Modelling Stock Market Volatility: Evidence from Vietnam
About: This article is published in VNU Journal of Science: Economics and Business.The article was published on 2017-09-24 and is currently open access. It has received 2 citations till now. The article focuses on the topics: Stock market bubble & Volatility swap.
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31 Mar 2019
TL;DR: In this article, the effects of derivatives of the Vietnam Ho Chi Minh (VN) Stock Index and VN30 futures contract for the underlying stock markets were analyzed using the Exponential Generalized Autoregressive Conditional Heteroscedastic (EGARCH) model.
Abstract: In this paper, we analyze the effects of derivatives of the Vietnam Ho Chi Minh (VN) Stock Index and VN30 futures contract for the underlying stock markets. We use the data taken from daily transactions in the market so that the research results will be more objective and more accurate. Specifically, we apply the Exponential Generalized Autoregressive Conditional Heteroscedastic (EGARCH) model to analyze the data. The results illustrate that the occurrence of leverage effects in the profitability of VN30 and VN stock indexes and the liquidity of futures contract transactions have increased over time. The main contribution of this paper is that it is possible to predict the growth trend of derivative securities to make appropriate recommendations for investors. However, the evidence still has some limitations since it only assesses the impact of futures contracts during the specific time, which is the period of instruments that have just appeared.
4 citations
Cites background from "Modelling Stock Market Volatility: ..."
...Tien et al. (2017) studied the modeling of fluctuations in Vietnam stock market based on time series data as daily closing prices of the VNIndex in the period 2005- 2016....
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TL;DR: In this paper , the authors examined the association between financial market volatility and actual economic incidents and selected the most adequate generalized autoregressive conditional Heteroskedasticity (GARCH) family models and corresponding distribution rules.
Abstract: The paper examines the association between financial market volatility and actual economic incidents. We specifically analyze the statistical characteristics of the stock price series and its association with the financial cycle. Using 20 years of Vietnamese main stock VNIndex daily data from 2 August 2000 to 31 December 2020, we select the most adequate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) family models and corresponding distribution rules. The paper initially assesses several types of GARCH models’ criteria, namely the log-likelihood, AIC and BIC, in choosing the best model to illustrate the financial cycle. We further use three different distribution rules, namely the normal distribution rule, the Student-t statistic distribution, and the Generalized Error Distribution (GED), in selecting the best GARCH model. The results show that Exponential Generalized Autoregressive Conditional Heteroscedastic (EGARCH) with student-t statistic distribution seems the best suited to demonstrate the stock price and its return volatility. It also suits the marginal distribution of the financial cycle. Our study further validates the lead time and volatility between the selected model results and the significant financial events using the turning point and Bull-Bear application (Lunde and Timmermann, 2004). Although the recommended model has shown no evidence as an effective forecast tool for the financial cycle in long run, this study paves the way for extensive research in the future.
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31 Mar 2019
TL;DR: In this article, the effects of derivatives of the Vietnam Ho Chi Minh (VN) Stock Index and VN30 futures contract for the underlying stock markets were analyzed using the Exponential Generalized Autoregressive Conditional Heteroscedastic (EGARCH) model.
Abstract: In this paper, we analyze the effects of derivatives of the Vietnam Ho Chi Minh (VN) Stock Index and VN30 futures contract for the underlying stock markets. We use the data taken from daily transactions in the market so that the research results will be more objective and more accurate. Specifically, we apply the Exponential Generalized Autoregressive Conditional Heteroscedastic (EGARCH) model to analyze the data. The results illustrate that the occurrence of leverage effects in the profitability of VN30 and VN stock indexes and the liquidity of futures contract transactions have increased over time. The main contribution of this paper is that it is possible to predict the growth trend of derivative securities to make appropriate recommendations for investors. However, the evidence still has some limitations since it only assesses the impact of futures contracts during the specific time, which is the period of instruments that have just appeared.
4 citations