股票市场快速发展,股票价格波动性研究备受关注,准确预测股价走势对投资者决策和市场稳定意义重大。鉴于股票价格波动的不确定性与非线性特征,单一模型预测效果欠佳。为此,本文提出将GARCH与BP神经网络相结合的组合预测方法,以中国农业...股票市场快速发展,股票价格波动性研究备受关注,准确预测股价走势对投资者决策和市场稳定意义重大。鉴于股票价格波动的不确定性与非线性特征,单一模型预测效果欠佳。为此,本文提出将GARCH与BP神经网络相结合的组合预测方法,以中国农业银行股票日收盘价数据为例,基于误差修正思想构建组合模型,运用BP神经网络对GARCH模型的残差数据进行预测校正。研究结果表明组合模型预测效果优于单一模型,验证了该组合模型在提高股票价格预测准确度方面的有效性。With the rapid development of the stock market, the study of stock price volatility has attracted much attention, and accurate prediction of stock price movements is of great significance to investors’ decision-making and market stability. In view of the uncertainty and nonlinear characteristics of stock price volatility, the prediction effect of a single model is not good. For this reason, this paper proposes a combined prediction method combining GARCH and BP neural network, taking the daily closing price data of Agricultural Bank of China as an example, constructing a combined model based on the idea of error correction, and utilizing BP neural network to correct the residual data of the GARCH model for prediction. The results show that the combination model predicts better than a single model, which verifies the effectiveness of the combination model in improving the accuracy of stock price prediction.展开更多
本文以绿色债券和传统债券市场收益率的波动性为研究主题,首先通过构建GARCH模型来度量债券收益率的波动性,其次通过DCC-GARCH模型来研究分析传统债券市场收益率波动性与绿色债券市场收益率波动性之间的联动关系,结果发现两者之间存在...本文以绿色债券和传统债券市场收益率的波动性为研究主题,首先通过构建GARCH模型来度量债券收益率的波动性,其次通过DCC-GARCH模型来研究分析传统债券市场收益率波动性与绿色债券市场收益率波动性之间的联动关系,结果发现两者之间存在正向相关关系。政府等决策部门在制定政策时应关注传统债券市场与绿色债券市场间的联动关系,以促进市场的稳定和健康发展。推动绿色债券市场的信息披露透明化,有助于投资者更好地理解两类市场的风险和收益波动性。投资者应密切关注影响两类市场的宏观经济和市场因素,以便在波动性增加时迅速调整投资组合。This paper takes the volatility of green bond and traditional bond market as the research theme. Firstly, GARCH model is constructed to measure the volatility of bond yield. Secondly, DCC-GARCH model is used to study and analyze the linkage relationship between the volatility of traditional bond market and the volatility of green bond market. The results show that there is a positive correlation between the two. The government and other decision-making departments should pay attention to the linkage between the traditional bond market and the green bond market when formulating policies, so as to promote the stable and healthy development of the market. Promoting transparency in the green bond market will help investors better understand the risk and return volatility of both markets. Investors should pay close attention to macroeconomic and market factors affecting both types of markets so that they can quickly adjust their portfolios when volatility increases.展开更多
在套期保值的理论和实务中,最优套期保值比率的估计其核心问题。在估计最优套期保值比率的众多方法中,Kroner and Sultan(1993)的ECM-GARCH模型将协整关系和时变方差结合起来,产生了较好的套期保值效果。本文结合中国期货及现货市场的特...在套期保值的理论和实务中,最优套期保值比率的估计其核心问题。在估计最优套期保值比率的众多方法中,Kroner and Sultan(1993)的ECM-GARCH模型将协整关系和时变方差结合起来,产生了较好的套期保值效果。本文结合中国期货及现货市场的特点,在Kroner and Sultan(1993)方法的基础上发展了一个修正的ECM-GARCH模型,并运用该模型、Bivariate GARCH及Kroner and Sultan(1993)的ECM-GARCH对中国铜期货市场的动态最优套期保值比率进行了对比研究,结果表明:在中国铜期货市场,基于修正的ECM-GARCH模型的套期保值效果比基于BGARCH模型及Kroner and Sultan(1993)的ECM-GARCH模型套期保值效果好得多,相对于BGARCH模型和Kroner and Sultan(1993)的ECM-GARCH模型,Modified ECM-GARCH模型套期保值的风险分别减少93.6%和92%。展开更多
