Predicting expected idiosyncratic volatility : empirical evidence from ARFIMA, HAR, and EGARCH models
Year of publication: |
2024
|
---|---|
Authors: | Xiao, Chuxuan ; Huang, Winifred ; Newton, David P. |
Published in: |
Review of quantitative finance and accounting. - Dordrecht [u.a.] : Springer, ISSN 1573-7179, ZDB-ID 2009625-2. - Vol. 63.2024, 3, p. 979-1006
|
Subject: | ARFIMA | Asset Pricing | EGARCH | HAR | Idiosyncratic volatility | Time-varying | Volatilität | Volatility | Prognoseverfahren | Forecasting model | Börsenkurs | Share price | ARCH-Modell | ARCH model | Zeitreihenanalyse | Time series analysis | CAPM | ARMA-Modell | ARMA model | Schätzung | Estimation |
-
Forecasting global stock market implied volatility indices
Degiannakis, Stavros, (2018)
-
Stock index volatility forecasting with high frequency data
Hol Uspensky, Eugenie, (2002)
-
Improving variance forecasts : the role of Realized Variance features
Papantonis, Ioannis, (2023)
- More ...
-
Newton, David, (2022)
-
Application of option pricing theory to R&D
Newton, David P., (1992)
-
Market conventions vs. actuarial yields : implications for bond swapping
Newton, David P., (1992)
- More ...