Volatility Spillovers among the Cryptocurrency Time Series
<p>This paper uses different multivariate GARCH models to model conditional correlations and analyze the volatility spillovers between cryptocurrency time series. The dynamic conditional correlation GARCH model is found to fit the data the best. Our empirical results are fourfold. First, on av...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
EconJournals
2019-04-01
|
| Series: | International Journal of Economics and Financial Issues |
| Online Access: | https://www.econjournals.com/index.php/ijefi/article/view/7383 |
| _version_ | 1797905605626691584 |
|---|---|
| author | Zouheir Mighri Majid Ibrahim Alsaggaf |
| author_facet | Zouheir Mighri Majid Ibrahim Alsaggaf |
| author_sort | Zouheir Mighri |
| collection | DOAJ |
| description | <p>This paper uses different multivariate GARCH models to model conditional correlations and analyze the volatility spillovers between cryptocurrency time series. The dynamic conditional correlation GARCH model is found to fit the data the best. Our empirical results are fourfold. First, on average, a $1 long position in BitShares (BTS) can be hedged for 15% with a short position in MonaCoin (MONA), while a $1 long position in MONA can be hedged for 14% with a short position in Ripple (XRP). Second, the average weight for the BTS/MONA portfolio is 0.48, indicating that for a $1 portfolio, 48% should be invested in BTS and 52% invested in MONA. Third, the average weight for the BTS/XRP portfolio indicates that 27% should be invested in BTS and 73 % invested in XRP. Finally, the average weight for the MONA/XRP portfolio indicates that 33% should be invested in MONA and 67% invested in XRP.</p><p><strong>Keywords</strong>: Cryptocurrencies,<strong> </strong>Multivariate GARCH, Volatility spillover, Hedging, Portfolio designs.</p><p><strong>JEL Classifications</strong><strong>: </strong>C5, C22, C32, G1.</p><p>DOI: <a href="https://doi.org/10.32479/ijefi.7383">https://doi.org/10.32479/ijefi.7383</a></p> |
| first_indexed | 2024-04-10T10:07:56Z |
| format | Article |
| id | doaj.art-6a086885c65b4f339926e5a6d37fdb83 |
| institution | Directory Open Access Journal |
| issn | 2146-4138 |
| language | English |
| last_indexed | 2024-04-10T10:07:56Z |
| publishDate | 2019-04-01 |
| publisher | EconJournals |
| record_format | Article |
| series | International Journal of Economics and Financial Issues |
| spelling | doaj.art-6a086885c65b4f339926e5a6d37fdb832023-02-15T16:22:23ZengEconJournalsInternational Journal of Economics and Financial Issues2146-41382019-04-019381903848Volatility Spillovers among the Cryptocurrency Time SeriesZouheir MighriMajid Ibrahim Alsaggaf<p>This paper uses different multivariate GARCH models to model conditional correlations and analyze the volatility spillovers between cryptocurrency time series. The dynamic conditional correlation GARCH model is found to fit the data the best. Our empirical results are fourfold. First, on average, a $1 long position in BitShares (BTS) can be hedged for 15% with a short position in MonaCoin (MONA), while a $1 long position in MONA can be hedged for 14% with a short position in Ripple (XRP). Second, the average weight for the BTS/MONA portfolio is 0.48, indicating that for a $1 portfolio, 48% should be invested in BTS and 52% invested in MONA. Third, the average weight for the BTS/XRP portfolio indicates that 27% should be invested in BTS and 73 % invested in XRP. Finally, the average weight for the MONA/XRP portfolio indicates that 33% should be invested in MONA and 67% invested in XRP.</p><p><strong>Keywords</strong>: Cryptocurrencies,<strong> </strong>Multivariate GARCH, Volatility spillover, Hedging, Portfolio designs.</p><p><strong>JEL Classifications</strong><strong>: </strong>C5, C22, C32, G1.</p><p>DOI: <a href="https://doi.org/10.32479/ijefi.7383">https://doi.org/10.32479/ijefi.7383</a></p>https://www.econjournals.com/index.php/ijefi/article/view/7383 |
| spellingShingle | Zouheir Mighri Majid Ibrahim Alsaggaf Volatility Spillovers among the Cryptocurrency Time Series International Journal of Economics and Financial Issues |
| title | Volatility Spillovers among the Cryptocurrency Time Series |
| title_full | Volatility Spillovers among the Cryptocurrency Time Series |
| title_fullStr | Volatility Spillovers among the Cryptocurrency Time Series |
| title_full_unstemmed | Volatility Spillovers among the Cryptocurrency Time Series |
| title_short | Volatility Spillovers among the Cryptocurrency Time Series |
| title_sort | volatility spillovers among the cryptocurrency time series |
| url | https://www.econjournals.com/index.php/ijefi/article/view/7383 |
| work_keys_str_mv | AT zouheirmighri volatilityspilloversamongthecryptocurrencytimeseries AT majidibrahimalsaggaf volatilityspilloversamongthecryptocurrencytimeseries |