Statistical Software for State Space Methods

In this paper we review the state space approach to time series analysis and establish the notation that is adopted in this special volume of the Journal of Statistical Software. We first provide some background on the history of state space methods for the analysis of time series. This is followed by a concise overview of linear Gaussian state space analysis including the modelling framework and appropriate estimation methods. We discuss the important class of unobserved component models which incorporate a trend, a seasonal, a cycle, and fixed explanatory and intervention variables for the univariate and multivariate analysis of time series. We continue the discussion by presenting methods for the computation of different estimates for the unobserved state vector: filtering, prediction, and smoothing. Estimation approaches for the other parameters in the model are also considered. Next, we discuss how the estimation procedures can be used for constructing confidence intervals, detecting outlier observations and structural breaks, and testing model assumptions of residual independence, homoscedasticity, and normality. We then show how ARIMA and ARIMA components models fit in the state space framework to time series analysis. We also provide a basic introduction for non-Gaussian state space models. Finally, we present an overview of the software tools currently available for the analysis of time series with state space methods as they are discussed in the other contributions to this special volume.

Modelling Round-the-Clock Price Discovery for Cross-Listed Stocks using State Space Methods

U.S. trading in non-U.S. stocks has grown dramatically. Round-the-clock, these stocks trade in the home market, in the U.S. market and, potentially, in both markets simultaneously. We develop a general methodology based on a state space model to study 24-hour price discovery in a multiple markets setting. As opposed to the standard variance ratio approach, this model deals naturally with (i) simultaneous quotes in an overlap, (ii) missing observations in a non-overlap, (iii) noise due to transitory microstructure effects, and (iv) contemporaneous correlation in returns due to market-wide factors. We provide an application of our model to Dutch-U.S. stocks. Our findings suggest a minor role for the NYSE in price discovery for Dutch shares, in spite of its non-trivial and growing market share. The results differ significantly from the variance ratio approach

Round-the-Clock Price Discovery for Cross-Listed Stocks: US-Dutch Evidence

U.S. trading in non-U.S. stocks has grown dramatically. Round-the-clock, these stocks trade in the home market, in the U.S. marketand, potentially, in both markets simultaneously. We use a state space model to study 24-hour price discovery. As opposed to thestandard variance ratio'' approach, this model deals naturally with (i) simultaneous quotes in an overlap, (ii) missing observations in anon-overlap, (iii) noise due to transitory microstructure effects, and (iv) contemporaneous correlation in returns due to market-widefactors. For NYSE-listed Dutch stocks, home market hours are a factor three more informative than U.S. market hours, which, inturn, are twice as informative as overnight hours. Surprisingly, strongest price discovery takes place in the NYSE preopening. Themodel shows results that are significantly different from the variance ratio approach

Extraction of level density and gamma strength function from primary gamma spectra

We present a new iterative procedure to extract the level density and the gamma strength function from primary gamma spectra for energies close up to the neutron binding energy. The procedure is tested on simulated spectra and on data from the Yb-173(He-3,alpha)Yb-172 reaction.Comment: 23 pages including 1 table and 7 figure

Gamma-widths, lifetimes and fluctuations in the nuclear quasi-continuum

Statistical $\gamma$-decay from highly excited states is determined by the nuclear level density (NLD) and the $\gamma$-ray strength function ($\gamma$SF). These average quantities have been measured for several nuclei using the Oslo method. For the first time, we exploit the NLD and $\gamma$SF to evaluate the $\gamma$-width in the energy region below the neutron binding energy, often called the quasi-continuum region. The lifetimes of states in the quasi-continuum are important benchmarks for a theoretical description of nuclear structure and dynamics at high temperature. The lifetimes may also have impact on reaction rates for the rapid neutron-capture process, now demonstrated to take place in neutron star mergers.Comment: CGS16, Shanghai 2017, Proceedings, 5 pages, 3 figure