressively on information (trading around earnings announcements).

In summary, evidence indicates that relatively small funds can predictably generate alpha via frequent trading.

Cautions regarding findings include:

  • Individual investors generally cannot trade as cheaply as funds.
  • The 11-year sample is nearly nearly seven years stale.

See “The Lure of Trading?” for a summary of seminal research on the relationship between individual investor trading frequency and performance.

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