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将信息作为交易特征加以利用:基于因果关系对模拟数据和金融数据的分析

Exploitation of Information as a Trading Characteristic: A Causality-Based Analysis of Simulated and Financial Data.

作者信息

Kyrtsou Catherine, Mikropoulou Christina, Papana Angeliki

机构信息

Department of Economics, University of Macedonia, 54636 Thessaloniki, Greece.

EconomiX, University of Paris 10, 92001 Paris, France.

出版信息

Entropy (Basel). 2020 Oct 8;22(10):1139. doi: 10.3390/e22101139.

Abstract

In financial markets, information constitutes a crucial factor contributing to the evolution of the system, while the presence of heterogeneous investors ensures its flow among financial products. When nonlinear trading strategies prevail, the diffusion mechanism reacts accordingly. Under these conditions, information englobes behavioral traces of traders' decisions and represents their actions. The resulting effect of information endogenization leads to the revision of traders' positions and affects connectivity among assets. In an effort to investigate the computational dimensions of this effect, we first simulate multivariate systems including several scenarios of noise terms, and then we apply direct causality tests to analyze the information flow among their variables. Finally, empirical evidence is provided in real financial data.

摘要

在金融市场中,信息是推动系统演变的关键因素,而异质投资者的存在确保了信息在金融产品之间的流动。当非线性交易策略盛行时,扩散机制会相应地做出反应。在这些条件下,信息包含了交易者决策的行为痕迹并代表了他们的行动。信息内生化的最终结果导致交易者头寸的调整,并影响资产之间的连通性。为了研究这种效应的计算维度,我们首先模拟包含多种噪声项情景的多元系统,然后应用直接因果关系检验来分析其变量之间的信息流。最后,在真实金融数据中提供了实证证据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c120/7597289/057677df1366/entropy-22-01139-g001.jpg

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