文摘股票市场快速发展,股票价格波动性研究备受关注,准确预测股价走势对投资者决策和市场稳定意义重大。鉴于股票价格波动的不确定性与非线性特征,单一模型预测效果欠佳。为此,本文提出将GARCH与BP神经网络相结合的组合预测方法,以中国农业银行股票日收盘价数据为例,基于误差修正思想构建组合模型,运用BP神经网络对GARCH模型的残差数据进行预测校正。研究结果表明组合模型预测效果优于单一模型,验证了该组合模型在提高股票价格预测准确度方面的有效性。With the rapid development of the stock market, the study of stock price volatility has attracted much attention, and accurate prediction of stock price movements is of great significance to investors’ decision-making and market stability. In view of the uncertainty and nonlinear characteristics of stock price volatility, the prediction effect of a single model is not good. For this reason, this paper proposes a combined prediction method combining GARCH and BP neural network, taking the daily closing price data of Agricultural Bank of China as an example, constructing a combined model based on the idea of error correction, and utilizing BP neural network to correct the residual data of the GARCH model for prediction. The results show that the combination model predicts better than a single model, which verifies the effectiveness of the combination model in improving the accuracy of stock price prediction.
文摘本文以绿色债券和传统债券市场收益率的波动性为研究主题,首先通过构建GARCH模型来度量债券收益率的波动性,其次通过DCC-GARCH模型来研究分析传统债券市场收益率波动性与绿色债券市场收益率波动性之间的联动关系,结果发现两者之间存在正向相关关系。政府等决策部门在制定政策时应关注传统债券市场与绿色债券市场间的联动关系,以促进市场的稳定和健康发展。推动绿色债券市场的信息披露透明化,有助于投资者更好地理解两类市场的风险和收益波动性。投资者应密切关注影响两类市场的宏观经济和市场因素,以便在波动性增加时迅速调整投资组合。This paper takes the volatility of green bond and traditional bond market as the research theme. Firstly, GARCH model is constructed to measure the volatility of bond yield. Secondly, DCC-GARCH model is used to study and analyze the linkage relationship between the volatility of traditional bond market and the volatility of green bond market. The results show that there is a positive correlation between the two. The government and other decision-making departments should pay attention to the linkage between the traditional bond market and the green bond market when formulating policies, so as to promote the stable and healthy development of the market. Promoting transparency in the green bond market will help investors better understand the risk and return volatility of both markets. Investors should pay close attention to macroeconomic and market factors affecting both types of markets so that they can quickly adjust their portfolios when volatility increases.
文摘在套期保值的理论和实务中,最优套期保值比率的估计其核心问题。在估计最优套期保值比率的众多方法中,Kroner and Sultan(1993)的ECM-GARCH模型将协整关系和时变方差结合起来,产生了较好的套期保值效果。本文结合中国期货及现货市场的特点,在Kroner and Sultan(1993)方法的基础上发展了一个修正的ECM-GARCH模型,并运用该模型、Bivariate GARCH及Kroner and Sultan(1993)的ECM-GARCH对中国铜期货市场的动态最优套期保值比率进行了对比研究,结果表明:在中国铜期货市场,基于修正的ECM-GARCH模型的套期保值效果比基于BGARCH模型及Kroner and Sultan(1993)的ECM-GARCH模型套期保值效果好得多,相对于BGARCH模型和Kroner and Sultan(1993)的ECM-GARCH模型,Modified ECM-GARCH模型套期保值的风险分别减少93.6%和92%。
