Optimisasi Portofolio Mean-VaR di bawah CAPM Transformasi Koyck dengan Volatilitas Tak Konstan dan Efek Long Memory
Keywords:ARFIMA, GARCH, CAPM, Koyck, VaR, Kuhn-Tucker.
AbstractIn this paper we formulated mean-VaR portfolio optimization through CAPM Koyck transformation. We assumed that lagged of risk premium which have highly influence on stock returns is infinite, while model parameters decrease geometrically. We also assumed that rate of return in risk premium market index is not constant, in other word has a non-constant volatility rate, and also has a long memory effect. The later was analyzed using ARFIMA. Non constant volatility rate was modeled via GARCH model. The portfolio optimization was constructed using Langrangian multiplier and the Kuhn-Tucker theorem was employed to obtain the solution by the least square method. Finally, we provide a numerical example of the optimization model based on several stocks traded in Indonesian capital market.
How to Cite
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).