From: Can news-based economic sentiment predict bubbles in precious metal markets?
 | Dependent variable: Bubble | |||
---|---|---|---|---|
Gold | Silver | Palladium | Platinum | |
Panel A: Probit models | ||||
\(NESI_{t - 1}\) | − 1.5088*** | 0.2503 | 0.7318 | − 1.0746*** |
(0.0020) | (0.7400) | (0.2810) | (0.0000) | |
\(Inflation_{t - 1}\) | 0.3800** | 0.1281* | 0.5802*** | 0.2080*** |
(0.0200) | (0.0940) | (0.0000) | (0.0000) | |
\(US{\text{DI}}_{t - 1}\) | − 1.2551*** | − 0.2018** | − 0.0546*** | − 0.6100*** |
(0.0030) | (0.0120) | (0.0080) | (0.0021) | |
\({\text{EFR}}_{t - 1}\) | − 0.1560** | 0.2178 | − 0.4890*** | − 0.2283*** |
(0.0240) | (0.2110) | (0.0000) | (0.0000) | |
\(T - Spread_{t - 1}\) | − 0.4356* | − 1.2005** | − 0.3744** | − 0.4551*** |
(0.0780) | (0.0120) | (0.0311) | (0.0200) | |
\({\text{GEA}}_{t - 1}\) | 0.0102*** | 0.0060** | 0.0045** | 0.0062*** |
(0.0000) | (0.0200) | (0.0138) | (0.0000) | |
\(Constant\) | 0.3189*** | 0.3698*** | 0.5793*** | 0.2435*** |
(0.0000) | (0.0029) | (0.0000) | (0.0000) | |
Panel B: Conditional marginal effects | ||||
\(NESI_{t - 1}\) | − 0.2675*** | 0.0170 | 0.0973 | − 0.2425*** |
(0.0060) | (0.7430) | (0.2440) | (0.0010) | |
\(Inflation_{t - 1}\) | 0.2447** | 0.0871* | 0.7419*** | 0.0498*** |
(0.0360) | (0.0945) | (0.0000) | (0.0000) | |
\(US{\text{DI}}_{t - 1}\) | − 0.2225*** | − 0.0137*** | − 0.0073*** | − 0.0226*** |
(0.0010) | (0.0020) | (0.0010) | (0.0020) | |
\({\text{EFR}}_{t - 1}\) | − 0.0277** | 0.0148 | − 0.0650*** | − 0.0515*** |
(0.0120) | (0.2070) | (0.0000) | (0.0000) | |
\(T - Spread_{t - 1}\) | − 0.0772** | − 0.0816** | − 0.0498** | − 0.1027** |
(0.0750) | (0.0160) | (0.0292) | (0.0220) | |
\({\text{GEA}}_{t - 1}\) | 0.0018*** | 0.0004** | 0.0006** | 0.0014*** |
(0.0000) | (0.0330) | (0.0135) | (0.0000) | |
\(Observations\) | 420 | 420 | 420 | 420 |
McFadden's pseud-R2 | 0.8334 | 0.5714 | 0.4757 | 0.6726 |
Log-likelihood | − 117.6715 | − 48.2477 | − 92.6440 | − 162.2984 |
Hosmer–Lemeshow test | 7.09 | 8.12 | 6.67 | 11.97 |
(0.3690) | (0.1887) | (0.1598) | (0.2176) | |
\({\text{Correct bubble}}\) | 84.13% | 75.00% | 74.42% | 96.30% |
\({\text{Correct no}} - {\text{bubble}}\) | 96.99% | 96.21% | 91.67% | 86.88% |
\({\text{Correct }}\left( {{\text{classified}}} \right){\text{ overall}}\) | 92.36% | 95.59% | 91.91% | 87.50% |