Term premia and the news

How do monetary policy expectations and term premia respond to news? This paper provides new answers to this question by means of a dynamic term structure model (DTSM) in which risk prices are restricted. This leads to more precise and more reliable estimates of expectations and term premium components. I provide a new econometric framework for DTSM estimation that allows the researcher to select plausible constraints from a large set of restrictions, to correctly quantify statistical uncertainty, and to incorporate model uncertainty in the inference about risk pricing. The main empirical result is that under the restrictions favored by the data the expectations component, and not the term premium, accounts for the majority of high-frequency movements of long-term interest rates and for essentially all of their procyclical response to macroeconomic news. At both high and low frequencies, term premia are more stable than implied by a DTSM with unconstrained risk prices. The apparent disconnect between long-term rates and policy rates that has puzzled macroeconomists for some time is resolved by appropriately restricting the risk adjustment in models for bond pricing.Bonds - Prices ; Interest rates

The signaling channel for Federal Reserve bond purchases

Previous research has emphasized the portfolio balance effects of Federal Reserve bond purchases, in which a reduced bond supply lowers term premia. In contrast, we find that such purchases have important signaling effects that lower expected future short term interest rates. Our evidence comes from dynamic term structure models that decompose declines in yields following Fed announcements into changes in risk premia and expected short rates. To overcome problems in measuring term premia, we consider unbiased model estimation and restricted risk price estimation. We also characterize the estimation uncertainty regarding the relative importance of the signaling and portfolio balance channels.Monetary policy ; Interest rates ; Bond market

Unbiased estimate of dynamic term structure models

Affine dynamic term structure models (DTSMs) are the standard finance representation of the yield curve. However, the literature on DTSMs has ignored the coefficient bias that plagues estimated autoregressive models of persistent time series. We introduce new simulation-based methods for reducing or even eliminating small-sample bias in empirical affine Gaussian DTSMs. With these methods, we show that conventional estimates of DTSM coefficients are severely biased, which results in misleading estimates of expected future short-term interest rates and long-maturity term premia. Our unbiased DTSM estimates imply risk-neutral rates and term premia that are more plausible from a macro-finance perspective.Interest rates

Robust Bond Risk Premia

A consensus has recently emerged that a number of variables in addition to the level, slope, and curvature of the term structure can help predict interest rates and excess bond returns. We demonstrate that the statistical tests that have been used to support this conclusion are subject to very large size distortions from a previously unrecognized problem arising from highly persistent regressors and correlation between the true predictors and lags of the dependent variable. We revisit the evidence using tests that are robust to this problem and conclude that the current consensus is wrong. Only the level and the slope of the yield curve are robust predictors of excess bond returns, and there is no robust and convincing evidence for unspanned macro risk

One-Component Order Parameter in URu2_2Si2_2 Uncovered by Resonant Ultrasound Spectroscopy and Machine Learning

The unusual correlated state that emerges in URu$_2$Si$_2$ below T$_{HO}$ = 17.5 K is known as "hidden order" because even basic characteristics of the order parameter, such as its dimensionality (whether it has one component or two), are "hidden". We use resonant ultrasound spectroscopy to measure the symmetry-resolved elastic anomalies across T$_{HO}$. We observe no anomalies in the shear elastic moduli, providing strong thermodynamic evidence for a one-component order parameter. We develop a machine learning framework that reaches this conclusion directly from the raw data, even in a crystal that is too small for traditional resonant ultrasound. Our result rules out a broad class of theories of hidden order based on two-component order parameters, and constrains the nature of the fluctuations from which unconventional superconductivity emerges at lower temperature. Our machine learning framework is a powerful new tool for classifying the ubiquitous competing orders in correlated electron systems

Efficiency of a Brownian information machine

A Brownian information machine extracts work from a heat bath through a feedback process that exploits the information acquired in a measurement. For the paradigmatic case of a particle trapped in a harmonic potential, we determine how power and efficiency for two variants of such a machine operating cyclically depend on the cycle time and the precision of the positional measurements. Controlling only the center of the trap leads to a machine that has zero efficiency at maximum power whereas additional optimal control of the stiffness of the trap leads to an efficiency bounded between 1/2, which holds for maximum power, and 1 reached even for finite cycle time in the limit of perfect measurements.Comment: 9 pages, 2 figure

