Stochastic Volatility Models (SVM) in the Analysis of Drought Periods

  • Jorge Alberto Achcar
  • Roberto Molina de Souza
  • Emílio Augusto Coelho-Barros


In the last few years, very atypical behavior of rain precipitation has been observed globally that may be attributed to climate changes. In this chapter, we approach the analysis of rain precipitation for a large city in Brazil: Campinas located in the southeast region of Brazil, São Paulo State, considering the time series of SPI (standard precipitation Index) measures (1, 3, 6, and 12-month timescales) ranging from January 01, 1947 to May 01, 2011. The present authors have previously used nonhomogeneous Poisson process approach (Achcar et al. Environ Ecol Stat 23:405–419, 2016, [1]) to analyze this data set. However, the analysis in this chapter uses a simpler methodology based on recently introduced SV (stochastic volatility) model (Ghysels, Statistical methods on finance, 1996, [9]) under a Bayesian approach. An excellent fit of the model for the data set is seen that shows some periods of great volatility, confirming atypical behavior for the rain precipitation.


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Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  • Jorge Alberto Achcar
    • 1
    • 2
  • Roberto Molina de Souza
    • 3
  • Emílio Augusto Coelho-Barros
    • 3
  1. 1.Medical SchoolUniversity of São PauloRibeirão PretoBrazil
  2. 2.Department of Social MedicineFMRP University of São PauloMonte Alegre Ribeirão PretoBrazil
  3. 3.Federal Technological University of ParanáCornélio ProcópioBrazil

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