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Synapse
May 20, 2026Open Access

A Time Series Volatility Model for All Share Index Returns Using Markov Switching Autoregression

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Authors

IOIfeoma Chinyere Okonjo

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Overview

Randomized trial investigates volatility in all share index returns, suggesting improved forecasting methods.

Key Points

  • The research aims to explore Markov switching autoregressive models for better predicting all share index returns.
  • Data collected on all share index returns from the Nigeria Stock Exchange (Jan 1985 - Dec 2019).
  • Estimated parameters and computed properties of the Markov switching autoregressive model.
  • Evaluated goodness of fit and autocorrelation measures.
  • The MS (3)-AR (3) model was identified as appropriate and robust for predicting index returns.
  • Model demonstrated efficiency in forecasting over the sampled period.
  • Autocorrelation measures indicated strong predictive power.

Cite This Study

Ifeoma Chinyere Okonjo (2026) studied this question.

synapsesocial.com/papers/6a0d5051f03e14405aa9bf84https://doi.org/10.5281/zenodo.20269781
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