Is there a window of exploitation before prices of individual stocks incorporate relevant information shocks? If so, what is its duration? In their January 2011 paper entitled “Speed of Convergence to Market Efficiency: The Role of ECNs”, Dennis Chung and Karel Hrazdil investigate the duration of stock price inefficiency based on the time interval over which order imbalances significantly predict short-term returns. They focus on the effect of electronic networks on this duration. Using high-frequency stock trade and quote data, institutional ownership levels and market capitalizations for 2,041 firms with shares trading contemporaneously on NYSE and an electronic network (Arca) during the first six months of 2008, they find that:
- The average duration of stock price inefficiency is about 27 (33) minutes for NYSE (Arca).
- For the 150 largest stocks, the average (median) duration of inefficiency is about 11 (five) minutes on both NYSE and Arca.
- For the smaller 1,891 stocks, the average duration of inefficiency is at least 26 (31) minutes on NYSE (Arca).
- Factors that tend to compress the duration of inefficiency are high trading volume (strongest impact), high participation of institutional traders and low participation of noise traders. The latter two factors are significant only for the smaller-firm subsample.
- After controlling for trading costs, volatility, noise traders, institutional traders and firm size, Arca compresses the duration of inefficiency by about five minutes compared to NYSE for both large and small firms.
In summary, evidence suggests that traders face a shrinking window for exploiting short-term stock price inefficiencies (order imbalances) as trading becomes more automated, with the longest windows perhaps available for small capitalization stocks with low volume and low institutional ownership.
The study does not address trading strategies for (or therefore profitability of) exploiting these inefficiencies. It seems reasonable to suppose that the recent acceleration of high-frequency trading is further compressing durations of order imbalance effects on stock prices.
