A New Financial Time Series Approach for Volatility Forecasting
| dc.contributor.author | Rathnayaka, R.M.K.T. | |
| dc.contributor.author | Seneiratna, D.M.K.N. | |
| dc.contributor.author | Arumawadu, H.I. | |
| dc.date.accessioned | 2016-12-20T08:59:36Z | |
| dc.date.available | 2016-12-20T08:59:36Z | |
| dc.date.issued | 2016 | |
| dc.description.abstract | The investment in capital market is easiest, fastest and securable way for building healthy financial foundation today. Because of the economic outlooks causing directly on these market fluctuations, the making decisions in the equity market has been regarding as one of the biggest challenges in the modern economy. The main purpose of this study is to take an attempt to understand the behavioral patterns and seek to develop a new hybrid forecasting approach under the volatility. The results are successfully implemented on Colombo stock exchange (CSE), Sri Lanka over the three year period from January 2013 to December 2015. The empirical results indicated that the new proposed hybrid approach is more suitable for forecasting price indices than traditional time series forecasting methodologies under the high volatility. | en_US |
| dc.identifier.citation | Rathnayaka, R.M.K.T., Seneiratna, D.M.K.N. and Arumawadu, H.I. 2016. A New Financial Time Series Approach for Volatility Forecasting. Symposium on Statistical & Computational Modelling with Applications (SymSCMA – 2016), Department of Statistics & Computer Science, University of Kelaniya, Sri Lanka. p 05-08. | en_US |
| dc.identifier.uri | http://repository.kln.ac.lk/handle/123456789/15545 | |
| dc.language.iso | en | en_US |
| dc.publisher | Department of Statistics & Computer Science, University of Kelaniya, Sri Lanka | en_US |
| dc.subject | ANN | en_US |
| dc.subject | ARIMA | en_US |
| dc.subject | ARIMA-ANN | en_US |
| dc.subject | Volatility | en_US |
| dc.title | A New Financial Time Series Approach for Volatility Forecasting | en_US |
| dc.type | Article | en_US |