| รหัสดีโอไอ | 10.14456/ssa.2015.24 |
|---|---|
| Creator | Josep Ginting |
| Title | Realized volatility model for market riskmeasurement in Indonesia stock exchange |
| Publisher | National Research Council of Thailand |
| Publication Year | 2015 |
| Journal Title | Social Science Asia |
| Journal Vol. | 1 |
| Journal No. | 3 (March) |
| Page no. | 93-104 |
| ISSN | 2229-2610 |
| Abstract | This paper discussed the testing of Realized Volatility (RV) model.The model was formulated based on intraday stock price data and interday stock price on the Indonesian Stock Exchange. At first, the idea of this research came when researcher looked back at the gambling factor in Indonesia Stock Market.The stocks price moved up and down with highly volatility and not in a normal pattern. Reflection of heteroskedasticity is in stocks price movement. For the investors in stock market it is the risk when the trend of market cannot be predicted, accurately and effectively. Of course investors will need tools to minimize market risk, optimally. In the first observation, found a signal that thebehavioral finance of investor influenced the stock price trend, from morning session until the market closed in the afternoon. However, the available tools to measure the price volatility of the shares was originally known ARCH (autoregressive conditionally heteroskedasticity) model, the model by using the closing price of stocks. Based on the ARCH structure, it cannot be used to have the optimal results of lower risk in highly frequency data. To solve that problem, need to formulate the newapproach by combining the intraday risk measurement with interday risk measurement which ARCH Model cannot provide it. The proposed model is Realized Volatility. Realize Volatility model is the model with combination between intraday volatility and interday volatility. This mathematical combination must use high frequency data, then the available tools cannot be used. In the process of research, not only the ARCH model, but also the ARIMA (Autoregressive Integrated MovingAverage) as the tools to test the model also cannot be used because the data is high frequency data. In this research used ARFIMA (Autoregressive Fragtionally Integrated Moving Average) to test the accuracy of the models, to replace the ARIMA. The result of this research is that RV model provided more accurate measurement than ARCH model. RV model will be helpful for investors who want to select the stocks with lower market risk. RV model also can help a treasury manager in bankingsector to assess and minimize market risk of foreign exchange, as well as can help fund manager select lower risk stocks and lower risk mutual fund. |
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