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Sensors 2021, 21, 6319 11 of 16 Table2. Descriptivestatisticsandpreliminarytestsfordataofgoldprice,cryptocurrencyreturn,andCOVID-19. Variable Period Min Q1 1292 1720 1429 −0.0156 −0.0147 −0.0151 −0.0212 −0.0203 −0.0204 −0.0235 −0.0216 −0.0232 0.0000 −0.0082 0.0000 −0.0317 −0.0339 −0.0328 −0.0182 −0.0244 −0.0208 Mean 1391 1792 1617 0.0018 0.0036 0.0028 0.0003 0.0043 0.0026 0.0027 0.0058 0.0045 −0.0018 0.0042 0.0016 −0.0018 0.0011 −0.0002 0.0003 0.0091 0.0053 Median Q3 Max 1400 1490 1573 1800 1880 2067 1617 1817 2067 0.0009 0.0188 0.1600 0.0033 0.0232 0.1718 0.0018 0.0210 0.1718 −0.0012 0.0183 0.1661 0.0052 0.0354 0.2256 0.0016 0.0293 0.2256 0.0005 0.0310 0.1787 0.0038 0.0327 0.5292 0.002 0.0323 0.5292 0.0000 0.0000 0.2877 0.0000 0.0217 0.4055 0.0000 0.0000 0.4055 0.0000 0.0000 0.2171 0.0000 0.0392 0.3474 0.0000 0.0317 0.3474 −0.0024 0.0133 0.1803 −0.0006 0.0218 1.3235 −0.0017 0.0179 1.3235 SD * 101.29 113 226.07 0.0376 0.0477 0.0436 0.0453 0.0618 0.0552 0.0489 0.0752 0.0650 0.0777 0.0940 0.0873 0.0445 0.0814 0.0678 0.0377 0.1163 0.0909 JB Test ** 31 12 51 137 9767.9 12196 96 5793 8429 43 4002.3 7818 317 1817 2550 109 1657 4590 452 36,238 154,646 Pre-COVID-19 Gold COVID-19 Both periods Pre-COVID-19 BTC COVID-19 Both periods Pre-COVID-19 ETH COVID-19 Both periods Pre-COVID-19 BNB COVID-19 Both periods Pre-COVID-19 ADA COVID-19 Both periods Pre-COVID-19 XRP COVID-19 Both periods Pre-COVID-19 DOGE COVID-19 Both periods 1235 1474 1235 −0.1518 −0.4647 −0.4647 −0.1833 −0.5507 −0.5507 −0.1929 −0.5428 −0.5428 −0.2877 −0.6931 −0.6931 −0.1542 −0.5486 −0.5486 −0.1156 −0.4523 −0.4523 * SD stands for standard deviation and ** all JB p-values are significant at 1%. Table3. Grangercausalitytestresultsfordataofgoldprices,cryptocurrencyreturn,andCOVID-19. COVID-19 Infected Cases COVID-19 Death Cases Null Hypothesis COVID-19 ≠⇒ Gold COVID-19 ≠⇒ BTC COVID-19 ≠⇒ ETH COVID-19 ≠⇒ BNB COVID-19 ≠⇒ ADA COVID-19 ≠⇒ XRP COVID-19 ≠⇒ DOGE Wald p-Value 0.4376 0.7262 0.9753 0.4044 1.9525 0.1207 0.7258 0.5371 1.0662 0.3634 2.4939 0.0597 0.8942 0.4442 Null Hypothesis Wald p-Value 0.1968 0.8985 0.6815 0.5638 0.8400 0.4726 0.2029 0.8944 2.0982 0.1000 2.2387 0.0834 2.2739 0.0796 COVID-19 COVID-19 COVID-19 COVID-19 COVID-19 COVID-19 COVID-19 ≠ ⇒ Gold ≠ ⇒ BTC ≠ ⇒ ETH ≠ ⇒ BNB ≠ ⇒ ADA ≠ ⇒ XRP ≠ ⇒ DOGE The results in Table 2 and Figures 2–4 also show a significant increase in the volatility of the returns of gold and currencies after the outbreak of the COVID-19, compared with the pre-pandemic period. Note that, in these figures, as mentioned, the vertical dotted line represents a threshold between the pre-COVID-19 period and during the pandemic. In addition, the circled points are the support vectors, and misclassification appears when the color of the support vectors does not match the color of the decision boundary. Thus, the traditional econometric and time-series models might not provide helpful results in such cases. Hence, due to its superior forecasting performance, we implement the SVM in our analysis. The SVM optimization strategy is usually done in two stages. First, we separate the observations into training and testing data sets. A rule of thumb indicates to consider the first 75% contiguous days as a training set to fit the model and the remaining 25% days as a testing set, which is used to validate the prediction accuracy of this model [40]. The best model is selected based on minimizing the mean absolute percentage error (MAPE), root mean square error (RMSE), or normalized root mean square error (NRMSE) defined asPDF Image | Predicting Cryptocurrency Returns Based on the Gold Prices
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