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Conditional variance forecasts for long-term stock returns

Mammen, Enno; Nielsen, Jens Perch; Scholz, Michael; … - In: Risks : open access journal 7 (2019) 4/113, pp. 1-22

of covariates as well as the smoothing parameters via cross-validation. We find that volatility forecastability is much …

Persistent link: https://www.econbiz.de/10012127861

A Mixed Frequency Stochastic Volatility Model for Intraday Stock Market Returns

Bekierman, Jeremias - 2019

We propose a mixed frequency stochastic volatility (MFSV) model for the dynamics of intraday asset return volatility …. In order to account for long-memory we separate stochastic daily and intraday volatility patterns by introducing a long …-run component that changes at daily frequency and a short-run component that captures the remaining intraday volatility dynamics. An …

Persistent link: https://www.econbiz.de/10012903646

The Impact of Derivatives on the Volatility of Turkish Stock Market

Cimen, Aysegul - 2019

impact of introduction of index futures and index options trading on the underlying spot market volatility are empirically … analysed. Conditional and unconditional volatility of Borsa Istanbul 30 Index is examined using GARCH model starting from its …

Persistent link: https://www.econbiz.de/10012891813

A latent dynamic factor approach to forecasting multivariate stock market volatility : conference paper

Gribisch, Bastian - 2013

This paper proposes a latent dynamic factor model for low- as well as high-dimensional realized covariance matrices of stock returns. The approach is based on the matrix logarithm and allows for flexible dynamic dependence patterns by combining common latent factors driven by HAR dynamics and...

Persistent link: https://www.econbiz.de/10010341025

High and low prices and the range in the European stock markets : a long-memory approach

Caporale, Guglielmo Maria; Gil-Alaña, Luis A.; Poza, Carlos - 2019

This paper uses fractional integration techniques to examine the stochastic behaviour of high and low stock prices in Europe and then to test for the possible existence of long-run linkages between them by looking at the range, i.e., the difference between the two logged series. Specifically,...

Persistent link: https://www.econbiz.de/10012022262

Stock Return Predictability in Frequency Domain

Kang, Jie; Jiang, Fuwei; Dai, Zhifeng - 2022

Using the long-term wavelet component of monthly S&P 500 excess returns as supervision information, we employ a machine learning method to extract the common predictive information of 14 prevalent macroeconomic variables, and construct a new macroeconomic index aligned for predicting stock...

Persistent link: https://www.econbiz.de/10014238602