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

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 cond...

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Main Authors: Catherine Kyrtsou, Christina Mikropoulou, Angeliki Papana
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Entropy
Subjects:
Online Access:https://www.mdpi.com/1099-4300/22/10/1139
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spelling doaj-44b85064ea9844d989ef668c8c583c492020-11-25T03:43:15ZengMDPI AGEntropy1099-43002020-10-01221139113910.3390/e22101139Exploitation of Information as a Trading Characteristic: A Causality-Based Analysis of Simulated and Financial DataCatherine Kyrtsou0Christina Mikropoulou1Angeliki Papana2Department of Economics, University of Macedonia, 54636 Thessaloniki, GreeceDepartment of Economics, University of Macedonia, 54636 Thessaloniki, GreeceDepartment of Economics, University of Macedonia, 54636 Thessaloniki, GreeceIn 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.https://www.mdpi.com/1099-4300/22/10/1139information endogenizationnonlinear connectivitydirect causalitystock portfolios
collection DOAJ
language English
format Article
sources DOAJ
author Catherine Kyrtsou
Christina Mikropoulou
Angeliki Papana
spellingShingle Catherine Kyrtsou
Christina Mikropoulou
Angeliki Papana
Exploitation of Information as a Trading Characteristic: A Causality-Based Analysis of Simulated and Financial Data
Entropy
information endogenization
nonlinear connectivity
direct causality
stock portfolios
author_facet Catherine Kyrtsou
Christina Mikropoulou
Angeliki Papana
author_sort Catherine Kyrtsou
title Exploitation of Information as a Trading Characteristic: A Causality-Based Analysis of Simulated and Financial Data
title_short Exploitation of Information as a Trading Characteristic: A Causality-Based Analysis of Simulated and Financial Data
title_full Exploitation of Information as a Trading Characteristic: A Causality-Based Analysis of Simulated and Financial Data
title_fullStr Exploitation of Information as a Trading Characteristic: A Causality-Based Analysis of Simulated and Financial Data
title_full_unstemmed Exploitation of Information as a Trading Characteristic: A Causality-Based Analysis of Simulated and Financial Data
title_sort exploitation of information as a trading characteristic: a causality-based analysis of simulated and financial data
publisher MDPI AG
series Entropy
issn 1099-4300
publishDate 2020-10-01
description 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.
topic information endogenization
nonlinear connectivity
direct causality
stock portfolios
url https://www.mdpi.com/1099-4300/22/10/1139
work_keys_str_mv AT catherinekyrtsou exploitationofinformationasatradingcharacteristicacausalitybasedanalysisofsimulatedandfinancialdata
AT christinamikropoulou exploitationofinformationasatradingcharacteristicacausalitybasedanalysisofsimulatedandfinancialdata
AT angelikipapana exploitationofinformationasatradingcharacteristicacausalitybasedanalysisofsimulatedandfinancialdata
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