Suchergebnisse

Sometimes, it is of interest to single out the fluctuations associated to a given frequency. We propose a new variant of SSA, Circulant SSA (CiSSA), that allows to extract the signal associated to any frequency specified beforehand. This is a novelty when compared with other SSA procedures that need to identify ex-post the frequencies associated to the extracted signals. We prove that CiSSA is asymptotically equivalent to these alternative procedures although with the advantage of avoiding the need of the subsequent frequency identification. We check its good performance and compare it to alternative SSA methods through several simulations for linear and nonlinear time series. We also prove its validity in the nonstationary case. We apply CiSSA in two different fields to show how it works with real data and find that it behaves successfully in both applications. Finally, we compare the performance of CiSSA with other state of the art techniques used for nonlinear and nonstationary signals with amplitude and frequency varying in time. ; Financial support from the Spanish government, contract grants MINECO/FEDER ECO2015-70331-C2-1-R, ECO2015-66593-P, ECO2016-76818-C3-3-P, PID2019-107161GB-C32 and PID2019-108079GB-C22 is acknowledged.

Der Autor gibt einen Literaturüberblick zur Fisher-Gleichung, wonach die nominelle Nettoverzinsung der Steuern der Inflationserwartung plus der realen Verzinsung entspricht, und testet das Modell anhand brasilianischer Daten aus den Jahren 1973-1990. Er kommt zu dem Ergebnis, daß in Zeiten progressiver Inflation die Regierung die öffentliche Schuldenlast nicht durch Ausgabe indexierter Schuldverschreibungen abbauen kann. (DSE/DÜI)

The book provides deep insights into the signal extraction problem - especially at the boundary of a sample, where asymmetric filters must be used - and how to solve it optimally. The traditional model-based approach (TRAMO/SEATS or X-12-ARIMA) is an inefficient estimation method because it relies on one-step ahead forecasting performances (of a model) whereas the signal extraction problem implicitly requires good multi-step ahead forecasts also. Unit roots are important properties of the input signal because they generate a set of constraints for the best extraction filter. Since traditional tests essentially rely on one-step ahead forecasting performances, new tests are presented here which implicitly account for multi-step ahead forecasting performances too. The gain in efficiency obtained by the new estimation method is analyzed in great detail, using simulated data as well as 'real world" time series

Since the early 1980s, the debate surrounding speculative bubbles has never subsided. A key obstacle to resolving this issue is the identification problem. A bubble is usually inferred from some assumed fundamental determinants of a price. These assumptions could be oversimplified. Furthermore, there might be data measurement errors. This paper attempts to capture such errors with a latent state variable. This variable is extracted using the Kalman filter. Based on the empirical comparisons, it is found that it is possible to attribute the observed large price swings in the property market of Hong Kong during the 1980s and 1990s to a periodically collapsing rational speculative bubble.