| Full text | |
| Author(s): |
Total Authors: 3
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| Affiliation: | [1] FGV, Sao Paulo Sch Econ, Sao Paulo, SP - Brazil
[2] Ctr Appl Res Econometr Finance & Stat, Campinas, SP - Brazil
[3] Rajagiri Business Sch, Rajagiri Valley Campus, Kochi, Kerala - India
[4] Minist Finance, Macro & Fiscal Policies Unit, The Hague - Saudi Arabia
Total Affiliations: 4
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| Document type: | Journal article |
| Source: | APPLIED ECONOMICS; v. 52, n. 24 NOV 2019. |
| Web of Science Citations: | 0 |
| Abstract | |
Risk management is an important and helpful process for investors, hedge funds, traders and market makers. One of its key points is the appropriate estimation of risk measures which can improve the investment decisions and trading strategies. The high volatility of cryptocurrencies turns them a really risky investment and consequently, appropriate risk measures estimation is extremely necessary. In this article, we deal with the estimation of two widely used risk measures such as Value-at-Risk and Expected Shortfall in a cryptocurrency context. To face the presence of outliers and the correlation between cryptocurrencies, we propose a methodology based on vine copulas and robust volatility models. Our procedure is illustrated in a seven-dimensional equal-weight cryptocurrency portfolio and displays good performance. (AU) | |
| FAPESP's process: | 16/18599-4 - Modeling and forecasting volatility of high dimensional financial series |
| Grantee: | Carlos Cesar Trucios Maza |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |