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• [7]
  

  2024 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2990759

  fHMM: Hidden Markov Models for Financial Time Series in R
  Oelschläger L, Adam T, Michels R (2024)
  Journal of Statistical Software 109(9): 1-25.

  PUB | DOI | WoS
   
• [6]
  

  2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2984297

  Bayesian probit models for preference classification: an analysis of chess players’ propensity for risk-taking
  Oelschläger L, Bauer D (2023)
  In: Proceedings of the 37th International Workshop on Statistical Modelling. TU Dortmund University (Ed); 549-553.

  PUB | Download (ext.)
   
• [5]
  

  2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2957037

  Detecting bearish and bullish markets in financial time series using hierarchical hidden Markov models
  Oelschläger L, Adam T (2021)
  Statistical Modelling 23(2): 107-126.

  PUB | DOI | WoS
   
• [4]
  

  2021 | Kurzbeitrag Konferenz / Poster | PUB-ID: 2951073

  Bayes Estimation of Latent Class Mixed Multinomial Probit Models
  Oelschläger L, Bauer D (2021)
  Presented at the TRB Annual Meeting 2021, Online.

  PUB | PDF
   
• [3]
  

  2021 | Wissenschaftliche Software | PUB-ID: 2982764

  fHMM: fitting hidden Markov models to financial data (R package)
  Oelschläger L, Adam T, Michels R (2021)
  CRAN.

  PUB
   
• [2]
  

  2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982766

  Hidden Markov models for multi-scale time series: an application to stock market data
  Adam T, Oelschläger L (2020)
  In: Proceedings of the 35th International Workshop on Statistical Modelling. Part I. Irigoien I, Lee D-J, Martínez-Minaya J, Rodríguez-Álvarez MX (Eds); Bilbao: Universidad del País Vasco: 2-7.

  PUB
   
• [1]
  

  2020 | Konferenzbeitrag | PUB-ID: 2951071

  Bayes Estimation of Latent Class Mixed Multinomial Probit Models
  Oelschläger L, Bauer D (2020)
  Presented at the TRB Annual Meeting 2021.

  PUB