TITLE:
Analysis of Hidden Markov Model for Financial Forecasting in Cryptocurrency
AUTHORS:
Emmanuel Nwabueze Ekwonwune, DonPatrick Uzondu Onwusiribe, Abraham Oghenemega Ovwonuri, Chinomso Daniel Okoronkwo
KEYWORDS:
Model, Markov Model, Crypto, Cryptocurrency, Financial Forecasting, Market and Finance
JOURNAL NAME:
Intelligent Information Management,
Vol.18 No.6,
November
9,
2026
ABSTRACT: This work is aimed at developing hidden Markov models for financial forecasting in cryptocurrency. The motivation is due to the risks associated with cryptocurrency, such as extreme market volatility and unpredictability, data quality and reliability issues, lack of standardization, the roles of some malicious actors, data security breaches (unauthenticated signal intrusion) into the most vulnerable database(s) or information systems, the use of rogue algorithms, privacy leakages, service providers and clients’ rights abuse, competitive aggressiveness, and an unregulated atmosphere, etc. This work aims to develop and evaluate a comprehensive HMM-based framework for cryptocurrency forecasting and risk management. It aims to maximize the facilities of the internet and artificial intelligence tools and integrate these resources with advanced machine learning techniques, which entails using a Hidden Markov Model to provide a robust risk management framework that will be essential for navigating the complexities of the cryptocurrency markets. The methodology adopted is a combination of Structured Systems Analysis and Design (SSADM) and Object-Oriented Analysis and Design (OOADM) Methodologies, which entails several steps such as problem detection, feasibility studies, analysis, design, implementation, and documentation. Finally, an interactive (user-friendly) software will be developed that will be able to provide the optimal solution: Hidden Markov Model for Financial Forecasting in Cryptocurrency (HMMFFIC). To achieve these, the following programming languages will be involved, namely: HTML (Hypertext Markup Language will be used for the layouts), CSS (Cascading Style Sheets for styling and beautification of the pages), Python (Frontend Programming for functionality and processing), PHP (Personal Home Page, or Hypertext Preprocessor for backend), and MySQL (for the database/cloud architectural design). The deployment of the optimal solution will provide the countermeasures needed to end the identified vulnerabilities and eliminate potential threats within the system and in the future.