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A predictive based regression algorithm for gene network selection

Gene selection has become a common task in most gene expression studies. The objective of such research is often to identify the smallest possible set of genes that can still achieve good predictive performance. To do so, many of the recently proposed classification methods require some form of dimension-reduction of the problem which finally provide a single model as an output and,…

Institution partenaire

Université de Genève

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English / 01/01/2016

Extreme Value Theory for Heavy-Tails in Electricity Prices

Typical characteristics of electricity day-ahead prices at EPEX are the very high volatility and a large number of extreme price changes. In this paper, we look at hourly spot prices at the German electricity market and apply extreme value theory (EVT) to investigate the tails of the price change distribution. Our results show the importance of delimiting price spikes and modeling…

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English / 29/06/2015

A spot-forward model for electricity prices with regime shifts

We propose a novel regime-switching approach for the simulation of electricity spot prices that is inspired by the class of fundamental models and takes into account the relation between spot and forward prices. Additionally the model is able to reproduce spikes and negative prices. Market prices are derived given an observed forward curve. We distinguish between a base regime and an…

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English / 20/02/2015

Time-frequency Granger causality with application to nonstationary brain signals

This PhD thesis concerns the modelling of time-varying causal relationships between two signals, with a focus on signals measuring neural activities. The ability to compute a dynamic and frequency-specific causality statistic in this context is essential and Granger causality provides a natural statistical tool. In Chapter 1 we propose a review of the existing methods allowing one to…

Institution partenaire

Université de Genève

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English / 01/01/2015

Robust Inference for Time Series Models: a Wavelet-Based Framework

We present a new framework for the robust estimation of time series models which is fairly general and, for example, covers models going from ARMA to state-space models. This approach provides estimators which are (i) consistent and asymptotically normally distributed, (ii) applicable to a broad spectrum of time series models, (iii) straightforward to implement and (iv)…

Institution partenaire

Université de Genève

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English / 01/01/2015

Simulation based bias correction methods for complex problems

Nowadays, the increase in data size and model complexity has led to increasingly difficult estimation problems. The numerical aspects of the estimation procedure can indeed be very challenging. To solve these estimation problems, approximate methods such as pseudo-likelihood functions or approximated estimating equations can be used as these methods are typically easier to implement…

Institution partenaire

Université de Genève

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English / 01/01/2015

Multivariate Dynamic Copula Models: Parameter Estimation and Forecast Evaluation

This paper introduces multivariate dynamic copula models to account for the time-varying dependence structure in asset portfolios. We firstly enhance the fexibility of this structure by modeling regimes with multivariate mixture copulas. In our second approach, we derive dynamic elliptical copulas by applying the dynamic conditional correlation model (DCC) to multivariate elliptical…

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English / 01/01/2015

Econometric Analysis of 15-Minute Intraday Electricity Prices

The trading activity in the German intraday electricity market has increased significantly over the last years. This is partially due to an increasing share of renewable energy, wind and photovoltaic, which requires power generators to balance out the forecasting errors in their production. We investigate the bidding behavior in the intraday market by looking at both last prices and…

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English / 01/01/2015

Prevalence and characteristics of addictive behaviors in a community sample: A latent class analysis

While addictions to substances such as alcohol, tobacco, and other drugs have been extensively investigated, interest has been growing in potential non-substance-related addictive behaviors (e.g., excessive gambling, buying or playing video games). In the current study, we sought to determine the prevalence and characteristics of a wide range of addictive behaviors in a general…

Institution partenaire

Université de Genève

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English / 01/01/2015

A spot-forward model for electricity prices

We propose a novel regime-switching approach for modeling electricity spot prices that takes into account the relation between spot and forward prices. Additionally the model is able to reproduce spikes and negative prices. Market prices are based on an observed forward curve. We distinguish between a base regime and an upper as well as a lower spike regime. The model parameters are…

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English / 15/07/2014

The impact of renewable energies on EEX day-ahead electricity prices

We analyze the impact of renewable energies, wind and photovoltaic, on the formation of day-ahead electricity prices at EEX. We give an overview of the policy decisions concerning the promotion of renewable energy sources in Germany, and discuss their consequences on day-ahead prices. An analysis of electricity spot prices reveals that the introduction of renewable energies enhances…

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English / 30/05/2014

Investors Behavior under Changing Market Volatility

This paper analyzes the reaction of the S&P 500 returns to changes in implied volatility given by the VIX index, using a daily data sample from 1990 to 2012. We found that in normal regimes increases (declines) in the expected market volatility result in lower (higher) subsequent stock market returns. Thus, investors enter into selling positions upon a perception of increased…

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English / 04/05/2014

Semiparametrically Efficient R-Estimation for Dynamic Location-Scale Models

We define rank-based estimators (R-estimators) for semiparametric time series models in whichthe conditional location and scale depend on a Euclidean parameter, while the innovation density isan infinite-dimensional nuisance. Applications include linear and nonlinear models, featuring eitherhomo- or heteroskedasticity (e.g. AR-ARCH and discretely observed diffusions with jumps). We…

Institution partenaire

Université de Genève

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English / 01/01/2014

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