161 research outputs found
A two-factor model for electricity prices with dynamic volatility
The wavelet transform is used to identify a biannual and an annual seasonality in the Phelix Day Peak and to separate the long-term trend from its short-term motion. The short-term/long-term model for commodity prices of Schwartz & Smith (2000) is applied but generalised to account for weekly periodicities and time-varying volatility. Eventually we find a bivariate SARMA-CCC-GARCH model to fit best. Moreover it surpasses the goodness of fit of an univariate GARCH model, which shows that the additional effort of dealing with a two-factor model is worthwile. --Wavelets,Seasonal Filter,Relative Wavelet Energy,Multivariate GARCH,Energy Price Modelling
Constructing a quasilinear moving average using the scaling function
The scaling function from multiresolution analysis can be used to constuct a smoothing tool in the context of time series analysis. We give a time series smoothing function for which we show the properties of a quasilinear moving average. Furthermore; we discuss its features and especially derive the distributional properties of our quasilinear moving average given some simple underlying stochastic processes. Eventually we compare it to existing smoothing methods in order to motivate its application --Scaling function,Quasilinear moving average,Influence function
Using wavelets for time series forecasting: Does it pay off?
By means of wavelet transform a time series can be decomposed into a time dependent sum of frequency components. As a result we are able to capture seasonalities with time-varying period and intensity, which nourishes the belief that incorporating the wavelet transform in existing forecasting methods can improve their quality. The article aims to verify this by comparing the power of classical and wavelet based techniques on the basis of four time series, each of them having individual characteristics. We find that wavelets do improve the forecasting quality. Depending on the data's characteristics and on the forecasting horizon we either favour a denoising step plus an ARIMA forecast or an multiscale wavelet decomposition plus an ARIMA forecast for each of the frequency components. --Forecasting,Wavelets,ARIMA,Denoising,Multiscale Analysis
Pricing an European gas storage facility using a continuous-time spot price model with GARCH diffusion
In this article we present both a theoretical framework and a solved example for pricing an European gas storage facility and computing the optimal strategy for its operation. As a representative price index we choose the Dutch TTF day-ahead gas price. We present statistical evidence that the volatility of this index is time-varying, so we introduce a new continuous-time model by incorporating GARCH diffusion into an Ornstein-Uhlenbeck process. Based on this price process we use dynamic programming methods to derive partial differential equations for pricing a storage facility. As an example we apply our methodology to a storage site located in Epe at the German-Dutch border. In this context we investigate the effects of multiple contract types, and perform a sensitivity analysis for all model parameters. We obtain a value surface displaying the properties of a financial straddle. Both volatility and mean reversion influence the facility value - but only around the long-run mean of the gas price. The terminal condition, which includes information about the contract provisions, is of importance if it contains e.g. penalty terms for low inventory levels. Otherwise its influence is diminishing for increasing lease periods. --TTF gas price,GARCH diffusion,natural gas storage,dynamic computing
Multivariate Copula Models at Work: Outperforming the desert island copula?
Since the pioneering work of Embrechts and co-authors in 1999, copula models enjoy steadily increasing popularity in finance. Whereas copulas are well-studied in the bivariate case, the higher-dimensional case still offers several open issues and it is by far not clear how to construct copulas which sufficiently capture the characteristics of financial returns. For this reason, elliptical copulas (i.e. Gaussian and Student-t copula) still dominate both empirical and practical applications. On the other hand, several attractive construction schemes appeared in the recent literature prom sing flexible but still manageable dependence models. The aim of this work is to empirically investigate whether these models are really capable to outperform its benchmark, i.e. the Student-t copula (which is termed by Paul Embrechts as "desert island copula" on account of its excellent fit to financial returns) and, in addition, to compare the fit of these different copula classes among themselves. --KS-copula,Hierarchical Archimedian,Product copulas,Pair-copula decomposition
LES study on the shape effect of ground obstacles on wake vortex dissipation
The lingering wake vortex following a landing aircraft has long been a hazard to aviation safety. Previous studies at the German Aerospace Center (DLR) confirmed the effectiveness of applying ground-based obstacles to improve the dissipation of the wake vortex pair by triggering the onset of the vortex bursting by the artificial introduction of shortwave instability. Following the design of the plate line obstacles as proposed by DLR for vortex dissipation, we further investigate the influence of the shape of the ground obstacles on dissipating wake vortex in the present work. The secondary vortex structure, resulting from the interaction between the vortical flow and the obstacle plate, stems from the location of the obstacle and travels outward along the vortex axis, thus spreading instability to the vortex structure along the way. 3D numerical simulations were conducted using Large Eddy Simulation with OpenFOAM solver
Inferring Proteolytic Processes from Mass Spectrometry Time Series Data Using Degradation Graphs
Background: Proteases play an essential part in a variety of biological
processes. Besides their importance under healthy conditions they are also
known to have a crucial role in complex diseases like cancer. In recent years,
it has been shown that not only the fragments produced by proteases but also
their dynamics, especially ex vivo, can serve as biomarkers. But so far, only
a few approaches were taken to explicitly model the dynamics of proteolysis in
the context of mass spectrometry. Results: We introduce a new concept to model
proteolytic processes, the degradation graph. The degradation graph is an
extension of the cleavage graph, a data structure to reconstruct and visualize
the proteolytic process. In contrast to previous approaches we extended the
model to incorporate endoproteolytic processes and present a method to
construct a degradation graph from mass spectrometry time series data. Based
on a degradation graph and the intensities extracted from the mass spectra it
is possible to estimate reaction rates of the underlying processes. We further
suggest a score to rate different degradation graphs in their ability to
explain the observed data. This score is used in an iterative heuristic to
improve the structure of the initially constructed degradation graph.
