Price Movers on the Stock Exchange of Thailand: Evidence from a Fully Automated Order‐Driven Market

This study examines which trade sizes move stock prices on the Stock Exchange of Thailand (SET), a pure limit order market, over two distinct market conditions of bull and bear. Using intraday data, the study finds that large‐sized trades (i.e., those larger than the 75th percentile) account for a disproportionately large impact on changes in traded and quoted prices. The finding remains even after it has been subjected to a battery of robustness checks. In contrast, the results of studies conducted in the United States show that informed traders employ trade sizes falling between the 40th and 95th percentiles ( Barclay and Warner, 1993 ; Chakravarty, 2001 ). Our results support the hypothesis that informed traders in a pure limit order market, such as the SET, where there are no market makers, also use larger‐size trades than those employed by informed traders in the United States.     

The Halloween Effect in U.S. Sectors

U.S. stock market sectors and industries perform better during winter than summer from 1926 to 2006. In more than two-thirds of sectors and industries, the difference in summer and winter returns, known as the Halloween effect, is statistically significant. There are, however, large differences across sectors and industries. The effect is almost absent in sectors related to consumer consumption but is strong in production sectors. We find that neither liquidity changes nor well-known risk factors can explain the anomaly. We illustrate how the differences between sectors and industries can improve the risk-return tradeoff using sector rotation.     

The Other January Effect: Evidence against market efficiency?

The Other January Effect (OJE), which suggests positive (negative) equity market returns in January predict positive (negative) returns in the following 11 months of the year, underperforms a simple buy-and-hold strategy before and after risk-adjustment. Even the best modified OJE strategy, which benefits from several ex-post adjustments, does not generate statistically or economically significant excess returns. When the OJE is tested with a method that is consistent with investor experience it is clear the OJE is no more profitable than an 11-month strategy that uses November or December as the conditioning month.     

Transaction costs in an illiquid order‐driven market

Transaction costs in many international equity markets are much larger than those in the USA. This raises questions such as what trade size these reported trading costs relate to and whether investors can reduce trading costs by timing their trades. We show, using data from the order‐driven New Zealand market, that transaction costs are frequently lower for larger trades, particularly in small stocks, and investors are able to reduce costs by timing their transactions. While investors who require immediate execution incur transaction costs that are much higher than reported average costs, patient investors can trade at much better rates.     

Who knows more about future currency volatility?

We use four currency pairs from October 1, 2001 to September 29, 2006 to compare the predictive power of the implied volatility derived from currency option prices that are traded on the Philadelphia Stock Exchange (PHLX), Chicago Mercantile Exchange (CME), and over‐the‐counter market (OTC). Among the competing implied volatility forecasts, OTC‐implied volatility subsumes the information content of PHLX‐ and CME‐implied volatility. Consistent with extant studies our result also shows that the implied volatility provides more information about future volatility–regardless of whether it is from the OTC, PHLX, or CME markets–than time series based volatility. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 29:270–295, 2009