Search Results
Working Paper
Price Discovery in the U.S. Treasury Cash Market: On Principal Trading Firms and Dealers
We explore the following question: does the trading activity of registered dealers on Treasury interdealer broker (IDB) platforms differ from that of principal trading firms (PTFs), and if so, how and to what effect on market liquidity? To do so, we use a novel dataset that combines Treasury cash transaction reports from FINRA’s Trade Reporting and Compliance Engine (TRACE) and publicly available limit order book data from BrokerTec. We find that trades conducted in a limit order book setting have high permanent price impact when a PTF is the passive party, playing the role of ...
Discussion Paper
Unlocking the Treasury Market through TRACE
This joint FEDS Note and Liberty Street Economics blog post from staff at the Board of Governors and Federal Reserve Bank of New York aims to share initial insights on the Treasury cash transactions data reported to Financial Industry Regulatory Authority (FINRA)'s Trade Reporting and Compliance Engine (TRACE).
Discussion Paper
Breaking Down TRACE Volumes Further
This joint FEDS Note and Liberty Street Economics blog post from staff at the Board of Governors and the Federal Reserve Bank of New York aims to share further initial insights on Treasury cash transactions reported in the Financial Industry Regulatory Authority (FINRA)’s Trace Reporting and Compliance Engine (TRACE).
Discussion Paper
Unlocking the Treasury Market through TRACE
The U.S. Treasury market is widely regarded as the deepest and most liquid securities market in the world, playing a critical role in the global economy and in the Federal Reserve’s implementation of monetary policy. Despite the Treasury market’s importance, the official sector has historically had limited access to information on cash market transactions. This data gap was most acutely demonstrated in the investigation of the October 15, 2014, flash event in the Treasury market, as highlighted in the Joint Staff Report (JSR). Following the JSR, steps were taken to improve regulators’ ...
Working Paper
Machine Learning, the Treasury Yield Curve and Recession Forecasting
We use machine learning methods to examine the power of Treasury term spreads and other financial market and macroeconomic variables to forecast US recessions, vis-à-vis probit regression. In particular we propose a novel strategy for conducting cross-validation on classifiers trained with macro/financial panel data of low frequency and compare the results to those obtained from standard k-folds cross-validation. Consistent with the existing literature we find that, in the time series setting, forecast accuracy estimates derived from k-folds are biased optimistically, and cross-validation ...