• Manoj B. Bhatkar
• Dr. Prashant M. Yawalkar

The exponential growth in data complexity and volume has pushed classical systems to their limits. Quantum computing, with its inherent parallelism and ability to handle high-dimensional spaces, offers a potential solution. Yet, the current state of quantum hardware—limited by qubit coherence, error rates, and scalability—necessitates a hybrid approach that integrates classical and quantum systems. Hybrid quantum-classical methods have emerged as a promising approach to tackle complex predictive analysis tasks, leveraging the computational advantages of quantum systems while mitigating their current limitations through classical computing frameworks. This paper provides a comprehensive review of recent advancements in hybrid quantum-classical algorithms, their applications in predictive analysis, and the challenges associated with their implementation. We explore key methodologies, such as variational quantum algorithms, quantum machine learning, and hybrid optimization techniques, highlighting their potential to revolutionize fields such as finance, healthcare, and materials science. Finally, we discuss the current limitations of quantum hardware and software and outline future research directions to bridge the gap between theoretical promise and practical applicability. This paper reviews hybrid quantum-classical methods, which combine the strengths of both paradigms to address predictive analysis challenges. We focus on their theoretical foundations, practical implementations, and applications. By examining the current state of the art, we aim to provide a roadmap for researchers and practitioners interested in leveraging these methods.

Stock price prediction, quantum machine learning, quantum-classical hybrid algorithms, variational quantum circuits, quantum feature maps.

"A Review of Hybrid Quantum-Classical Methods for Enhanced Accuracy in Stock Price Prediction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 8, page no.195-201, August-2025, Available :http://www.jetir.org/papers/JETIRHA06027.pdf

"A Review of Hybrid Quantum-Classical Methods for Enhanced Accuracy in Stock Price Prediction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 8, page no. pp195-201, August-2025, Available at : http://www.jetir.org/papers/JETIRHA06027.pdf