广义可见曲率:加密货币泡沫识别和价格趋势预测指标

IF 6.7 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Decision Support Systems Pub Date : 2024-08-21 DOI:10.1016/j.dss.2024.114309
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引用次数: 0

摘要

我们提出了一种基于对数价格时间序列的新型曲率指标,该指标能捕捉趋势、加速度和波动性之间的相互作用,可用于量化风险和改进交易策略。我们将其用于诊断加密货币价格时间序列中的爆炸性泡沫行为,并为即将发生的市场变化或波动性增加提供预警信号。这大大改进了标准统计测试,如广义上扩增迪基-富勒(GSADF)和后向 SADF 测试。此外,将我们基于曲率的指标作为一个特征纳入光梯度提升机,还增强了它的预测能力,具体体现在分类准确性和交易性能上。
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Generalized visible curvature: An indicator for bubble identification and price trend prediction in cryptocurrencies

We propose a novel curvature-based indicator constructed on log-price time series that captures an interplay between trend, acceleration, and volatility found relevant to quantify risks and improve trading strategies. We apply it to diagnose explosive bubble-like behaviors in cryptocurrency price time series and provide early warning signals of impending market shifts or increased volatility. This improves significantly on standard statistical tests such as the Generalized Supremum Augmented Dickey–Fuller (GSADF) and the Backward SADF tests. Furthermore, the incorporation of our curvature-based indicator as a feature into the Light Gradient Boosting Machine enhances its predictive capabilities, as measured by classification accuracy and trading performance.

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来源期刊
Decision Support Systems
Decision Support Systems 工程技术-计算机:人工智能
CiteScore
14.70
自引率
6.70%
发文量
119
审稿时长
13 months
期刊介绍: The common thread of articles published in Decision Support Systems is their relevance to theoretical and technical issues in the support of enhanced decision making. The areas addressed may include foundations, functionality, interfaces, implementation, impacts, and evaluation of decision support systems (DSSs).
期刊最新文献
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