Papers by Shaikh M A Sarfarazurrehman
Journal of Computational Analysis and Applications, 2023
The real estate sector is a fundamental pillar of global economic stability, yet it remains highl... more The real estate sector is a fundamental pillar of global economic stability, yet it remains highly vulnerable to macroeconomic fluctuations and market crashes. Traditional risk assessment methodologies often fail to account for the complex, non-linear relationships between economic indicators and real estate dynamics. With advancements in artificial intelligence (AI) and machine learning, predictive modeling has emerged as a powerful tool for forecasting real estate market crashes. This research explores AI-driven predictive techniques by analyzing key macroeconomic indicators such as GDP growth, interest rates, inflation, unemployment, foreign direct investment, and government regulations. Using machine learning models such as time-series forecasting, deep learning, and feature engineering, the study constructs a framework to improve predictive accuracy and early warning signals for market instability. Empirical findings suggest that AI models outperform traditional forecasting methods, offering valuable insights for investors and policymakers. This study concludes with strategic recommendations for integrating AI-driven analytics into real estate investment risk management.
Journal of Information Systems Engineering and Management, 2025
The integration of Artificial Intelligence (AI) into financial risk management has opened new ave... more The integration of Artificial Intelligence (AI) into financial risk management has opened new avenues for enhancing the resilience of equity portfolios, particularly during extreme market events such as pandemics and financial crises. This paper proposes an AI-based model for dynamic risk management in equity portfolios, aiming to address the limitations of traditional static risk models by incorporating advanced machine learning techniques and real-time data analysis. The model leverages diverse data sources, including market indicators, economic indicators, and alternative data, to predict and manage risks effectively. Through a comprehensive literature review and methodological framework, this study highlights the potential of AI in transforming risk management practices and improving portfolio performance during periods of heightened market volatility
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Papers by Shaikh M A Sarfarazurrehman