基于复杂网络和模糊逻辑理论的金融市场波动

IF 1.5 Q2 COMPUTER SCIENCE, THEORY & METHODS
Zhi-yuan Li
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引用次数: 0

摘要

波动性是金融市场的固有属性,通常表示为金融资产价格的波动程度。金融市场的波动性是指市场存在不确定性或风险。本文主要基于复杂网络和模糊逻辑理论研究金融市场波动。本文首先对复杂网络和模糊逻辑的理论构建进行了系统的组织和总结。在复杂网络方面,梳理了复杂网络的定义、常用函数(复杂网络的经典模型)的理论及求解方法。在模糊逻辑理论的构建中,从可量化的金融市场波动指标入手,讨论了实现波动率和隐含波动率的构建模型,讨论了隐含波动率和无模型模型的复杂网络模型。对理论构建方法进行了比较和分析。最后,总结了隐含波动率指数的理论构建方法,指出无模型隐含波动率作为市场波动率和风险度量指标的优势,它包含更有效的未来风险信息,并且基于隐含波动率。对指标和复杂网络模型的实证研究奠定了理论基础。实验数据表明,债券市场与外汇市场的相关系数波动最大,达到0.35;其次是股票市场和债券市场,大概是0.17;波动最小的股票市场和外汇市场在0.08左右。实验结果表明,基于复杂网络和模糊逻辑理论的金融市场波动率研究数据更为准确。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Financial market volatility based on complex network and fuzzy logic theory
Volatility is an inherent attribute of the financial market, which is usually expressed as the degree of volatility of financial asset prices. The volatility of the financial market means that there is uncertainty or risk in the market. This paper mainly studies financial market fluctuations based on complex networks and fuzzy logic theory. This article first systematically organizes and summarizes the theoretical construction of complex networks and fuzzy logic. In terms of complex networks, the definition of complex networks, the theory of commonly used functions (classical models of complex networks) and the solving methods are sorted out. In the construction of fuzzy logic theory, starting with quantifiable financial market volatility indicators, the construction models of realized volatility and implied volatility are discussed, and complex network models of implied volatility and model-free models are discussed. The theoretical construction methods were compared and analyzed. Finally, it summarizes the theoretical construction methods of implied volatility index and points out the advantages of model-free implied volatility as a market volatility and risk measurement index, which contains more effective future risk information and is based on implied volatility. The empirical research on indexes and complex network models has laid a theoretical foundation. Experimental data shows that the bond market and the foreign exchange market have the largest fluctuations in the correlation coefficient, reaching 0.35; followed by the stock market and the bond market, which is about 0.17; the stock market and foreign exchange market with the smallest fluctuations are about 0.08. The experimental results show that the financial market volatility research data based on complex networks and fuzzy logic theory is more accurate.
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来源期刊
CiteScore
2.80
自引率
23.10%
发文量
31
期刊介绍: The International Journal of Fuzzy Logic and Intelligent Systems (pISSN 1598-2645, eISSN 2093-744X) is published quarterly by the Korean Institute of Intelligent Systems. The official title of the journal is International Journal of Fuzzy Logic and Intelligent Systems and the abbreviated title is Int. J. Fuzzy Log. Intell. Syst. Some, or all, of the articles in the journal are indexed in SCOPUS, Korea Citation Index (KCI), DOI/CrossrRef, DBLP, and Google Scholar. The journal was launched in 2001 and dedicated to the dissemination of well-defined theoretical and empirical studies results that have a potential impact on the realization of intelligent systems based on fuzzy logic and intelligent systems theory. Specific topics include, but are not limited to: a) computational intelligence techniques including fuzzy logic systems, neural networks and evolutionary computation; b) intelligent control, instrumentation and robotics; c) adaptive signal and multimedia processing; d) intelligent information processing including pattern recognition and information processing; e) machine learning and smart systems including data mining and intelligent service practices; f) fuzzy theory and its applications.
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