An intraweek seasonality in the implied volatilities of T-bond and T-note options

Abstract

This paper initiates the study of intraweek seasonalities in the implied volatilities of options on futures contracts on U.S. Treasury bonds and notes. Research on intraweek regularities is important to public policy because the structure and usage of derivative markets is a regulatory issue. The topic is also important to discussions of market efficiency. For example, empirical observation of various trading regularities has stimulated research into market closing effects, weekend perturbations in discount rates, and patterns in news dissemination. Other theoretical topics which are stimulated by day-of-the-week research are models of bid-asked spreads (Roll [21]), trading concentration due to the interaction of liquidity and information traders (Admati and Pfleiderer [l]), and the role of noise and its effect on liquidity (Black [4]). Poole [20] and Eisemann and Timme [4] discuss the micro-mechanics of the Federal Reserve system and the Federal funds market. Stigum [23] and Melton [16] provide anecdotal evidence of high Friday and Wednesday volatility of the Federal funds rate. Dyl [7] concludes that Friday Federal funds rates are on average higher than other days. Spindt and Hoffmeister [22] explain how the mechanics of the Federal funds system lead to high variability of rates on Friday, especially on the second Friday of each reporting period. Findings of intraweek regularities have often been accompanied by analysis of particular institutional features or related anomalies (see, for example, PhillipsPatrick and Schneeweis [19] who relate high Monday dividends to the putative Monday effect in stocks, or Jaffe and Westerfield [12] who study the effects of currency seasonals and clearing procedures in the weekend effect context). A healthy skepticism should prevail in all discussions of intraweek regularities. Using a Bayesian approach, Connally [S] claims that most perceived anomalies of this type are due to incorrect hypothesis testing procedures, unduly large samples and historical accidents.