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Two volatility forecasting evaluation measures are considered; the squared one-day ahead forecast error and its … standardized version. The mean squared forecast error is the widely accepted evaluation function for the realized volatility … forecasting accuracy. Additionally, we explore the forecasting accuracy based on the squared distance of the forecast error …
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Measuring economic activity in real-time is a crucial issue in applied research and in the decision-making process of policy makers; however, it also poses intricate challenges to statistical filtering methods that are built to operate optimally under the auspices of an infinite number of...
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In this paper, we consider a stochastic asset price model where the trend is an unobservable Ornstein Uhlenbeck process. We first review some classical results from Kalman filtering. Expectedly, the choice of the parameters is crucial to put it into practice. For this purpose, we obtain the...
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We propose a novel and numerically efficient quantification approach to forecast uncertainty of the real price of oil …, estimation of time-varying forecast biases and facets of miscalibration of individual forecast densities and time-varying inter …-varying forecast uncertainty and risk for the real price of oil over the period 1974-2018. We show that the combination approach …
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We propose a novel and numerically efficient quantification approach to forecast uncertainty of the real price of oil …, estimation of time-varying forecast biases and facets of miscalibration of individual forecast densities and time-varying inter …-varying forecast uncertainty and risk for the real price of oil over the period 1974-2018. We show that the combination approach …
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