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2016 | OriginalPaper | Buchkapitel

Intraday Data vs Daily Data to Forecast Volatility in Financial Markets

verfasst von : António A. F. Santos

Erschienen in: Time Series Analysis and Forecasting

Verlag: Springer International Publishing

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Abstract

The measurement of the volatility is key in financial markets. It is well established in the literature that the evolution of the volatility can be forecasted. Recently, measures of volatility have been developed using intraday data, for example, the realized volatility. Here the forecasts of volatility are defined through the stochastic volatility model. After estimating the parameters through Bayesian estimation methods using Markov chain Monte Carlo, forecasts are obtained using particle filter methods. With intraday data additional information can help understanding better the evolution of the financial volatility. The aim is to build a more clear picture of the evolution of the volatility in financial markets through the comparison of volatility measures using daily observations and intraday data.

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Titel: Intraday Data vs Daily Data to Forecast Volatility in Financial Markets
verfasst von: António A. F. Santos
Verlag: Springer International Publishing
Buch: Time Series Analysis and Forecasting
Print ISBN: 978-3-319-28723-2

Electronic ISBN: 978-3-319-28725-6

Copyright-Jahr: 2016
DOI: https://doi.org/10.1007/978-3-319-28725-6_12

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