We consider a d-dimensional continuous martingale X(t) with quadratic variation matrix ⟨ X⟩_t=∫_0^t Σ(s) ds and develop tests for the rank of its spot covariance matrix Σ(t), t∈[0,1]. The process X is observed under observational noise, as is standard for microstructure noise models in high-frequency finance. We test the null hypothesis ℋ_0:rank(Σ(t))≤ r against local alternatives ℋ_1,n:λ_r+1(Σ(t))≥ v_n, where λ_r+1 denotes the (r+1)st eigenvalue and v_n↓ 0 as the sample size n→∞. We construct test statistics based on eigenvalues of carefully calibrated localized spectral covariance matrix estimates. Critical values are provided non-asymptotically as well as asymptotically via maximal eigenvalues of Gaussian orthogonal ensembles. The power analysis establishes asymptotic consistency for a separation rate v_n (_r^-1/(β+1)n^-β/(β+1))∧ n^-β/(β+2), depending on the Hölder-regularity β of Σ and a possible spectral gap _r≥ 0 under ℋ_0. A lower bound shows the optimality of this rate. We discuss why the rate is much faster than conventional estimation rates. The theory is illustrated by simulations and a real data example with German government bonds of varying maturity.

This paper develops high-frequency econometric methods to test for jumps in the spread of bond yields. We derive a coherent inference procedure that detects a jump in the yield spread only if at least one of the two underlying bonds displays a jump. We formalize the test as a sequential procedure in the context of an intersection union test in multiple testing and introduce a new bivariate jump test for pre-averaged intra-day returns. In an empirical application involving high-frequency data of U.S. government bonds, we contrast response patterns of term spreads and break-even in ation across monetary policy announcements, in ation, and employment news releases.

We study the rank of the instantaneous or spot covariance matrix $\Sigma_X(t)$ of a multidimensional continuous semi-martingale $X(t)$. Given high-frequency observations $X(i/n)$, $i=0,\ldots,n$, we test the null hypothesis $rank(\Sigma_X(t))\le r$ for all $t$ against local alternatives where the average $(r+1)$st eigenvalue is larger than some signal detection rate $v_n$. A major problem is that the inherent averaging in local covariance statistics produces a bias that distorts the rank statistics. We show that the bias depends on the regularity and a spectral gap of $\Sigma_X(t)$. We establish explicit matrix perturbation and concentration results that provide non-asymptotic uniform critical values and optimal signal detection rates $v_n$. This leads to a rank estimation method via sequential testing. For a class of stochastic volatility models, we determine data-driven critical values via normed p-variations of estimated local covariance matrices. The methods are illustrated by simulations and an application to high-frequency data of U.S. government bonds.

This paper develops a two-step inference procedure to test for a local one-for-one relation of contemporaneous jumps in high-frequency financial data corrupted by market microstructure noise. The first step develops a new bivariate Lee-Mykland jump test for pre-averaged, intra-day returns. If a jump is detected in at least one of the two assets, then the second step tests for equal jump sizes. We apply the test procedure to pairs of nominal and inflation-indexed government bond yields at monetary policy announcements in the U.S., U.K., and Euro Area. The analysis provides new high-frequency evidence about the anchoring of inflation expectations and central banks' ability to push a measure of inflation expectations towards their inflation target.

An extensive empirical literature documents a generally negative correlation, named the "leverage effect," between asset returns and changes of volatility. It is more challenging to establish such a return-volatility relationship for jumps in high-frequency data. We propose new nonparametric methods to assess and test for a discontinuous leverage effect --- i.e. a relation between contemporaneous jumps in prices and volatility. The methods are robust to market microstructure noise and build on a newly developed price-jump localization and estimation procedure. Our empirical investigation of six years of transaction data from 320 NASDAQ firms displays no unconditional negative correlation between price and volatility cojumps. We show, however, that there is a strong relation between price-volatility cojumps if one conditions on the sign of price jumps and whether the price jumps are market-wide or idiosyncratic. Firms' volatility levels strongly explain the cross-section of discontinuous leverage while debt-to-equity ratios have no significant explanatory power.

We introduce a statistical test for simultaneous jumps in the price of a financial asset and its volatility process. The proposed test is based on high-frequency data and is robust to market microstructure frictions. For the test, local estimators of volatility jumps at price jump arrival times are designed using a nonparametric spectral estimator of the spot volatility process. A simulation study and an empirical example with NASDAQ order book data demonstrate the practicability of the proposed methods and highlight the important role played by price volatility co-jumps.

The publication of a projected path of future policy decisions by central banks is a controversially debated method to improve monetary policy guidance. The paper proposes a new approach to evaluate the effect of the guidance strategy on the predictability of monetary policy. The empirical investigation is based on jump probabilities of Norwegian interest rates on announcement days of the Norges Bank before and after the introduction of quantitative guidance. Within the standard semimartingale framework, we propose a new methodology to detect jumps. We derive a representation of the quadratic variation in terms of a wavelet spectrum. An adaptive threshold procedure on wavelet spectrum estimates aims at localizing jumps. Our main empirical result indicates that quantitative guidance significantly improves the predictability of monetary policy.

