Trading Activity in the Treasury Futures Market and Its Role in Futures Price Fluctuations

Abstract

Chapter 1: Trading Treasury Futures: A Vector Autoregressive (VAR) Analysis on the Volume-Volatility RelationDoes trading by hedgers or speculators destabilize the Treasury futures market? And if it is the case, how do they destabilize the market? This is an empirical study on the volume-volatility relation which is central to the market microstructure literature. Vector autoregressive (VAR) analysis is conducted on the 2-, 5-, 10-, and 30-year Treasury futures contracts traded at the Chicago Board of Trade. With some mixed results, it can be roughly concluded that speculators destabilize the Treasury futures market, causing a more turbulent trading pattern as evident in the increased volatility. However, the same can not be said of hedgers; available evidence at best suggests a weak relation between hedging and a decreased price volatility (indicating a market being stabilized). To my knowledge, this study is the first in applying the VAR technique to the context of Treasury futures trading, and the first in comparing the three different volatility measures (intra-day, historical, and GARCH) simultaneously. In addition, GARCH volatility specifications are comprehensively tested and the commonly-used GARCH(1,1) is conveniently arrived at. It is also the first in examining the volume and open interest by constructing two different trading activity series (aggregate and active contract amounts) in the same study, and the results are compared. On the volume-volatility relation, it is among the few that have a specific focus on each individual contract instead of an all-as-one approach. The long period of data (from year 1991 to 2006) is applied to the VAR framework.Chapter 2: Volume and Volatility: The Relation, Two Models, and Regulating Market Squeezes of Treasury Futures TradingI review in Chapter 2 the classes of models in theorizing the volume-volatility relation. The strategic trading models of private information by Kyle (1985) and differences of opinion model of public information by Harris and Raviv (1993) are discussed. I propose that the differences of opinion model are more suitable for trading behavior in the Treasury futures market, since virtually all diligent analysts are exposed to the same set of public data (such as Federal Open Market Committee announcements, Fed watchers' studied guesses, or quarterly GDP growth rates and monthly nonfarm payrolls for general economic outlook), but they nonetheless infer their interest rate expectations with different interpretations of data. Unlike the cases in stock or corporate bond markets where differential accesses to private information are essential, differences in interpretation are more significant in Treasury futures trading and private information is less distinctive for individual contracts. The main predictions of the Harris and Raviv model are compared with my VAR results from Chapter 1; it is especially notable that the positively autocorrelated volume pattern is confirmed by the surprisingly strong VAR evidence. I then conclude with the recent episode (09/2006) of market squeeze warnings to Treasury primary dealers. Implications on Treasury futures trading in terms of regulating the market are discussed.