Name
Abstract | ||
|---|---|---|
Financial time series data cannot be adequately modelled by a normal distribution and empirical evidence on the non-normality assumption is very well documented in the financial literature; see [R.F. Engle, Autoregressive conditional heteroskedasticity with estimates of the variance of UK inflation, Econometrica 50 (1982) 987–1008] and [T. Bollerslev, Generalized autoregressive conditional heteroscedasticity, J. Econometrics 31 (1986) 307–327] for details. The kurtosis of various classes of RCA models has been the subject of a study by Appadoo et al. [S.S. Appadoo, M. Gharahmani, A. Thavaneswaran, Moment properties of some volatility models, Math. Sci. 30 (2005) 50–63] and Thavaneswaran et al. [A. Thavaneswaran, S.S. Appadoo, M. Samanta, Random coefficient GARCH models, Math. Comput. Modelling 41 (2005) 723–733]. In this work we derive the kurtosis of the correlated RCA model as well as the normal GARCH model under the assumption that the errors are correlated. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1016/j.aml.2005.11.003 | Applied Mathematics Letters |
Keywords | Field | DocType |
Moments properties,Kurtosis,Correlated RCA models,Correlated GARCH models | Econometrics,Time series,Autoregressive model,Heteroscedasticity,Normal distribution,Conditional probability distribution,Autoregressive conditional heteroskedasticity,Volatility (finance),Kurtosis,Mathematics | Journal |
Volume | Issue | ISSN |
19 | 8 | 0893-9659 |
Citations | PageRank | References |
3 | 0.90 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| S.S. Appadoo | 1 | 97 | 12.82 |
| A. Thavaneswaran | 2 | 130 | 21.94 |
| Jagbir Singh | 3 | 3 | 0.90 |