Browsing by Subject "Wavelet analysis"

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A mobile, scanning eye-safe lidar for the study of atmospheric aerosol particles and transport processes in the lower troposphere
(2009) Pal, Sandip; Wulfmeyer, Volker
A high-power eye-safe scanning aerosol lidar system in the ultraviolet wavelength region is introduced for the study of the optical properties of aerosol particles and transport processes in the atmosphere, especially in the atmospheric boundary layer (ABL). This system operates with an average power of 9 W in combination with a 40-cm scanner with a speed of up to 10° s-1. A modified version of the lidar inversion algorithm is developed for the retrieval of optical properties of aerosols from scanning lidar measurements. The lidar data can be analyzed with previously unachieved temporal and spatial resolution of 0.03 s and 3 m, respectively.
Bidirectional relationship between investor sentiment and excessreturns : new evidence from the wavelet perspective
(2015) Marczak, Martyna; Beißinger, Thomas
This paper sheds new light on the mutual relationship between investor sentiment and excess returns corresponding to the bubble component of stock prices. We propose to use the wavelet concept of the phase angle to determine the lead–lag relation between these variables. The wavelet phase angle allows for decoupling short– and long–run relations and is additionally capable of identifying time–varying comovement patterns. By applying this concept to excess returns of the monthly S&P500 index and two alternative monthly US sentiment indicators we find that in the short run (until 3 months) sentiment is leading returns whereas for periods above 3 months the opposite can be observed.
Four essays in the empirical analysis of business cycles and structural breaks
(2015) Marczak, Martyna; Beißinger, Thomas
Business cycle analysis has a long history in the macroeconomics literature and since its origins it poses a challenge for both empirical and theoretical research. The enduring interest in this research area is dictated by its high relevance for economic policy. Reliable information on the state of the economy plays a crucial role in the monitoring of the economy and in the policy-making process. This involves the choice of the method for extraction of a proper business cycle indicator. Moreover, the business cycle analyst also has to take account of structural breaks as well as seasonal and higher frequency movements of the series that can affect the properties of a business cycle indicator. Another reason for the keen interest in empirical business cycle research can be seen in the need to validate theoretical approaches. A prominent example is the debate on the cyclical behavior of real wages which evolved to one of the most lively and long--lasting debates in macroeconomics. This thesis tries to contribute to the literature under the aforementioned aspects. It offers a new methodological perspective with respect to the extraction of business cycles and detection of structural breaks. Furthermore, it sheds some light on the question of real wage cyclicality from the empirical point of view. The first essay proposes a new multivariate model based on a band-pass filter to construct business cycle indicators. Using this method and a dataset with monthly and quarterly US time series, two monthly business cycle indicators are obtained for the US. It is shown that the proposed method not only reproduces historical recessions very well, but it also performs good in terms of forecasting. The second essay for the first time in the literature combines indicator saturation as a general-to-specific approach to detect outliers and structural breaks with the structural time series model for the purpose of seasonal adjustment. The performance of the impulse-indicator and step-indicator saturation for detecting additive outliers and level shifts is tested in both a comprehensive Monte Carlo simulation exercise and an empirical application. The latter involves five European industrial production series. Its focus lies on the question whether the recessionary episode starting towards the end of 2008 can be described by the inherent model dynamics, or whether it represents a major structural change. In the third essay, stylized facts about the cyclicality of real consumer wages and real producer wages in Germany are established. First, various detrending methods are applied to estimate a business cycle and real wage cycles. The comovements between real wage cycles and the business cycle are then examined both in the time domain and in the frequency domain by resorting to the concept of the phase angle. According to the frequency domain results, the consumer real wage lags behind the business cycle. Moreover, it exhibits an anticyclical behavior in the short run, whereas in the longer run a procyclical behavior can be observed. For the producer real wage, in contrast, the results in the frequency domain are not clear-cut. The fourth essay compares the cyclical behavior of consumer and producer real wages in the USA and Germany. This study is the first one which employs wavelet analysis as a comovement tool in the context of the examined research question. From the findings of this study it can be inferred that the USA and Germany differ with respect to the lead-lag relationship of real wages and the business cycle. In the USA, both real wages are leading the business cycle in the entire time interval. The German consumer real wage is, on the other hand, lagging the business cycle. For the German producer real wage, the lead-lag pattern changes over time. In addition, the results show that real wages in the USA as well in Germany are procyclical or acyclical until 1980 and countercyclical thereafter.