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量子波希姆启发潜力模型非高斯时间序列及其在金融市场的应用
Reza Hosseini1, Samin Tajik2, Zahra Koohi Lai3
1Department of Physics, Shahid Beheshti University, Evin, Tehran 1983969411, Iran.
Entropy (Basel, Switzerland)
|July 29, 2023
概括
量子建模揭示了时间序列中的罕见事件创造了潜在的障碍. 这种波希姆力学方法,使用多分形随机步行,准确地捕获非高斯行为,与标准统计不同.
科学领域:
- 量子力学就是量子力学.
- 时间序列分析时间序列分析.
- 金融建模金融建模
背景情况:
- 高斯统计低估了时间序列中的罕见事件.
- 事件之间的强合导致非高斯概率密度.
- 了解罕见事件对于准确的时间序列分析至关重要.
研究的目的:
- 使用量子测量研究罕见事件对时间序列概率密度的影响.
- 模型非高斯时间序列行为及其量子力学含义.
- 将量子潜力分析应用于金融市场.
主要方法:
- 实现基于波希姆力学的量子建模.
- 利用多分形随机步行 (MRW) 方法来建模非高斯时间序列.
- 分析了MRW参数λ在衍生量子潜力的作用.
- 标普金融市场时间序列的计算量子潜力.
主要成果:
- 时间序列中的罕见事件可以在量子潜力的高频区域产生潜在障碍.
- 波赫姆量子分析表明,量子潜力的行为受到非高斯度 (λ) 的显著影响.
- 衍生的量子潜能对罕见事件表现出明显的特征,偏离高斯假设.
- 对于标准普尔金融市场数据,量子潜力已经成功计算出来,证实了罕见事件的存在.
结论:
- 波希姆力学和量子潜能为分析罕见事件的时间序列提供了强大的框架.
- 多分体随机走路参数λ是确定量子潜力的结构和罕见事件的影响的关键.
- 量子潜力分析提供了对金融市场动态的洞察,突出了由于罕见事件而与高斯行为偏差的偏差.
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