Return equation using GARCH and PARCH model for NSE return Table 4
| GARCH (NSE) | PARCH (NSE) | |||||||
|---|---|---|---|---|---|---|---|---|
| Pre-L2 | Pre-L1 | Post-L1 | Post-L2 | Pre-L2 | Pre-L1 | Post-L1 | Post-L2 | |
| Panel A: Mean equation | ||||||||
| Constant, Β0 | −0.080* | −0.081* | 0.077* | 0.081* | 0.060* | 0.065* | 0.064* | 0.066* |
| Buddha Purnima | 0.093 | 0.188 | −0.306 | −0.053 | 0.116 | 0.173 | −0.294 | −0.101 |
| Christmas | −0.032 | 0.281 | 0.120 | 0.343* | 0.330* | 0.424** | 0.156 | 0.379* |
| Diwali | 0.141** | 0.107 | 0.041 | −0.039 | 0.145** | 0.118 | 0.049 | −0.043 |
| Dussehra | −0.213 | −0.190 | −0.016 | −0.162 | −0.211 | −0.214 | −0.013 | −0.188 |
| Eid al -Fitr | 0.189** | −0.095 | 0.311 | 0.044 | 0.027 | −0.091 | 0.277 | 0.010 |
| Ganesh Chaturthi | 0.180** | 0.265 | 0.456** | 0.366* | 0.203** | 0.285 | 0.458** | 0.379* |
| Good Friday | −0.179 | −0.279 | 0.014 | −0.044 | −0.159 | −0.266 | 0.000 | −0.061 |
| Gurunanak Jayanti | 0.014 | 0.095 | −0.012 | 0.176 | −0.019 | 0.093 | −0.026 | 0.126 |
| Holi | 0.002 | 0.055 | −0.005 | −0.050 | 0.027 | 0.074 | −0.055 | −0.090 |
| Mahashivratri | 0.223 | 0.211 | 0.129 | −0.082 | 0.212 | 0.218 | 0.133 | −0.117 |
| Mahavir Jayanti | −0.086 | −0.036 | −0.051 | −0.080 | 0.083 | −0.024 | −0.054 | −0.066 |
| Muharram | 0.121*** | −0.111 | −0.330*** | −0.041 | 0.048 | −0.093 | −0.339*** | −0.047 |
| Panel B: Variance equation | ||||||||
| C | 0.044* | 0.044* | 0.021* | 0.045* | 0.033* | 0.034* | 0.022 | 0.036* |
| Resid(−1)^2 | 0.109* | 0.110* | 0.097* | 0.110* | 0.120* | 0.120* | 0.108* | 0.121 |
| Garch(−1) | 0.841* | 0.8783* | 0.895* | 0.851* | 0.268* | 0.265* | 0.183* | 0.251* |
| γ | 0.888* | 0.887* | 0.899* | 0.885* | ||||
| δ | 1.127* | 1.171* | 1.601* | 1.237** | ||||
| Diagnostic test for specified model | ||||||||
| Ged parameter | 1.186 | 1.186 | 1.458 | 1.187 | 1.23965 | 1.288 | 1.460 | 1.189 |
| Log likelihood | 10,331.4 | 10,331.9 | 10,163.5 | 10,326.9 | 18,380.88 | 10,297.3 | 10,144.8 | 10,292.8 |
| ARCH-LM (10) | 0.991 | 0.969 | 0.873 | 0.969 | 0.997 | 1.00 | 0.921 | 0.972 |
| Q2 (10) | 0.970 | 0.996 | 0.901 | 0.970 | 0.995 | 0.998 | 0.922 | 0.991 |
| Wald test | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| GARCH (NSE) | PARCH (NSE) | |||||||
|---|---|---|---|---|---|---|---|---|
| Pre-L2 | Pre-L1 | Post-L1 | Post-L2 | Pre-L2 | Pre-L1 | Post-L1 | Post-L2 | |
| Constant, | −0.080 | −0.081 | 0.077 | 0.081 | 0.060 | 0.065 | 0.064 | 0.066 |
