Predicting stock realized variance based on an asymmetric robust regression approach
Year of publication: |
2023
|
---|---|
Authors: | Zhang, Yaojie ; He, Mengxi ; Zhao, Yuqi ; Hao, Xianfeng |
Subject: | asymmetric effect | heterogeneous autoregressive realized volatility | out-of-sample forecasting | robust regression model | stock market volatility | Volatilität | Volatility | Regressionsanalyse | Regression analysis | Prognoseverfahren | Forecasting model | Börsenkurs | Share price | Schätzung | Estimation | ARCH-Modell | ARCH model | Aktienmarkt | Stock market | Robustes Verfahren | Robust statistics | Theorie | Theory | Kapitaleinkommen | Capital income | Varianzanalyse | Analysis of variance | Zeitreihenanalyse | Time series analysis |
-
Forecasting European stock volatility : the role of the UK
Gao, Jun, (2023)
-
Paye, Bradley S., (2012)
-
Discrete-time volatility forecasting : a quantile regression approach
Oliveira, Víctor Henriques, (2020)
- More ...
-
Forecasting stock return volatility using a robust regression model
He, Mengxi, (2021)
-
Forecasting realized volatility of Chinese stock market : A simple but efficient truncated approach
Wen, Danyan, (2021)
-
Forecasting Bitcoin volatility : A new insight from the threshold regression model
Zhang, Yaojie, (2021)
- More ...