Proposal of Classification Method of Time Series Data in International Emissions Trading Market Using Agent-based Simulation

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  • NAKADA Tomohiro
    Department of Electrical Engineering, Matsue College of Technology
  • TAKADAMA Keiki
    Department of Informatics, The University of Electro-Communications
  • WATANABE Shigeyoshi
    Department of Information and Communication Engineering, The University of Electro-Communications

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Other Title
  • エージェントベースシミュレーションを用いた国際排出権取引市場における時系列データの分類法の提案
  • エージェントベースシミュレーション オ モチイタ コクサイ ハイシュツケン トリヒキ シジョウ ニ オケル ジケイレツ データ ノ ブンルイホウ ノ テイアン

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This paper proposes the classification method using Bayesian analytical method to classify the time series data in the international emissions trading market depend on the agent-based simulation and compares the case with Discrete Fourier transform analytical method. The purpose demonstrates the analytical methods mapping time series data such as market price. These analytical methods have revealed the following results: (1) the classification methods indicate the distance of mapping from the time series data, it is easier the understanding and inference than time series data; (2) these methods can analyze the uncertain time series data using the distance via agent-based simulation including stationary process and non-stationary process; and (3) Bayesian analytical method can show the 1% difference description of the emission reduction targets of agent.

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