Statistical Analysis of Indonesia Stock Market
| Autor: | Bakti Siregar, 錫誠嘉 |
|---|---|
| Rok vydání: | 2016 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 104 Liberalization and economic integration become topics of discussion and research in recent years. Indonesia is one of the countries that actively participates in the achievement of liberalization and economic integration, especially in the ASEAN region. Indonesia stock market has a high degree of volatility which can be used to produce high investment returns, which is one of the reasons to attract foreign investors to enter Indonesia stockmarket. Volatility plays an important role for market participants to control and reduce their market risk of financial assets In this study we establish the volatility models for the stocks listed in the Indonesia stock market index LQ45. The models we considered include the Autoregressive Conditional Heteroskedasticity (ARCH) proposed by Engle (1982), Generalized Autoregrassive Conditional Heteroskedasticity (GARCH) by Bollerslev (1986), the Stochastic Volatility Model (SVM) by Jacquier, Polson and Rossi (1994), and Autoregressive Moving Average (ARMA) by Box, Jankins, and Reinsel (1994). We use the daily log returns to establish the models and select the best one via Akaike information criterion (AIC).Moreover, we use it to predict the future volatility. In the end, we also apply machine learning application such as the K-means method to figure out how itsmovement of the clusters volatility in Indonesia stocks. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
| Externí odkaz: |
|