OpenAlex · The Journal of Finance · 2004 · cites 391
ABSTRACT We examine the role of price discovery in the U.S. Treasury market through the empirical relationship between orderflow, liquidity, and the yield curve. We find that orderflow imbalances (excess buying or selling pressure) account for up to 26% of the day‐to‐day variation in yields on days without major macroeconomic announcements. The effect of orderflow on yields is permanent and strongest when liquidity i…
Michael W. Brandt, Kenneth A. Kavajecz
OpenAlex · European Finance Review · 2005 · cites 189
Abstract This paper examines the price differences between very liquid on-the-run U.S. Treasury securities and less liquid off-the-run securities over the on/off cycle. Comparing pairs of securities in time-series regressions allows us to disregard any fixed cross-sectional differences between securities. Also, since the liquidity of Treasury notes varies predictably over time, we can distinguish between current and …
David Goldreich, Bernd Hanke, Purnendu Nath
OpenAlex · Journal of Financial and Quantitative Analysis · 2010 · cites 174
Abstract In this paper, we identify jumps in U.S. Treasury-bond (T-bond) prices and investigate what causes such unexpected large price changes. In particular, we examine the relative importance of macroeconomic news announcements versus variation in market liquidity in explaining the observed jumps in the U.S. Treasury market. We show that while jumps occur mostly at prescheduled macroeconomic announcement times, an…
George J. Jiang, Ingrid Lo, Adrien Verdelhan
OpenAlex · Econstor (Econstor) · 2001 · cites 125
This paper examines a comprehensive set of liquidity measures for the U.S. Treasury market. The measures are analyzed relative to one another, across securities, and over time. I find highly significant price impact coefficients, such that a simple model that explains price changes with net order flow produces an R² statistic above 30 percent for the two-year note. The price impact coefficients are highly correlated …
Michael J. Fleming
OpenAlex · Speech · 2020 · cites 31
Remarks at Brookings-Chicago Booth Task Force on Financial Stability (TFFS) meeting, panel on market liquidity (delivered via videoconference).
Lorie Logan
OpenAlex · The Journal of Finance · 1999 · cites 728
The arrival of public information in the U.S. Treasury market sets off a two‐stage adjustment process for prices, trading volume, and bid‐ask spreads. In a brief first stage, the release of a major macroeconomic announcement induces a sharp and nearly instantaneous price change with a reduction in trading volume, demonstrating that price reactions to public information do not require trading. The spread widens dramat…
Michael J. Fleming, Eli M. Remolona
OpenAlex · The Quarterly Journal of Economics · 2015 · cites 893
Abstract The high-frequency trading arms race is a symptom of flawed market design. Instead of the continuous limit order book market design that is currently predominant, we argue that financial exchanges should use frequent batch auctions: uniform price double auctions conducted, for example, every tenth of a second. That is, time should be treated as discrete instead of continuous, and orders should be processed i…
Eric Budish, Peter Cramton, John J. Shim
arXiv · arXiv · 2026
This paper compares different methods for forecasting the term structure of U.S. and European zero-coupon government bonds using both traditional econometric and Machine Learning (ML) approaches. We compare classical models (e.g., Dynamic Nelson-Siegel (DNS) and Principal Component Analysis (PCA)) with different Neural Network (NN) architectures, including those inspired by the classical models, on the U.S. Treasury …
Tobias Lausser, Joao Eduardo Vuolo, Rudi Zagst
arXiv · arXiv · 2026
We address the problem of executing large client orders in continuous double-auction markets under time and liquidity constraints. We propose a model predictive control (MPC) framework that balances three competing objectives: order completion, market impact, and opportunity cost. Our algorithm is guided by a trading schedule (such as time-weighted average price or volume-weighted average price) but allows for deviat…
Thomas P. McAuliffe, Samuel Liew, Yuchao Li, Andrey Ushenin, Chihang Wang