Another Look to the Price-Dividend Ratio: A Markov-Switching Approach

This paper analyzes the stationarity of this ratio in the context of a Markov-switching model à la Hamilton (1989) where an asymmetric speed of adjustment is introduced. This particular specification robustly supports a nonlinear reversion process and identifies two relevant episodes: the post-war period from the mid-50’s to the mid-70’s and the so called “90’s boom” period. A three-regime Markov-switching model displays the best regime identification and reveals that only the first part of the 90’s boom (1985-1995) and the post-war period are near-nonstationary states. Interestingly, the last part of the 90’s boom (1996-2000), characterized by a growing price-dividend ratio, is entirely attributed to a regime featuring a highly reverting process.

Markov Switching Risk Premium and the term structure of interest rates. Empirical evidence from US post-war interest rates

This paper considers the basic present value model of interest rates under rational expectations with two additional features. First, following McCallum (1994), the model assumes a policy reaction function where changes in the short-term interest rate are determined by the long-short spread. Second, the short-term interest rate and the risk premium processes are characterized by a Markov regime-switching model. Using US post-war interest rate data, this paper finds evidence that a two-regime switching model fits the data better than the basic model. The estimation results also show the presence of two alternative states displaying quite different features.

An Alternative View of the US Price-Dividend Ratio Dynamics

As a necessary condition for the validity of the present value model, the price-dividend ratio must be stationary. However, significant market episodes seem to provide evidence of prices significantly drifting apart from dividends while other episodes show prices anchoring back to dividends. This paper investigates the stationarity of this ratio in the context of a Markov- switching model à la Hamilton (1989) where an asymmetric speed of adjustment towards a unique attractor is introduced. A three-regime model displays the best regime identification and reveals that the first part of the 90’s boom (1985-1995) and the post-war period are characterized by a stationary state featuring a slow reverting process to a relatively high attractor. Interestingly, the latter part of the 90’s boom (1996-2000), characterized by a growing price-dividend ratio, is entirely attributed to a stationary regime featuring a highly reverting process to the attractor. Finally, the post-Lehman Brothers episode of the subprime crisis can be classified into a temporary nonstationary regime.

Switching Regimes in the Term Structure of Interest Rates During U.S. Post-War: A case for the Lucas proof equilibrium?

Published as an article in: Studies in Nonlinear Dynamics & Econometrics, 2004, vol. 8, issue 1, pages 5.

New methods for generating populations in Markov network based EDAs: Decimation strategies and model-based template recombination

Methods for generating a new population are a fundamental component of estimation of distribution algorithms (EDAs). They serve to transfer the information contained in the probabilistic model to the new generated population. In EDAs based on Markov networks, methods for generating new populations usually discard information contained in the model to gain in efficiency. Other methods like Gibbs sampling use information about all interactions in the model but are computationally very costly. In this paper we propose new methods for generating new solutions in EDAs based on Markov networks. We introduce approaches based on inference methods for computing the most probable configurations and model-based template recombination. We show that the application of different variants of inference methods can increase the EDAs’ convergence rate and reduce the number of function evaluations needed to find the optimum of binary and non-binary discrete functions.

Dialog Systems based on Markov decision processes over two real tasks

In this work the state of the art of the automatic dialogue strategy management using Markov decision processes (MDP) with reinforcement learning (RL) is described. Partially observable Markov decision processes (POMDP) are also described. To test the validity of these methods, two spoken dialogue systems have been developed. The first one is a spoken dialogue system for weather forecast providing, and the second one is a more complex system for train information. With the first system, comparisons between a rule-based system and an automatically trained system have been done, using a real corpus to train the automatic strategy. In the second system, the scalability of these methods when used in larger systems has been tested.

Code-switching, Metalinguistics, and Translation in a Bilingual/Bicultural Novel: Sandra Cisneros' Caramelo or Puro Cuento

Raquel Merino Álvarez, José Miguel Santamaría, Eterio Pajares (eds.)

Two-magnon bound state causes ultrafast thermally induced magnetisation switching

There has been much interest recently in the discovery of thermally induced magnetisation switching using femtosecond laser excitation, where a ferrimagnetic system can be switched deterministically without an applied magnetic field. Experimental results suggest that the reversal occurs due to intrinsic material properties, but so far the microscopic mechanism responsible for reversal has not been identified. Using computational and analytic methods we show that the switching is caused by the excitation of two-magnon bound states, the properties of which are dependent on material factors. This discovery allows us to accurately predict the onset of switching and the identification of this mechanism will allow new classes of materials to be identified or designed for memory devices in the THz regime.

Exchange biased FeNi/FeMn bilayers with coercivity and switching field enhanced by FeMn surface oxidation

FeNi/FeMn bilayers were grown in a magnetic field and subjected to heat treatments at temperatures of 50 to 350 degrees C in vacuum or in a gas mixture containing oxygen. In the as-deposited state, the hysteresis loop of 30 nm FeNi layer was shifted. Low temperature annealing leads to a decrease of the exchange bias field. Heat treatments at higher temperatures in gas mixture result in partial oxidation of 20 nm thick FeMn layer leading to a nonlinear dependence of coercivity and a switching field of FeNi layer on annealing temperature. The maximum of coercivity and switching field were observed after annealing at 300 degrees C.

Design and evaluation of an optical switching node

[EN]For a good development of elastic optical networks, the design of flexible optical switching nodes is required. This work analyses the previously proposed flexible architectures and, based on the most appropriate, which is the Architecture on Demand (AoD), proposes a specific configuration of the node that includes spatial and spectral switching and the wavelength conversion functionality with a low blocking probability and the minimum amount of modules; the characteristics of the traffic that the designed node is able to cope with are specified in the last chapter. An evaluation of the designed node is also done, and, compared to the other architectures, it is shown that the Architecture on Demand gives better results than others and that it has a higher potential for future developments.