Risk Analysis of Financial Time-series Using Multi-Scale Entropy

被引：0
|
作者：
Nobukawa, Sou [1 ]
Sekine, Tomoaki [1 ]
Chiba, Masaru [2 ]
Yamanishi, Teruya [2 ]
Nishimura, Haruhiko [3 ]
机构：
[1] Chiba Inst Technol, Dept Comp Sci, Chiba, Japan
[2] Fukui Univ Technol, Dept Management & Informat Sci, Fukui, Japan
[3] Univ Hyogo, Grad Sch Appl Informat, Kobe, Hyogo, Japan
来源：
2018 57TH ANNUAL CONFERENCE OF THE SOCIETY OF INSTRUMENT AND CONTROL ENGINEERS OF JAPAN (SICE) | 2018年
关键词：
Financial data; risk analysis; multi-scale entropy; VOLATILITY;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Recently, there are growing concerns about the time-scale dependency of complexity in financial data. To evaluate the risk of financial data, we adopt a multi-scale entropy analysis, which can measure complexity with time scale dependency, to time-series of TOPIX during 1/7/1992-6/1/2016. The results confirm that sample entropy exhibits higher value, especially with large-scale factor, near main financial incidents. Furthermore, we classify a multi-scale entropy profile against the time-scale by K-means. Furthermore, we confirm that the multi-scale entropy profile during main financial incidents belongs to the class with larger 1st component of principal component analysis. Therefore, we conclude that multi-scale entropy is a useful tool for evaluating the risk of financial data.
引用
收藏
页码：1023 / 1028
页数：6
相关论文
共 50 条
  • [1] Multi-Scale Entropy Analysis as a Method for Time-Series Analysis of Climate Data
    Balzter, Heiko
    Tate, Nicholas J.
    Kaduk, Joerg
    Harper, David
    Page, Susan
    Morrison, Ross
    Muskulus, Michael
    Jones, Phil
    [J]. CLIMATE, 2015, 3 (01) : 227 - 240
  • [2] Cumulative Tsallis entropy based on multi-scale permuted distribution of financial time series
    Zhang, Yali
    Shang, Pengjian
    He, Jiayi
    Xiong, Hui
    [J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2020, 548
  • [3] Cumulative Tsallis entropy based on multi-scale permuted distribution of financial time series
    Zhang, Yali
    Shang, Pengjian
    He, Jiayi
    Xiong, Hui
    [J]. Physica A: Statistical Mechanics and its Applications, 2021, 548
  • [4] Multi-Scale Shapelets Discovery for Time-Series Classification
    Cai, Borui
    Huang, Guangyan
    Xiang, Yong
    Angelova, Maia
    Guo, Limin
    Chi, Chi-Hung
    [J]. INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING, 2020, 19 (03) : 721 - 739
  • [5] Multi-Scale Event Detection in Financial Time Series
    de Salles, Diego Silva
    Gea, Cristiane
    Mello, Carlos E.
    Assis, Laura
    Coutinho, Rafaelli
    Bezerra, Eduardo
    Ogasawara, Eduardo
    [J]. COMPUTATIONAL ECONOMICS, 2024,
  • [6] Multi-scale description and prediction of financial time series
    Nawroth, A. P.
    Friedrich, R.
    Peinke, J.
    [J]. NEW JOURNAL OF PHYSICS, 2010, 12
  • [7] Clustering framework based on multi-scale analysis of intraday financial time series
    Shi, Yong
    Li, Bo
    Du, Guangle
    Dai, Wei
    [J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2021, 567
  • [8] A multi-scale smoothing kernel for measuring time-series similarity
    Troncoso, A.
    Arias, M.
    Riquelme, J. C.
    [J]. NEUROCOMPUTING, 2015, 167 : 8 - 17
  • [9] Wavelet-Based Multi-Scale Entropy Analysis of Complex Rainfall Time Series
    Chou, Chien-Ming
    [J]. ENTROPY, 2011, 13 (01) : 241 - 253
  • [10] Multi-scale Temporal Memory for Clinical Event Time-Series Prediction
    Lee, Jeong Min
    Hauskrecht, Milos
    [J]. ARTIFICIAL INTELLIGENCE IN MEDICINE (AIME 2020), 2020, : 313 - 324
12345