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An Analysis of Intraday Patterns in Bid/Ask Spreads for NYSE Stocks

Journal of Finance 1992 47(2), 753-764
ABSTRACT The behavior of time‐weighted bid–ask spreads over the trading day are examined. The plot of minute‐by‐minute spreads versus time of day has a crude reverse J ‐shaped pattern. Schwartz identifies four determinants of spreads: activity, risk, information, and competition. Using a linear regression model, a significant relationship between these same factors and intraday spreads is demonstrated, but dummy variables for time of day have a reverse J ‐shape. For given values of the activity, risk, information and competition measures, spreads are higher at the beginning and end of the day relative to the interior period.

Adjusting for Beta Bias: An Assessment of Alternate Techniques: A Note

Journal of Finance 1986 41(1), 277-286
ABSTRACT This paper tests the effectiveness of techniques proposed by: Scholes‐Williams; Dimson; Fowler, Rorke, and Jog; and Cohen, Hawawini, Maier, Schwartz, and Whitcomb to control for bias in beta estimates from thin trading and price adjustment delays. Each technique produces beta estimates that reduce the amount of this bias, but the amount of reduction in the best case is only 29%.

Cointegration, Error Correction, and Price Discovery on Informationally Linked Security Markets

Journal of Financial and Quantitative Analysis 1995 30(4), 563
Using synchronous transactions data for IBM from the New York, Pacific, and Midwest Stock Exchanges, we estimate an error correction model to investigate whether each of the exchanges is contributing to price discovery. Johansen's test yields two cointegrating vectors, which together verify the expected long-run equilibrium of equal prices across the three exchanges. Two error correction terms specified as the differences from IBM prices on the NYSE indicate that adjustments maintaining the long-run cointegration equilibrium take place on all three exchanges. That is, IBM prices on the NYSE adjust toward IBM prices on the Midwest and Pacific Exchanges, just as Midwest and Pacific prices adjust to the NYSE.

An Investigation of Transactions Data for NYSE Stocks

Journal of Finance 1985 40(3), 723-739
ABSTRACT Using transactions data, the behavior of returns and characteristics of trades at the micro level is examined. A minute‐by‐minute market return series is formed and tested for normality and autocorrelation. Evidence of differences in return distributions is found among overnight trades, trades during the first 30 minutes following the market opening, trades at the close, and trades during the remainder of the day. The latter distribution is found to be normal. Unusually high returns and standard deviations of returns are found at the beginning and the end of the trading day. When the beginning‐and end‐of‐the‐day effects are omitted, autocorrelation in the market return series is reduced substantially. A number of patterns in trading are reported.

Volatility effects of institutional trading in foreign stocks

Journal of Banking & Finance 2006 30(8), 2199-2214 open access
This paper examines the impact of institutional trades on volatility in international stocks across 43 countries. There is a temporary volatility spike during the trade execution period, merely reflecting the price impact costs faced by the institutions. Cross sectional regressions suggest that trade imbalances, enforcement of insider trading laws, stock prices, and an emerging market classification are positively associated with temporary volatility increases whereas the presence of market makers and better shareholders’ rights dampen such increases. In the long term, institutional trades do not destabilize markets as the levels of volatility after their trades are almost identical to their pre-decision levels.

International Evidence on Institutional Trading Behavior and Price Impact

Journal of Finance 2004 59(2), 869-898 open access
ABSTRACT This study characterizes institutional trading in international stocks from 37 countries during 1997 to 1998 and 2001. We find that the underlying market condition is a major determinant of the price impact and, more importantly, of the asymmetry between price impacts of institutional buy and sell orders. In bullish markets, institutional purchases have a bigger price impact than sells; however, in the bearish markets, sells have a higher price impact. This differs from previous findings on price impact asymmetry. Our study further suggests that price impact varies depending on order characteristics, firm‐specific factors, and cross‐country differences.