Forecasting Volatility of Australian Stock Market Applying WTC-DCA-Informer Framework

IF 2.7 3区 经济学 Q1 ECONOMICS
Hongjun Zeng, Ran Wu, Mohammad Zoynul Abedin, Abdullahi D. Ahmed
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引用次数: 0

Abstract

This article proposed a novel hybrid framework, the WTC-DCA-Informer, for forecasting volatility in the Australian stock market. The findings indicated that (1) through a comprehensive comparison with various machine learning and deep learning models, the proposed WTC-DCA-Informer framework significantly outperformed traditional methods in terms of predictive performance. (2) Across different training set proportions, the WTC-DCA-Informer model demonstrated exceptional forecasting capabilities, achieving a coefficient of determination (R2) as high as 0.9216 and a mean absolute percentage error (MAPE) as low as 13.6947%. (3) The model exhibited strong adaptability and robustness in responding to significant market fluctuations and structural changes before and after the outbreak of COVID-19. This study offers a new perspective and tool for forecasting financial market volatility, with substantial theoretical and practical implications for enhancing the efficiency and stability of financial markets.

应用WTC-DCA-Informer框架预测澳大利亚股市波动
本文提出了一种新的混合框架,即WTC-DCA-Informer,用于预测澳大利亚股市的波动率。研究结果表明:(1)通过与各种机器学习和深度学习模型的综合比较,所提出的WTC-DCA-Informer框架在预测性能方面明显优于传统方法。(2)在不同的训练集比例下,WTC-DCA-Informer模型均表现出卓越的预测能力,决定系数(R2)高达0.9216,平均绝对百分比误差(MAPE)低至13.6947%。(3)模型对疫情前后显著的市场波动和结构变化具有较强的适应性和鲁棒性。本研究为预测金融市场波动提供了新的视角和工具,对提高金融市场的效率和稳定性具有重要的理论和实践意义。
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来源期刊
CiteScore
5.40
自引率
5.90%
发文量
91
期刊介绍: The Journal of Forecasting is an international journal that publishes refereed papers on forecasting. It is multidisciplinary, welcoming papers dealing with any aspect of forecasting: theoretical, practical, computational and methodological. A broad interpretation of the topic is taken with approaches from various subject areas, such as statistics, economics, psychology, systems engineering and social sciences, all encouraged. Furthermore, the Journal welcomes a wide diversity of applications in such fields as business, government, technology and the environment. Of particular interest are papers dealing with modelling issues and the relationship of forecasting systems to decision-making processes.
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