Discovering the Drivers of Stock Market Volatility in a Data-Rich World
Year of publication: |
[2022]
|
---|---|
Authors: | Cho, Hoon ; Chun, Dohyun ; Ryu, Doojin |
Publisher: |
[S.l.] : SSRN |
Subject: | Volatilität | Volatility | Aktienmarkt | Stock market | Welt | World | Börsenkurs | Share price |
Extent: | 1 Online-Ressource (56 p) |
---|---|
Type of publication: | Book / Working Paper |
Language: | English |
Notes: | Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments June 3, 2022 erstellt |
Other identifiers: | 10.2139/ssrn.4127304 [DOI] |
Classification: | C53 - Forecasting and Other Model Applications ; c55 ; G17 - Financial Forecasting |
Source: | ECONIS - Online Catalogue of the ZBW |
-
Predictive Regressions for Aggregate Stock Market Volatility with Machine Learning
Díaz, Juan, (2021)
-
Forecasting Stock Market Volatility and Application to Volatility Timing Portfolios
Chun, Dohyun, (2022)
-
Gooijer, Jan G. de, (2009)
- More ...
-
Discovering the Drivers of Market Volatility : Asset Allocation Applications
Cho, Hoon, (2021)
-
Economic indicators and stock market volatility in an emerging economy
Chun, Dohyun, (2020)
-
Chun, Dohyun, (2018)
- More ...