Reducing theoretical uncertainties in mb and lambda1

We calculate general moments of the lepton energy spectrum in inclusive semileptonic B -> X_c l \nu decay. Moments which allow the determination of mb^{1S} and lambda1 with theoretical uncertainties Delta(mb^{1S}) ~ 0.04 GeV and Delta(lambda1) ~ 0.05 GeV^2 are presented. The short distance 1S mass is used to extract a mass parameter free of renormalon ambiguities. Moments which are insensitive to mb and lambda1 and therefore test the size of the 1/mb^3 matrix elements and the validity of the OPE are also presented. Finally, we give an expression for the total branching ratio with a lower cut on the lepton energy, which allows one to eliminate a source of model dependence in current determinations of |Vcb| from B -> X_c l \nu decay.Comment: 8 pages, one figur

Broadband Observations of the Compton-thick Nucleus of NGC 3393

We present new NuSTAR and Chandra observations of NGC 3393, a galaxy reported to host the smallest separation dual AGN resolved in the X-rays. While past results suggested a 150 pc separation dual AGN, three times deeper Chandra imaging, combined with adaptive optics and radio imaging suggest a single, heavily obscured, radio-bright AGN. Using VLA and VLBA data, we find an AGN with a two-sided jet rather than a dual AGN and that the hard X-ray, UV, optical, NIR, and radio emission are all from a single point source with a radius <0.2". We find that the previously reported dual AGN is most likely a spurious detection resulting from the low number of X-ray counts (<160) at 6-7 keV and Gaussian smoothing of the data on scales much smaller than the PSF (0.25" vs. 0.80" FWHM). We show that statistical noise in a single Chandra PSF generates spurious dual peaks of the same separation (0.55$\pm$0.07" vs. 0.6") and flux ratio (39$\pm$9% vs. 32% of counts) as the purported dual AGN. With NuSTAR, we measure a Compton-thick source (NH=$2.2\pm0.4\times10^{24}$ cm$^{-2}$) with a large torus half-opening angle, {\theta}=79 which we postulate results from feedback from strong radio jets. This AGN shows a 2-10 keV intrinsic to observed flux ratio of 150. Using simulations, we find that even the deepest Chandra observations would severely underestimate the intrinsic luminosity of NGC 3393 above z>0.2, but would detect an unobscured AGN of this luminosity out to high redshift (z=5).Comment: Accepted for publication in ApJ. 15 Figures and 4 table

Probing the Complex and Variable X-ray Absorption of Markarian 6 with XMM-Newton

We report on an X-ray observation of the Seyfert 1.5 galaxy Mrk 6 obtained with the EPIC instruments onboard XMM-Newton. Archival BeppoSAX PDS data from 18-120 keV were also used to constrain the underlying hard power-law continuum. The results from our spectral analyses generally favor a double partial-covering model, although other spectral models such as absorption by a mixture of partially ionized and neutral gas cannot be firmly ruled out. Our best-fitting model consists of a power law with a photon index of 1.81+/-0.20 and partial covering with large column densities up to 10^{23} cm**-2. We also detect a narrow emission line consistent with Fe Kalpha fluorescence at 6.45+/-0.04 keV with an equivalent width of ~93+/-25 eV. Joint analyses of XMM-Newton, ASCA, and BeppoSAX data further provide evidence for both spectral variability (a factor of ~2 change in absorbing column) and absorption-corrected flux variations (by ~60%) during the ~4 year period probed by the observations.Comment: 7 pages, 2 figures. accepted for publication in the Astronomical Journa

B decay shape variables and the precision determination of |Vcb| and mb

We present expressions for shape variables of B decay distributions in several different mass schemes, to order $\alpha_s^2\beta_0$ and (Lambda_{QCD}/mb)^3. Such observables are sensitive to the b quark mass and matrix elements in the heavy quark effective theory, and recent measurements allow precision determinations of some of these parameters. We perform a combined fit to recent experimental results from CLEO, BABAR, and DELPHI, and discuss the theoretical uncertainties due to nonperturbative and perturbative effects. We discuss the possible discrepancy between the OPE prediction, recent BABAR results and the measured branching fraction to D and D* states. We find |Vcb| = (40.8 +- 0.9) x 10^{-3} and mb^{1S} = 4.74 +- 0.10 GeV, where the errors are dominated by experimental uncertainties.Comment: 23 pages, 3 figures, Version to appear in PR