Enhancing cryptocurrency market volatility forecasting with daily dynamic tuning strategy
Year of publication: |
2024
|
---|---|
Authors: | Feng, Lingbing ; Qi, Jiajun ; Lucey, Brian M. |
Published in: |
International review of financial analysis. - Amsterdam [u.a.] : Elsevier Science, ISSN 1057-5219, ZDB-ID 2029229-6. - Vol. 94.2024, Art.-No. 103239, p. 1-14
|
Subject: | Cryptocurrency market | Dynamic tuning | Economic value | Variable importance | Volatility forecasting | ARCH-Modell | ARCH model | Volatilität | Volatility | Prognoseverfahren | Forecasting model | Virtuelle Währung | Virtual currency |
-
Chen, Zhenlong, (2024)
-
Volatility models for cryptocurrencies and applications in the options market
Chi, Yeguang, (2021)
-
Forecasting Bitcoin realized volatility by measuring the spillover effect among cryptocurrencies
Qiu, Yue, (2021)
- More ...
-
Feng, Lingbing, (2024)
-
A simulation study on the distributions of disturbances in the GARCH model
Feng, Lingbing, (2017)
-
The role of government intervention in financial development: micro‐evidence from China
Feng, Lingbing, (2019)
- More ...