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Codes for "Option Pricing and Hedging for Discrete Time Autoregressive Hidden Markov Model"

https://arxiv.org/abs/1707.02019

Modeling Asset Returns

the following models are available for modelisation

  • HMM (hidden markov model)
  • ARHMM (autoregressive hidden markov model)
  • VHMM (multidimentional hidden hidden markov model)
  • VARHMM (multidimentional autoregressive hidden hidden markov model)

Est<model>.m for calibrating the models
Gof<model>.m for Goodness-of-fit test
Sim<model>.m for simulation

to simulate some processes, calibrate the different models and run Godness-of-fit test, run:

simulate_and_calibrate.m

Optimal Hedging

the following models are available for hedging:

  • Delta-Hedging
    (HedgingError_DH.m)
  • Optimal Hedging with Gaussian Returns
    (HedgingError_Gaussian.m OR HedgingGaussian.m + Hedging_Error_Gaussian_ac.m
  • Optimal Hedging with HMM Returns and Semi-exact approximation
    (HedgingError_HMM.m OR HedgingHMM.m + Hedging_Error_HMM_ac.m
  • Optimal Hedging with HMM Returns and Monte Carlo approximation
    (HedgingError_HMM_MC.m OR HedgingHMM.m + Hedging_Error_HMM_ac.m
  • Optimal Hedging with ARHMM Returns and Semi-exact approximation
    (HedgingError_ARHMM.m OR HedgingARHMM.m + Hedging_Error_ARHMM_ac.m
  • Optimal Hedging with ARHMM Returns and Monte Carlo approximation
    (HedgingError_ARHMM_MC.m OR HedgingARHMM.m + Hedging_Error_ARHMM_ac.m

to price an option and hedge it under multiple simulations, run:

simulate_and_hedge.m

this script will reproduce Figure 8:

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Codebase for "Option Pricing and Hedging for Discrete Time Autoregressive Hidden Markov Model"

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