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Analysis of Nse Using Eviews

In:

Submitted By anishmenon
Words 2133
Pages 9
Case Study: CNX Nifty Midcap Index

Descriptive statistics A. Closing price

1. Normality Test – non-normal distribution

2. Stationarity test for Log returns – series is stationary

Null Hypothesis: LOG_RETURNS has a unit root | | Exogenous: Constant | | | Lag Length: 0 (Automatic based on SIC, MAXLAG=23) | | | | | | | | | | | | | | t-Statistic | Prob.* | | | | | | | | | | | Augmented Dickey-Fuller test statistic | -35.96681 | 0.0000 | Test critical values: | 1% level | | -3.434655 | | | 5% level | | -2.863328 | | | 10% level | | -2.567771 | | | | | | | | | | | | *MacKinnon (1996) one-sided p-values. | | | | | | | | | | | | Augmented Dickey-Fuller Test Equation | | Dependent Variable: D(LOG_RETURNS) | | Method: Least Squares | | | Date: 11/03/10 Time: 16:06 | | | Sample (adjusted): 1/04/2005 11/02/2010 | | Included observations: 1449 after adjustments | | | | | | | | | | | | Coefficient | Std. Error | t-Statistic | Prob. | | | | | | | | | | | LOG_RETURNS(-1) | -0.944031 | 0.026247 | -35.96681 | 0.0000 | C | 0.000692 | 0.000484 | 1.429639 | 0.1530 | | | | | | | | | | | R-squared | 0.472016 | Mean dependent var | 1.64E-07 | Adjusted R-squared | 0.471651 | S.D. dependent var | 0.025333 | S.E. of regression | 0.018414 | Akaike info criterion | -5.150009 | Sum squared resid | 0.490653 | Schwarz criterion | -5.142723 | Log likelihood | 3733.181 | Hannan-Quinn criter. | -5.147290 | F-statistic | 1293.611 | Durbin-Watson stat | 1.996888 | Prob(F-statistic) | 0.000000 | | | | | | | | | | | | | |

PHILLIP Peron test for Log return series

Null Hypothesis: LOG_RETURNS has a unit root | | Exogenous: Constant | | | Bandwidth: 11

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