Volatility forecasting in the Bitcoin market: A new proposed measure based on the VS-ACARR approach |
| |
| Institution: | 1. School of Finance, Anhui University of Finance and Economics, Bengbu 233030, Anhui, PR China;2. College of Business, Zayed University, P.O. Box 144534. Abu Dhabi, United Arab Emirates;1. Department of Business Administration, Konkuk University, Gwangjin‐gu, Seoul 05029, Republic of Korea;2. Department of Finance, Dong-A University, 225, Gudeok-ro, Seo-gu, Busan 49236, Republic of Korea;1. Department of Finance and Accounting, University of Tunis El Manar and IFGT, Tunis, Tunisia;2. Department of Economics and Finance, College of Economics and Political Science, Sultan Qaboos University, Muscat, Oman;3. ISEG – Lisbon School of Economics and Management, SOCIUS/CSG – Research in Social Sciences and Management, Universidade de Lisboa, Rua Miguel Lupi, 20, 1249-078 Lisbon, Portugal;4. HSE University, Pokrovsky Blv. 11, 109028 Moscow, Russian Federation;5. PNU Business School, Pusan National University, Busan, South Korea;1. Department of Commerce, Dr. Bhim Rao Ambedkar College, University of Delhi, New Delhi, India;2. Faculty of Management Studies, University of Delhi, New Delhi 110007, India;3. Department of Economics and Finance, Institute of Management, Nirma University, India;4. School of Finance, Anhui University of Finance and Economics, Bengbu 233030, Anhui, China;5. ISEG – Lisbon School of Economics & Management, Universidade de Lisboa, Rua Miguel Lupi, 20, 1249-078 Lisbon, Portugal;6. Africa-Asia Centre for Sustainability, Business School, University of Aberdeen, Scotland, U.K;7. SOCIUS/CSG – Research in Social Sciences and Management, Universidade de Lisboa, Rua Miguel Lupi, 20, 1249-078 Lisbon, Portugal |
| |
| Abstract: | This paper proposes a new volatility-spillover-asymmetric conditional autoregressive range (VS-ACARR) approach that takes into account the intraday information, the volatility spillover from crude oil as well as the volatility asymmetry (leverage effect) to model/forecast Bitcoin volatility (price range). An empirical application to Bitcoin and crude oil (WTI) price ranges shows the existence of strong volatility spillover from crude oil to the Bitcoin market and a weak leverage effect in the Bitcoin market. The VS-ACARR model yields higher forecasting accuracy than the GARCH, CARR, and VS-CARR models regarding out-of-sample forecast performance, suggesting that accounting for the volatility spillover and asymmetry can significantly improve the forecasting accuracy of Bitcoin volatility. The superior forecast performance of the VS-ACARR model is robust to alternative out-of-sample forecast windows. Our findings highlight the importance of accommodating intraday information, spillover from crude oil, and volatility asymmetry in forecasting Bitcoin volatility. |
| |
| Keywords: | Bitcoin Price range Volatility spillover Crude oil Leverage effect Conditional Auto Regressive Range (CARR) |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
