Abstract
Although volatility in returns on equity stocks/shares is inherent, the presence of excessive volatility may not be preferred by a large number of equity investors (in particular, genuine long-term investors).
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Appendices
Annexure 7.1: Glossary of Terms
S. no. | Terms | Meaning |
---|---|---|
1 | Heteroscedasticity | A collection of random variables is heteroscedastic if there are subpopulations that have different variabilities from others |
2 | Leptokurtosis | Leptokurtosis deals with distributions having fatter tails and narrower and higher ‘peakedness’ at the mean compared to a normal distribution |
3 | Leverage effect | The condition where the impact of negative shocks is much greater than the positive shocks in driving the departure from normality or vice versa |
4 | Mean-reverting | ‘Mean-reverting’ behaviour of volatility suggests there is a normal level of volatility and deviations from that level are eventually cleared |
5 | Stationarity | The overall condition wherein the time series appears to have been drawn from a ‘stationary’ process, that is, a stochastic process where the joint probability distribution does not change when shifted in time and space |
6 | Volatility | A statistical measure of the dispersion of returns for a given security or a market index |
7 | Volatility clustering | The phrase ‘volatility clustering’ implies that periods of high (low) volatility are followed by periods of high (low) volatility, suggesting the presence of strong clustering of high and low fluctuations of the variable concerned |
Annexure 7.2: Ljung-Box Q2 Statistics
Ljung-box statistics | Test statistic | p-value |
---|---|---|
Q, 12 | 209.02 | 0.000 |
Q, 24 | 248.64 | 0.000 |
Q, 36 | 260.42 | 0.000 |
Q, 48 | 296.31 | 0.000 |
Q, 72 | 332.09 | 0.000 |
Q, 96 | 352.51 | 0.000 |
Q, 120 | 382.83 | 0.000 |
Q, 144 | 433.08 | 0.000 |
Q, 168 | 483.08 | 0.000 |
Q, 192 | 483.08 | 0.000 |
Q, 200 | 500.59 | 0.000 |
Annexure 7.3: Lagrange Multiplier Test
Lagrange multiplier test | Test statistic | p-value |
---|---|---|
LM, 5 | 40.51826 | 0.000 |
LM, 10 | 23.10503 | 0.000 |
LM, 20 | 13.26816 | 0.000 |
LM, 30 | 9.091963 | 0.000 |
LM, 40 | 7.006252 | 0.000 |
LM, 50 | 5.976162 | 0.000 |
LM, 60 | 5.184236 | 0.000 |
LM, 70 | 4.73443 | 0.000 |
LM, 80 | 4.238505 | 0.000 |
LM, 90 | 3.867223 | 0.000 |
LM, 100 | 3.627176 | 0.000 |
Annexure 7.4: Stationarity Test Statistics
Tests | Statistic value |
---|---|
ADF test for 1 lag (intercept and trend) | −39.04482 |
Philips–Perron (PP) test (intercept and trend) | −47.04032 |
Kwiatkowski–Phillips–Schmidt–Shin (KPSS) test statistics | 0.076364 |
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Singh, S., Jain, P.K., Yadav, S.S. (2016). Volatility in Stock Returns. In: Equity Markets in India. India Studies in Business and Economics. Springer, Singapore. https://doi.org/10.1007/978-981-10-0868-9_7
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