Exploring Apple’s Stock Price Volatility Using Five GARCH Models
| Autor: | Sihan Fu, Kexin He, Jialin Li, Zheng Tao |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Proceedings of Business and Economic Studies. 5:137-145 |
| ISSN: | 2209-265X 2209-2641 |
| Popis: | The financial market is the core of national economic development, and stocks play an important role in the financial market. Analyzing stock prices has become the focus of investors, analysts, and people in related fields. This paper evaluates the volatility of Apple Inc. (AAPL) returns using five generalized autoregressive conditional heteroskedasticity (GARCH) models: sGARCH with constant mean, GARCH with sstd, GJR-GARCH, AR(1) GJR-GARCH, and GJR-GARCH in mean. The distribution of AAPL’s closing price and earnings data was analyzed, and skewed student t-distribution (sstd) and normal distribution (norm) were used to further compare the data distribution of the five models and capture the shape, skewness, and loglikelihood in Model 4 – AR(1) GJR-GARCH. Through further analysis, the results showed that Model 4, AR(1) GJR-GARCH, is the optimal model to describe the volatility of the return series of AAPL. The analysis of the research process is both, a process of exploration and reflection. By analyzing the stock price of AAPL, we reflect on the shortcomings of previous analysis methods, clarify the purpose of the experiment, and identify the optimal analysis model. |
| Databáze: | OpenAIRE |
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