Özdemir Onur
Department of International Trade and Finance (English), Istanbul Gelisim University, Istanbul, Turkey.
Financ Innov. 2022;8(1):12. doi: 10.1186/s40854-021-00319-0. Epub 2022 Feb 3.
This study investigates the dynamic mechanism of financial markets on volatility spillovers across eight major cryptocurrency returns, namely Bitcoin, Ethereum, Stellar, Ripple, Tether, Cardano, Litecoin, and Eos from November 17, 2019, to January 25, 2021. The study captures the financial behavior of investors during the COVID-19 pandemic as a result of national lockdowns and slowdown of production. Three different methods, namely, EGARCH, DCC-GARCH, and wavelet, are used to understand whether cryptocurrency markets have been exposed to extreme volatility. While GARCH family models provide information about asset returns at given time scales, wavelets capture that information across different frequencies without losing inputs from the time horizon. The overall results show that three cryptocurrency markets (i.e., Bitcoin, Ethereum, and Litecoin) are highly volatile and mutually dependent over the sample period. This result means that any kind of shock in one market leads investors to act in the same direction in the other market and thus indirectly causes volatility spillovers in those markets. The results also imply that the volatility spillover across cryptocurrency markets was more influential in the second lockdown that started at the beginning of November 2020. Finally, to calculate the financial risk, two methods-namely, value-at-risk (VaR) and conditional value-at-risk (CVaR)-are used, along with two additional stock indices (the Shanghai Composite Index and S&P 500). Regardless of the confidence level investigated, the selected crypto assets, with the exception of the USDT were found to have substantially greater downside risk than SSE and S&P 500.
本研究调查了2019年11月17日至2021年1月25日期间，金融市场对八种主要加密货币收益（即比特币、以太坊、恒星币、瑞波币、泰达币、卡尔达诺、莱特币和柚子币）波动溢出的动态机制。该研究捕捉了新冠疫情期间，由于全国封锁和生产放缓，投资者的金融行为。使用了三种不同的方法，即指数广义自回归条件异方差模型（EGARCH）、动态条件相关广义自回归条件异方差模型（DCC-GARCH）和小波分析，来了解加密货币市场是否经历了极端波动。虽然广义自回归条件异方差（GARCH）族模型提供了给定时间尺度上资产回报的信息，但小波分析可以在不同频率上捕捉这些信息，而不会丢失时间范围内的输入信息。总体结果表明，在样本期内，三个加密货币市场（即比特币、以太坊和莱特币）波动性高且相互依赖。这一结果意味着，一个市场的任何冲击都会导致投资者在另一个市场采取相同方向的行动，从而间接导致这些市场的波动溢出。结果还表明，2020年11月初开始的第二次封锁期间，加密货币市场之间的波动溢出影响更大。最后，为了计算金融风险，使用了两种方法，即风险价值（VaR）和条件风险价值（CVaR），以及另外两个股票指数（上证综合指数和标准普尔500指数）。无论所研究的置信水平如何，除泰达币外，所选加密资产的下行风险均显著高于上证综指和标准普尔500指数。
