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Bayesian Extreme Value Optimization Algorithm: Application to Forecast the Rubber Futures in Futures Exchange Markets

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Structural Changes and their Econometric Modeling (TES 2019)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 808))

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Abstract

This paper statistically investigated the extreme event statistics, which is valid across multiple time-period trends. The Non-stationary Extreme Value Analysis (NEVA) based on Bayesian inference was conducted. The series of RSS3 future contracts traded in Japan’s TOCOM, Singapore’s SICOM, Chinese’s SHFE and Thailand’s AFET were observed during the period 1990 to 2018. By providing posterior probability intervals (5% and 95% quantiles), the NEVA offers the 30-year predictions of the four future markets, which are able to reliably describe extremes and their future contracts levels. The scenarios of the RSS3 futures exchanges inform that TOCOM provides explicitly evidence for of long-run constancy, while, SICOM, SHFE and AFET seem to be higher price volatility. Therefore, the unbiased prediction tool, especially for the RSS3 futures contracts, is very crucial for stakeholders to hedge against price uncertainty.

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Author information

Authors and Affiliations

  1. Faculty of Economics, Prince of Songkla University, Songkhla, Thailand

    Arisara Romyen

  2. Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand

    Arisara Romyen, Satawat Wannapan & Chukiat Chaiboonsri

  3. Puey Ungphakorn Center of Excellence in Econometrics, Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand

    Chukiat Chaiboonsri

Authors
  1. Arisara Romyen
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  2. Satawat Wannapan
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  3. Chukiat Chaiboonsri
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Corresponding author

Correspondence to Arisara Romyen .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Texas at El Paso, El Paso, TX, USA

    Vladik Kreinovich

  2. Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand

    Songsak Sriboonchitta

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Romyen, A., Wannapan, S., Chaiboonsri, C. (2019). Bayesian Extreme Value Optimization Algorithm: Application to Forecast the Rubber Futures in Futures Exchange Markets. In: Kreinovich, V., Sriboonchitta, S. (eds) Structural Changes and their Econometric Modeling. TES 2019. Studies in Computational Intelligence, vol 808. Springer, Cham. https://doi.org/10.1007/978-3-030-04263-9_46

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