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Research & Reviews: Discrete Mathematical Structures Original Research

Analysis of Gold Price Trend Using the Hidden Markov Model

  1. Sarode Rekha (Short-Term Post Doctoral Fellow), Indian Statistical Institute, Theoretical Statistics and Mathematics Unit,
  2. Thirupathi Rao Padi Department of Statistics, Pondicherry University
  3. Raj Kumar Sahoo Department. of Statistics, Utkal University

Abstract

This study aims to analyze the behavior of gold prices in India through a two-state Hidden Markov Model (HMM). We first formulated crucial parameters, such as the Transition Probability Matrix (TPM), Initial Probability Vector (IPV), and Emission Probability Matrix (EPM). Subsequently, we constructed a hidden Markov probability distribution and evaluated Pearson’s coefficients to gauge the correlations separately for each state. The goodness of fit of the developed model was assessed using the chi-square test. Real-time data from the internet, particularly from the Bombay Stock Exchange (BSE) for hidden states and gold prices in India for emission states, were utilized for the model application. We categorized states as incremental or decrement based on the positivity of returns for both the BSE and gold prices. Utilizing the model, we computed probability distributions and statistical measures and validated its performance by gathering future data from various online sources. This study employs an HMM to comprehend the dynamics of gold prices in India, establish meaningful relationships, and validate predictive capabilities using real-time data. In saummary, this study utilizes an HMM to explore the dynamics of gold prices in India. By identifying significant relationships and validating the model's predictions using real-time data, this study offers valuable insights into market behavior and presents a reliable tool for forecasting future gold price trends.

Keywords

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