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In this paper, we use factor-augmented HAR-type models to predict the daily integrated volatility of asset returns. Our approach is based on a proposed two-step dimension reduction procedure designed to extract latent common volatility factors from a large dimensional and high-frequency returns...
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This paper investigates the effect of characteristic-based time-varying factor beta on the diffusion-index type forecast. Specifically, the factor beta includes two distinct components: the "instrumental beta'' is a function of some observed stable variables, while the "idiosyncratic beta''...
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Numerous tests designed to detect realized jumps over a fixed time span have been proposed and extensively studied in the financial econometrics literature. These tests differ from “long time span tests” that detect jumps by examining the magnitude of the intensity parameter in the data...
Persistent link: https://www.econbiz.de/10012898873
Numerous tests designed to detect realized jumps over a fixed time span have been proposed and extensively studied in the financial econometrics literature. These tests differ from “long time span tests” that detect jumps by examining the magnitude of the jump intensity parameter in the data...
Persistent link: https://www.econbiz.de/10012025640
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The development of new tests and methods used in the evaluation of time series forecasts and forecasting models remains as important today as it has for the last 50 years. Paraphrasing what Sir Clive W.J. Granger (arguably the father of modern day time series forecasting) said in the 1990s at a...
Persistent link: https://www.econbiz.de/10012864375
In this paper, we introduce a class of multi-frequency financial and macroeconomic uncertainty measures. The factors are latent variables extracted from a state space model that includes multiple different frequencies of non-parametrically estimated components of quadratic variation, as well as...
Persistent link: https://www.econbiz.de/10013321464
In recent years, the field of financial econometrics has seen tremendous gains in the amount of data available for use in modeling and prediction. Much of this data is very high frequency, and even 'tick-based', and hence falls into the category of what might be termed big data. The availability...
Persistent link: https://www.econbiz.de/10012913503