# Bitcoin as a Safe Haven during COVID-19 Disease
## 3 Data and Methods
### Results
#### 3.2.2 DCC Model Results: Dynamic Conditional Correlations
Choosing the DCC-eGARCH(1,1) model, we proceeded with the computation of the dynamic conditional correlations. Tables 10-13 describe some statistics of these correlations related to the pairs Bitcoin/Ether indexes. Precisely, the median, the minimum and the maximum of the dynamic correlation between the pairs Bitcoin/Ether indexes are shown in six time windows. The first time window is the time-interval range between 1 July 2019 and 4 March 2020. Hence, it is the time window preceding the start of the pandemic. The other five time windows correspond to the _event windows_ fourteen days long during the  
\begin{table}
\begin{tabular}{c c c c c} \hline  & **Estimate** & **Std. Error** & **t Value** & **Pr (>|t|)** \\ \hline \([DAX]\), \(\omega\) & \(-0.177843\) & \(0.082192\) & \(-2.1637\) & \(0.030484\) \\ \([DAX]\), \(\omega\)1 & \(-0.132051\) & \(0.048471\) & \(-2.7243\) & \(0.006443\) \\ \([DAX]\), \(\beta\)1 & \(0.976456\) & \(0.009049\) & \(1.0790\times 10^{2}\) & \(0.000000\) \\ \([DAX]\), \(\gamma\)1 & \(0.209744\) & \(0.068337\) & \(3.0693\) & \(0.002146\) \\ \(\{}^{\prime}GSPC]\), \(\omega\) & \(-0.634528\) & \(0.354695\) & \(-1.7889\) & \(0.073624\) \\ \(\{}^{\prime}GSPC]\), \(\omega\)1 & \(-0.137234\) & \(0.114002\) & \(-1.2038\) & \(0.228672\) \\ \(\{}^{\prime}GSPC]\), \(\beta\)1 & \(0.922111\) & \(0.042674\) & \(2.1608\times 10\) & \(0.000000\) \\ \(\{}^{\prime}GSPC]\), \(\gamma\)1 & \(0.455469\) & \(0.135636\) & \(3.3580\) & \(0.000785\) \\ \(\{}^{\prime}FTSE]\), \(\omega\) & \(-0.426567\) & \(0.081726\) & \(-5.2195\) & \(0.000000\) \\ \([^{\prime}FTSE]\), \(\omega\)1 & \(-0.175619\) & \(0.046570\) & \(-3.7710\) & \(0.000163\) \\ \([^{\prime}FTSE]\), \(\beta\)1 & \(0.949165\) & \(0.009356\) & \(1.0145\times 10^{2}\) & \(0.000000\) \\ \([^{\prime}FTSE]\), \(\gamma\)1 & \(0.152212\) & \(0.058722\) & \(2.5921\) & \(0.009541\) \\ \([^{\prime}N225]\), \(\omega\) & \(-0.528630\) & \(0.141238\) & \(-3.7428\) & \(0.000182\) \\ \([^{\prime}N225]\), \(\omega\)1 & \(-0.237799\) & \(0.055749\) & \(-4.2655\) & \(0.000020\) \\ \([^{\prime}N225]\), \(\beta\)1 & \(0.939065\) & \(0.015363\) & \(6.1124\times 10\) & \(0.000000\) \\ \([^{\prime}N225]\), \(\gamma\)1 & \(0.266471\) & \(0.063192\) & \(4.2168\) & \(0.000025\) \\ \([BTC-USD]\), \(\omega\) & \(-0.552653\) & \(0.485819\) & \(-1.1376\) & \(0.255300\) \\ \([BTC-USD]\), \(\omega\)1 & \(-0.082472\) & \(0.168872\) & \(-4.8837\times 10^{-1}\) & \(0.625290\) \\ \([BTC-USD]\), \(\beta\)1 & \(0.900147\) & \(0.094514\) & \(9.5239\) & \(0.000000\) \\ \([BTC-USD]\), \(\gamma\)1 & \(0.197932\) & \(0.308051\) & \(6.4253\times 10^{-1}\) & \(0.520530\) \\ \([ETH-USD]\), \(\omega\) & \(-0.504108\) & \(0.908202\) & \(-5.5506\times 10^{-1}\) & \(0.578852\) \\ \([ETH-USD]\), \(\omega\)1 & \(-0.028082\) & \(0.220747\) & \(-1.2721\times 10^{-1}\) & \(0.898771\) \\ \([ETH-USD]\), \(\beta\)1 & \(0.898401\) & \(0.190023\) & \(4.7278\) & \(0.000002\) \\ \([ETH-USD]\), \(\gamma\)1 & \(0.213930\) & \(0.488293\) & \(4.3812\times 10^{-1}\) & \(0.661301\) \\ \([UIRTH]\), \(\omega\) & \(-0.370  
COVID-19 pandemic. This to investigate the trend of the correlations in the same windows in which we solved the regression model described in the previous sections. The statistics, shown in the Tables (look at the underlined correlations), highlight that some pairwise correlations, in some _event windows_ during the COVID-19 pandemic, were slightly lower or more negative than those in the period pre-pandemic, named _July- March 4_ in the Tables. In addition, there is also some correspondence between these correlations' values and the trend highlighted through the previously described regression analysis. For example, for the returns of the SSE A Share Index (_retSS_ variable) the median values computed in the 16 August +14, and 14 January +14 _event windows_ (0.1191 and 0.0314, respectively) are slightly lower than the median computed in the _July-March 4_ time window (0.1194).