利用混合动态演化神经模糊推理系统模型估算沙特股票市场的波动性

Q4 Business, Management and Accounting
Nawaf N. Hamadneh, Jamil J. Jaber, Saratha Sathasivam
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引用次数: 0

摘要

本文研究了 KSA 股票市场(Tadawul)的波动性风险,重点是使用股票市场价格标准差的对数(LSCP)作为输出变量预测波动性。为加强波动率预测,该研究建议结合使用动态演化神经模糊推理系统(DENFIS)和非线性频谱模型--最大重叠离散小波变换(MODWT)。本研究利用由 4609 个观测值组成的数据集,通过自相关(AC)、偏自相关(PAC)、相关性和格兰杰因果关系检验,研究了收盘股价(LCP)、油价自然对数(Loil)、生活成本自然对数(LCL)和银行同业拆借利率(IB)的滞后 1 输入。回归分析表明,变量对 LSCP 有显著影响:在普通最小二乘法(OLS)模型中,LCP 有负效应,Loil 有正效应,而在固定效应模型中,LCL 和 IB 有正效应,在随机效应模型中,LCL 和 IB 有负效应。我们发现,MODWT-Haar-DENFIS 模型有可能成为股市预测的有效模型,因此开发了该模型。研究结果为投资者和政策制定者提供了有价值的见解,有助于风险管理、投资决策和制定减缓股市波动的措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimating Volatility of Saudi Stock Market Using Hybrid Dynamic Evolving Neural Fuzzy Inference System Models
This paper examines the volatility risk in the KSA stock market (Tadawul), with a specific focus on predicting volatility using the logarithm of the standard deviation of stock market prices (LSCP) as the output variable. To enhance volatility prediction, it proposes the combined use of the dynamic evolving neural fuzzy inference system (DENFIS) and the nonlinear spectral model, maximum overlapping discrete wavelet transform (MODWT). This study utilizes a dataset comprising 4609 observations and investigates the inputs of lag 1 of the close stock price (LCP), the natural logarithm of oil price (Loil), the natural logarithm of cost of living (LCL), and the interbank rate (IB), determined through autocorrelation (AC), partial autocorrelation (PAC), correlation, and Granger causality tests. Regression analysis reveals significant effects of variables on LSCP: LCP has a negative effect, and Loil has a positive effect in the ordinary least square (OLS) model, while LCL and IB have positive effects in the fixed effect model and negative effects in the random effect model. The MODWT-Haar-DENFIS model was developed as we found that the model has the potential to be an effective model for stock market forecasting. The results provide valuable insights for investors and policymakers, aiding in risk management, investment decisions, and the development of measures to mitigate stock market volatility.
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来源期刊
CiteScore
4.50
自引率
0.00%
发文量
512
审稿时长
11 weeks
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