Realtime estmation of the degree of market efficiency using variable weighted sample entropy

Koichi Sugisaki, Hiromitsu Ohmori

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Recently, the complex features of financial time series have been studied using a variety of methods developed in econophysics. These analyses of extensive financial data have empirically pointed to the breakdown of the efficient market hypothesis(EMH), in particular the weak-form of EMH. Sample Entropy(SampEn) can be used to quantify the randomness in the time series. In the financial time series analysis, the SampEn can quantify the degree of market efficiency. In this paper, we investigated the degree of market efficiency of the US market and Asian market around the epoch of Black Monday and Asian Currency Crisis respectively by using variable weighted SampEn algorithm.

Original languageEnglish
Title of host publicationProceedings of SICE Annual Conference 2008 - International Conference on Instrumentation, Control and Information Technology
Pages1415-1418
Number of pages4
DOIs
Publication statusPublished - 2008 Dec 1
EventSICE Annual Conference 2008 - International Conference on Instrumentation, Control and Information Technology - Tokyo, Japan
Duration: 2008 Aug 202008 Aug 22

Publication series

NameProceedings of the SICE Annual Conference

Other

OtherSICE Annual Conference 2008 - International Conference on Instrumentation, Control and Information Technology
CountryJapan
CityTokyo
Period08/8/2008/8/22

Keywords

  • Market crash
  • Market efficiency
  • Real-time
  • Sample entropy

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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    Sugisaki, K., & Ohmori, H. (2008). Realtime estmation of the degree of market efficiency using variable weighted sample entropy. In Proceedings of SICE Annual Conference 2008 - International Conference on Instrumentation, Control and Information Technology (pp. 1415-1418). [4654880] (Proceedings of the SICE Annual Conference). https://doi.org/10.1109/SICE.2008.4654880