Drivers of Realized Volatility for Emerging Countries with a Focus on South Africa: Fundamentals versus Sentiment
We use a quantile machine learning (random forests) approach to analyse the predictive ability of newspapers-based macroeconomic attention indexes (MAIs) on eight major fundamentals of the United States on the realized volatility of a major commodity-exporting emerging stock market, namely South Afr...
Main Authors: | Rangan Gupta, Jacobus Nel, Christian Pierdzioch |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-03-01
|
Series: | Mathematics |
Subjects: | |
Online Access: | https://www.mdpi.com/2227-7390/11/6/1371 |
Similar Items
-
Do U.S. economic conditions at the state level predict the realized volatility of oil-price returns? A quantile machine-learning approach
by: Rangan Gupta, et al.
Published: (2023-01-01) -
Realized Stock-Market Volatility of the United States and the Presidential Approval Rating
by: Rangan Gupta, et al.
Published: (2023-07-01) -
Climate Risks and the Realized Volatility Oil and Gas Prices: Results of an Out-of-Sample Forecasting Experiment
by: Rangan Gupta, et al.
Published: (2021-12-01) -
Modeling Realized Variance with Realized Quarticity
by: Hiroyuki Kawakatsu
Published: (2022-09-01) -
Assessing the Impact of the Realized Range on the (E)GARCH Volatility: Evidence from Brazil
by: Victor Bello Accioly, et al.
Published: (2016-01-01)