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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 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
. -- Diffusions ; integrated volatility ; realized volatility measures ; kernels ; microstructure noise ; conditional confidence …
Persistent link: https://www.econbiz.de/10009130720
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
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
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/10011916897
When analysing the volatility related to high frequency financial data, mostly non-parametric approaches based on realised or bipower variation are applied. This article instead starts from a continuous time diffusion model and derives a parametric analog at high frequency for it, allowing...
Persistent link: https://www.econbiz.de/10011374428
This paper introduces conformal inference, a powerful and flexible framework for constructing prediction intervals with guaranteed coverage in finite samples. Unlike conventional methods, conformal inference makes no assumptions about the underlying data distribution other than exchangeability....
Persistent link: https://www.econbiz.de/10015158178
Forecasting temperature in time and space is an important precondition for both the design of weather derivatives and the assessment of the hedging effectiveness of index based weather insurance. In this article, we show how this task can be accomplished by means of Kriging techniques. Moreover,...
Persistent link: https://www.econbiz.de/10010251600