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We propose a general class of Markov-switching-ARFIMA processes in order to combine strands of long memory and Markov-switching literature. Although the coverage of this class of models is broad, we show that these models can be easily estimated with the DLV algorithm proposed. This algorithm...
Persistent link: https://www.econbiz.de/10003633683
We introduce a new hybrid approach to joint estimation of Value at Risk (VaR) and Expected Shortfall (ES) for high quantiles of return distributions. We investigate the relative performance of VaR and ES models using daily returns for sixteen stock market indices (eight from developed and eight...
Persistent link: https://www.econbiz.de/10003891679
This paper studies the performance of nonparametric quantile regression as a tool to predict Value at Risk (VaR). The approach is flexible as it requires no assumptions on the form of return distributions. A monotonized double kernel local linear estimator is applied to estimate moderate (1%)...
Persistent link: https://www.econbiz.de/10003952845
Financial risk control has always been challenging and becomes now an even harder problem as joint extreme events occur more frequently. For decision makers and government regulators, it is therefore important to obtain accurate information on the interdependency of risk factors. Given a...
Persistent link: https://www.econbiz.de/10009425497
The present paper offers a careful description of empirical identification of possible multiple changes in regime. We apply recently developed tools designed to select between regime-switching models among a broad class of linear and nonlinear regression models and provide a discussion of the...
Persistent link: https://www.econbiz.de/10001685116
We demonstrate that the parameters controlling skewness and kurtosis in popular equity return models estimated at daily frequency can be obtained almost as precisely as if volatility is observable by simply incorporating the strong information content of realized volatility measures extracted...
Persistent link: https://www.econbiz.de/10013128339
This paper focuses on a number of newly proposed on-line forecast combination algorithms in Sancetta (2010), Yang (2004), and Wei and Yang (2012). We first establish certain asymptotic properties of these algorithms and compare them with the Bates and Granger (1969) method. We then show that...
Persistent link: https://www.econbiz.de/10013072496
Currently, the methods used by producers of official statistics do not facilitate the seasonal and calendar adjustment of daily time series, even though an increasing number of series with daily observations are available. The aim of this paper is the development of a procedure to estimate and...
Persistent link: https://www.econbiz.de/10012897682
Spot prices of electricity in liberalized markets feature seasonality, mean reversion, random short-term jumps, skewness and highly kurtosis, as a result from the interaction between the supply and demand and the physical restrictions for transportation and storage. To account for such stylized...
Persistent link: https://www.econbiz.de/10012858752
In this paper, we discuss and compare empirically various ways of computing multistep quantile forecasts of demand, with a special emphasis on the use of the quantile regression methodology. Such forecasts constitute a basis for production planning and inventory management in logistic systems...
Persistent link: https://www.econbiz.de/10012932647