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

Nominal interest rates and the news

How do interest rates react to news? This paper presents a new methodology, based on a simple dynamic term structure model, which provides for an integrated analysis of the effects of monetary policy actions and macroeconomic news on the term structure of interest rates. I find several new empirical results: First, monetary policy directly affects distant forward rates. Second, policy news is more complex than macro news. Third, while payroll news causes the most action in interest rates, it does not affect distant forward rates. Fourth, the term structure response to macro news is consistent with considerable interest rate smoothing.Interest rates ; Monetary policy

Evaluation of the TruNarc Handheld Narcotics Analyzer as a Pre-Analysis Screening Device for the Orange County Crime Lab

Forensic analysis of suspected narcotics is often dangerous as the substances’ composition is unknown. Many techniques for drug identification require handling of the substance outside of its packaging, which can expose the analyst to potentially harmful chemicals. The TruNarc Handheld Narcotics Analyzer is a portable Raman spectroscopy device that is non-destructive of evidence and can be used to screen drugs through simple packaging to minimize the risk of exposure. The Orange County Crime Lab (OCCL) is testing the limits of this device to determine if it can be used to screen new evidence within the Seized Drugs Lab. The OCCL has used this device on over 85 pieces of individual casework, which were then confirmed using gas chromatography and mass spectrometry (GC/MS). Methamphetamine, cocaine, and fentanyl in various forms such as powders, crystalline substances, and tablets, are all drugs we are optimistic that the TruNarc will be able to accurately identify in casework. We found that the three drugs of interest could be identified in most cases where substances were light in color, in powder or crystalline form, and in translucent plastic packaging. However, mixtures and tablets were difficult for the TruNarc to accurately identify. Further testing will be done to determine the lower limits of detection for drugs of interest before making a decision on implementing the device as a pre-analysis screening method in the laboratory and field settings

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

Evaluating Characteristics of De Novo Assembly Software on 454 Transcriptome Data: A Simulation Approach

Background: The quantity of transcriptome data is rapidly increasing for non-model organisms. As sequencing technology advances, focus shifts towards solving bioinformatic challenges, of which sequence read assembly is the first task. Recent studies have compared the performance of different software to establish a best practice for transcriptome assembly. Here, we adapted a simulation approach to evaluate specific features of assembly programs on 454 data. The novelty of our study is that the simulation allows us to calculate a model assembly as reference point for comparison. Findings: The simulation approach allows us to compare basic metrics of assemblies computed by different software applications (CAP3, MIRA, Newbler, and Oases) to a known optimal solution. We found MIRA and CAP3 are conservative in merging reads. This resulted in comparably high number of short contigs. In contrast, Newbler more readily merged reads into longer contigs, while Oases produced the overall shortest assembly. Due to the simulation approach, reads could be traced back to their correct placement within the transcriptome. Together with mapping reads onto the assembled contigs, we were able to evaluate ambiguity in the assemblies. This analysis further supported the conservative nature of MIRA and CAP3, which resulted in low proportions of chimeric contigs, but high redundancy. Newbler produced less redundancy, but the proportion of chimeric contigs was higher. Conclusion: Our evaluation of four assemblers suggested that MIRA and Newbler slightly outperformed the othe

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

Does voter polarisation induce party extremism? The moderating role of abstention

This article contributes to the literature on representation by examining how the ideological polarisation of the electorate affects parties’ programmatic positions in multiparty systems. The main argument is that parties face incentives to adopt more extreme positions when the electorate becomes more ideologically polarised and the share of non-moderate voters is higher. The reason is that by adopting moderate positions parties will prompt their non-moderate core constituents to sit out the election. This risk is conditioned by voters’ propensity to abstain. A higher (lower) propensity to abstain means that parties alienate a larger (smaller) share of their core constituents when adopting a moderate position. Parties therefore respond to greater voter polarisation by adopting more extreme positions, but the effect declines as voters’ propensity to abstain decreases. An empirical analysis of parties’ programmatic positions in 11 Western European countries between 1977 and 2016 strongly supports this expectation