Showing 1 - 10 of 24,394
The sum of squared intraday returns provides an unbiased and almost error-free measure of ex-post volatility. In this … paper we develop a nonlinear Autoregressive Fractionally Integrated Moving Average (ARFIMA) model for realized volatility …, which accommodates level shifts, day-of-the-week effects, leverage effects and volatility level effects. Applying the model …
Persistent link: https://www.econbiz.de/10011335205
In this study, we apply a rolling window approach to wavelet-filtered (denoised) S&P500 returns (2000–2020) to obtain time varying Hurst exponents. We analyse the dynamics of the Hurst exponents by applying statistical tests (e.g., for stationarity, Gaussianity and self-similarity), a...
Persistent link: https://www.econbiz.de/10013229642
model in several ways, it allows for all the primary stylized facts of financial asset returns, including volatility … volatility, but without the estimation problems associated with the latter, and being applicable in the multivariate setting for …
Persistent link: https://www.econbiz.de/10010256409
The empirical literature of stock market predictability mainly suffers from model uncertainty and parameter instability. To meet this challenge, we propose a novel approach that combines the documented merits of diffusion indices, regime-switching models, and forecast combination to predict the...
Persistent link: https://www.econbiz.de/10012416151
Forecasting-volatility models typically rely on either daily or high frequency (HF) data and the choice between these … two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer of many … forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the assumptions of jumping …
Persistent link: https://www.econbiz.de/10011730304
Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these … two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer from … these two family forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the …
Persistent link: https://www.econbiz.de/10011674479
Many recent modelling advances in finance topics ranging from the pricing of volatility-based derivative products to … number of recent papers have addressed volatility predictability, some from the perspective of the usefulness of jumps in … forecasting volatility. Key papers in this area include Andersen, Bollerslev, Diebold and Labys (2003), Corsi (2004), Andersen …
Persistent link: https://www.econbiz.de/10009771770
When estimating and forecasting realized volatility in the presence of jumps, a form of bias-variance tradeoff is …
Persistent link: https://www.econbiz.de/10014188741
We propose a new predictor - the innovation in the daily return minimum in the U.S. stock market () - for predicting international stock market returns. Using monthly data for a wide range of 17 MSCI international stock markets during the period spanning over half a century from January 1972 to...
Persistent link: https://www.econbiz.de/10015361591
Global financial markets frequently experience extreme volatility, which poses significant challenges in forecasting … especially challenging in China's A-share market, which is characterized by high volatility and active government involvement …
Persistent link: https://www.econbiz.de/10015413148