| Buddha Purnima | 0.093 | 0.188 | −0.306 | −0.053 | 0.116 | 0.173 | −0.294 | −0.101 |
| Christmas | −0.032 | 0.281 | 0.120 | 0.343 | 0.330 | 0.424 | 0.156 | 0.379 |
| Diwali | 0.141 | 0.107 | 0.041 | −0.039 | 0.145 | 0.118 | 0.049 | −0.043 |
| Dussehra | −0.213 | −0.190 | −0.016 | −0.162 | −0.211 | −0.214 | −0.013 | −0.188 |
| Eid al -Fitr | 0.189 | −0.095 | 0.311 | 0.044 | 0.027 | −0.091 | 0.277 | 0.010 |
| Ganesh Chaturthi | 0.180 | 0.265 | 0.456 | 0.366 | 0.203 | 0.285 | 0.458 | 0.379 |
| Good Friday | −0.179 | −0.279 | 0.014 | −0.044 | −0.159 | −0.266 | 0.000 | −0.061 |
| Gurunanak Jayanti | 0.014 | 0.095 | −0.012 | 0.176 | −0.019 | 0.093 | −0.026 | 0.126 |
| Holi | 0.002 | 0.055 | −0.005 | −0.050 | 0.027 | 0.074 | −0.055 | −0.090 |
| Mahashivratri | 0.223 | 0.211 | 0.129 | −0.082 | 0.212 | 0.218 | 0.133 | −0.117 |
| Mahavir Jayanti | −0.086 | −0.036 | −0.051 | −0.080 | 0.083 | −0.024 | −0.054 | −0.066 |
| Muharram | 0.121 | −0.111 | −0.330 | −0.041 | 0.048 | −0.093 | −0.339 | −0.047 |
| 0.044 | 0.044 | 0.021 | 0.045 | 0.033 | 0.034 | 0.022 | 0.036 | |
| Resid(−1)^2 | 0.109 | 0.110 | 0.097 | 0.110 | 0.120 | 0.120 | 0.108 | 0.121 |
| Garch(−1) | 0.841 | 0.8783 | 0.895 | 0.851 | 0.268 | 0.265 | 0.183 | 0.251 |
| 0.888 | 0.887 | 0.899 | 0.885 | |||||
| 1.127 | 1.171 | 1.601 | 1.237 | |||||
| Ged parameter | 1.186 | 1.186 | 1.458 | 1.187 | 1.23965 | 1.288 | 1.460 | 1.189 |
| Log likelihood | 10,331.4 | 10,331.9 | 10,163.5 | 10,326.9 | 18,380.88 | 10,297.3 | 10,144.8 | 10,292.8 |
| ARCH-LM (10) | 0.991 | 0.969 | 0.873 | 0.969 | 0.997 | 1.00 | 0.921 | 0.972 |
| 0.970 | 0.996 | 0.901 | 0.970 | 0.995 | 0.998 | 0.922 | 0.991 | |
| Wald test | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
Notes: Return equation using GARCH and PARCH model for NSE return;
This table represents the estimate for regression specification using the GARCH and PARCH Model. The parameter γ captures asymmetry in the model (γ < 0, γ ≠ 0 ∼ asymmetric). The power term δ capture both standard deviation (δ = 1) and conditional variance (δ = 2). EViews legacy technique was adopted to maximize the log-likelihood function of the GED. The ARCH LM test the null hypothesis of no autocorrelation up to 10 lags. The Ljung-Box Q-square statistics up to order 10 failed to rejected the null hypothesis of no autocorrelation. The null hypothesis of Wald test is H0: β1 = β2 …. = β12 = 0;
Panel A *, ** and *** represent statistical significance at 1, 5 and 10% levels, respectively
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