U.S. Treasury Markets: The High-Frequency Evidence
Boston College – Carroll School of Management
Blue Mountain Credit Fund still in the red YTD; here are their biggest holdings
Queen’s University – Smith School of Business
July 1, 2014
Handbook of Fixed-Income Securities, First Edition. Edited by Pietro Veronesi. 2015 John Wiley Sons, Inc.
This paper reviews the existing empirical evidence on the time-series behavior of the U.S. Treasury markets at high frequency: daily and intra-day data. The use of high-frequency data in econometric analyses is a major recent development in the study of the fixed income markets: the response of prices to scheduled and unscheduled news, conditional-volatility dynamics, and jump and diffusion behavior, can all be examined much more precisely with high-frequency data. High-frequency data are also important for the characterization of the trading environment as they allow us to examine the immediate impact of trading on prices and how this impact is affected by the presence of macro news. Lastly, the presence and impact of high-frequency trading can only be studied by analyzing high-frequency data.
U.S. Treasury Markets: The High-Frequency Evidence – Introduction
This chapter reviews the existing empirical evidence on the time-series behavior of the U.S. Treasury markets at high frequency: daily and intra-day data. We believe that the use of high-frequency data in econometric analyses is a major recent development in the study of the fixed income markets, and has important implications for our understanding of how financial markets work. The response of prices to scheduled and unscheduled news, for example, can be examined much more precisely with high-frequency data, by isolating behavior within narrow windows surrounding the news releases. The instantaneous adjustment to news is what we would expect in a rational, frictionless market. If we were to detect a sluggish response to news, on the other hand, then we would conclude that behavioral effects and/or transaction costs and limits to arbitrage play an important role in these markets.
One can also take advantage of high-frequency data in the study of conditional-volatility dynamics, by relating volatility to macro news and intra-day seasonal patterns, and by constructing realized-volatility measures that approximate the true volatility process as sampling becomes more frequent. In addition, jump and diffusion behavior becomes easier to separate at high frequency.
High-frequency data are also important for the characterization of the trading environment. For example, researchers are able to investigate how liquidity changes during the trading day and around news releases. By using high-frequency data it is also possible to examine the immediate impact of trading on prices and how this impact is affected by the presence of macro news.
Moreover, bond risk premia can be better estimated using high-frequency data. It is possible to distinguish between days with and without macro news announcements, and, within announcement days, between volatile price behavior surrounding announcements and behavior further away from the announcements. This allows us to better understand the way bond risk premia are earned: e.g., the possible time-variation of conditional risk premia vs. the constant risk premia implied by the expectation hypothesis (EH), and the possible compensation for macro risks.
Lastly, the advent of high-frequency trading (HFT) in several markets—including the fixed income markets—has attracted a great deal of attention.2 By definition, the presence of HFT can only be identified by analyzing high-frequency data.
Indeed, several studies using high-frequency data for the U.S. Treasury markets have appeared during the last two decades and this is an ideal moment to review them. This is a selective review, though, which emphasizes what we think are the most important issues when looking at the Treasury markets through a “high-frequency lens.” Our up-front apology is offered to any researchers whose papers we have omitted. The U.S. Treasury market is one of the largest and most important financial markets in the world. Having a better understanding of how this market works is obviously important to practitioners–the main target audience of this review. Specifically, we believe that the studies reviewed in this chapter are relevant for the management, hedging, and pricing of Treasury securities and the many other instruments that are benchmarked against the Treasury yield curve, and also for trading and implementation strategies.
In our review, we start with motivating evidence on the behavior of the U.S. Treasury market during the recent financial crisis. We then focus on literature covering the following four topics: i) the reaction of prices and rates to macroeconomic news; ii) market micro-structure effects; iii) bond risk premia; and iv) the effects of high frequency trading.3;4 Each section concludes with a brief summary of the main results reviewed.
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