• Siyona Patole
• Rosalyn Fernandes
• Sakshi Patil
• Vijaya Chimale

The financial market is highly dynamic, characterized by volatility and complex interdependencies between various factors. Predicting market trends accurately is crucial for making informed investment decisions. Machine Learning (ML) has emerged as a transformative technology, revolutionizing how financial market prediction and analysis are conducted. This research paper examines the effectiveness of ML in predicting financial markets, highlighting the methodologies used, applications in finance, advantages, disadvantages, and future research directions. The paper concludes that while ML offers significant potential for improving market predictions, challenges such as overfitting, data quality, and market unpredictability remain areas of concern.

Machine Learning (ML), Stock Price Prediction, Financial Market Analysis, Deep Learning, Long Short-Term Memory (LSTM) Networks, Support Vector Machines (SVM), Random Forests, Market Sentiment Analysis, Quantitative Finance, Algorithmic Trading, Time Series Forecasting, Risk Management, Reinforcement Learning, Predictive Modeling, Non-linear Relationships in Finance

"Effectiveness of Machine Learning in Financial Market Prediction and Analysis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 11, page no.c571-c578, November-2024, Available :http://www.jetir.org/papers/JETIR2411275.pdf

"Effectiveness of Machine Learning in Financial Market Prediction and Analysis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 11, page no. ppc571-c578, November-2024, Available at : http://www.jetir.org/papers/JETIR2411275.pdf