Conclusion: We show that the proposed method is able to recover all degraded
and generated peptides, the underlying reactions, and the reaction rates of
proteolytic processes based on mass spectrometry time series data. We use
simulated and real data to demonstrate that a given process can be
reconstructed even in the presence of extensive noise, isobaric signals and
false identifications. While the model is currently only validated on peptide
data it is also applicable to proteins, as long as the necessary time series
data can be produced
A Novel Approach to Generate Hourly Photovoltaic Power Scenarios
Photovoltaic power is playing an ever-increasing role in the energy mix of countries
worldwide. It is a stochastic energy source, and simulation models are needed to establish reliable risk
management. This paper presents a novel approach for simulating hourly solar irradiation andâas a
consequenceâphotovoltaic power based on easily accessible data such as wind, temperature, and
cloudiness. Solar simulations are generated via a multiplication factor that scales the maximum
possible solar irradiation. Photovoltaic simulations are then derived using formulas that approximate
the physical interdependencies. The resulting simulations are unbiased on an annual level and
reasonably reflect historic irradiation movements. Interpreting our approach as a descriptive model,
we find that error values vary over the year and with granularity. Errors are highest when considering
hourly values in wintertime, especially in the morning or late afternoon
The RWTH Aachen German and English LVCSR systems for IWSLT-2013
Abstract In this paper, German and English large vocabulary continuous speech recognition (LVCSR) systems developed by the RWTH Aachen University for the IWSLT-2013 evaluation campaign are presented. Good improvements are obtained with state-of-the-art monolingual and multilingual bottleneck features. In addition, an open vocabulary approach using morphemic sub-lexical units is investigated along with the language model adaptation for the German LVCSR. For both the languages, competitive WERs are achieved using system combination
Transforming Growth Factor β1 Oppositely Regulates the Hypertrophic and Contractile Response to β-Adrenergic Stimulation in the Heart
BACKGROUND: Neuroendocrine activation and local mediators such as transforming growth factor-βâ (TGF-βâ) contribute to the pathobiology of cardiac hypertrophy and failure, but the underlying mechanisms are incompletely understood. We aimed to characterize the functional network involving TGF-βâ, the renin-angiotensin system, and the β-adrenergic system in the heart. METHODS: Transgenic mice overexpressing TGF-βâ (TGF-βâ-Tg) were treated with a β-blocker, an ATâ-receptor antagonist, or a TGF-β-antagonist (sTGFβR-Fc), were morphologically characterized. Contractile function was assessed by dobutamine stress echocardiography in vivo and isolated myocytes in vitro. Functional alterations were related to regulators of cardiac energy metabolism. RESULTS: Compared to wild-type controls, TGF-βâ-Tg mice displayed an increased heart-to-body-weight ratio involving both fibrosis and myocyte hypertrophy. TGF-βâ overexpression increased the hypertrophic responsiveness to β-adrenergic stimulation. In contrast, the inotropic response to β-adrenergic stimulation was diminished in TGF-βâ-Tg mice, albeit unchanged basal contractility. Treatment with sTGF-βR-Fc completely prevented the cardiac phenotype in transgenic mice. Chronic β-blocker treatment also prevented hypertrophy and ANF induction by isoprenaline, and restored the inotropic response to β-adrenergic stimulation without affecting TGF-βâ levels, whereas ATâ-receptor blockade had no effect. The impaired contractile reserve in TGF-βâ-Tg mice was accompanied by an upregulation of mitochondrial uncoupling proteins (UCPs) which was reversed by β-adrenoceptor blockade. UCP-inhibition restored the contractile response to β-adrenoceptor stimulation in vitro and in vivo. Finally, cardiac TGF-βâ and UCP expression were elevated in heart failure in humans, and UCP--but not TGF-βâ--was downregulated by β-blocker treatment. CONCLUSIONS: Our data support the concept that TGF-βâ acts downstream of angiotensin II in cardiomyocytes, and furthermore, highlight the critical role of the β-adrenergic system in TGF-βâ-induced cardiac phenotype. Our data indicate for the first time, that TGF-βâ directly influences mitochondrial energy metabolism by regulating UCP3 expression. β-blockers may act beneficially by normalizing regulatory mechanisms of cellular hypertrophy and energy metabolism
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