The publication of a projected path of future policy decisions by central banks is a controversially debated method to improve monetary policy guidance. The paper proposes a new approach to evaluate the effect of the guidance strategy on the predictability of monetary policy. The empirical investigation is based on jump probabilities of Norwegian interest rates on announcement days of the Norges Bank before and after the introduction of quantitative guidance. Within the standard semimartingale framework, we propose a new methodology to detect jumps. We derive a representation of the quadratic variation in terms of a wavelet spectrum. An adaptive threshold procedure on wavelet spectrum estimates aims at localizing jumps. Our main empirical result indicates that quantitative guidance significantly improves the predictability of monetary policy.

To what extent are US and Euro Area (EA) inflation expectations determined by foreign shocks? How do transmissions change during the great recession and European sovereign debt crisis? We address these questions with a flexible structural VAR model of weekly financial markets’ inflation expectations and an index of commodity futures. For the identification of the model, we exploit the heteroscedasticity of the data. We propose instrument-type regressions to uncover the economic nature and origin of identified shocks. In line with the discussion about global inflation, we find that inflation expectations can be labeled global over short expectations horizons but local at long horizons. While large US macro shocks explain the strong drop in US and EA inflation expectations during the great recession, expectations shocks are the important driver from 2009 on.

This paper proposes a new econometric approach to disentangle two distinct response patterns of the yield curve to monetary policy announcements. Based on cojumps in intraday tick-data of a short and long term interest rate, we develop a day-wise test that detects the occurrence of a significant policy surprise and identifies the market perceived source of the surprise. The new test is applied to 133 policy announcements of the European Central Bank (ECB) in the period from 2001-2012. Our main findings indicate a good predictability of ECB policy decisions and remarkably stable perceptions about the ECB’s policy preferences.

This paper extends the discussion of international comovements of actual inflation rates to inflation expectations. Financial market expectations about inflation rates in the United States (US) and Euro Area (EA) are modeled in a structural vector autoregression (SVAR). We demonstrate how the heteroscedasticity of the expectations data enables a flexible and data-driven statistical identification of the model. A multi-step procedure is proposed to explore the economic nature and geographical source of structural shocks. We emphasize the SVAR s ability to derive shocks that disentangle US specific, EA specific and global components. Our main empirical finding indicates that so-called global inflation translates to short horizon inflation expectations. In contrast, long expectations horizons are mostly driven by domestic shocks, thus, appear rather local. Results support the view of credible monetary policy strategies that anchor inflation expectations.

We establish estimation methods to determine co-jumps in multivariate high-frequency data with non-synchronous observations and market microstructure. A rate-optimal estimator of the entire quadratic covariation of an Itô-semimartingale is constructed by a locally adaptive spectral approach. Thresholding allows to disentangle the co-jump from the continuous part. We derive a feasible limit theorem for a truncated estimator of integrated covolatility which facilitates asymptotically efficient (co-)volatility estimation in the presence of jumps. A test for common jumps is presented. Simulations and an empirical application to intra-day tick-data from EUREX futures demonstrate the practical value of the approach.

This paper proposes a new approach to assess the degree of anchoring of inflation expectations. We extend the static setup of the predominant news regressions by introducing exponential smooth transition autoregressive dynamics. Our approach provides estimates of a market-perceived inflation target as well as the strength of the anchor that holds expectations at that target. A cross-country study based on a new data set of daily break-even inflation rates for the US, EMU, UK and Sweden shows that the degree of anchoring varies substantially across countries and expectations horizons.

We quantify spillovers of inflation expectations between the United States (US) and Euro Area (EA) based on break-even inflation (BEI) rates. In contrast to previous studies, we model US and EA BEI rates jointly in a structural vector autoregressive (SVAR) model. The SVAR approach allows to identify US and EA specific inflation expectations shocks. By modeling the heteroscedasticity of the data, we are able to test the identifying restrictions of structural shocks and analyze time-varying spillovers. Adjusted for BEI risk premia, our main result suggests that spillovers of inflation expectations increase during times of macroeconomic stress. We document a significant impact of the European sovereign debt crisis on US expectations. The finding contributes to the discussion about a weakening of inflation control by national central banks and speaks in favor of internationally coordinated policy actions, especially during crisis times.

We quantify spillovers of inflation expectations between the United States (US) and Euro Area (EA) based on break-even inflation (BEI) rates. In contrast to previous studies, we model US and EA BEI rates jointly in a structural vector autoregressive (SVAR) model. The SVAR approach allows to identify US and EA specific inflation expectations shocks. By modeling the heteroscedasticity of the data, we are able to test the identifying restrictions of structural shocks and analyze time-varying spillovers. Adjusted for BEI risk premia, our main result suggests that spillovers of inflation expectations increase during times of macroeconomic stress. We document a significant impact of the European sovereign debt crisis on US expectations. The finding contributes to the discussion about a weakening of inflation control by national central banks and speaks in favor of internationally coordinated policy actions, especially during crisis times.

This paper investigates the information content of the Norges Bank’s key rate projections. Wavelet spectrum estimates provide the basis for estimating jump probabilities of short- and long-term interest rates on monetary policy announcement days before and after the introduction of key rate projections. The behavior of short-term interest rates reveals that key rate projections have only little effects on market’s forecasting ability of current target rate changes. In contrast, longer-term interest rates indicate that the announcement of key rate projections has significantly reduced market participants’ revisions of the expected future policy path. Therefore, the announcement of key rate projections further improves central bank communication.