BEHAVIORAL FINANCE IN EMERGING MARKETS: TOWARDS AN INVESTOR SENTIMENT INDEX FOR INDIA AND ARGENTINE SOVEREIGN BONDS
1Prof Sebastian Laza, 2Prof Dr S. Sandhya, 3Prof Dr J Satpathy
1University of Cuyo, Mendoza, Agrentina
2Professor and Research Head, NITTE School of Management, Bengaluru, India
3Professor Emeritus, Poornaprajna Institute of Management, Udipi, India
Abstract: This paper explores the critical role of investor sentiment in understanding market behavior, with a particular focus on emerging markets, specifically India and Argentine. Drawing on the theory of behavioral finance, we examine how sentiment-driven factors—such as emotions, cognitive biases, and social influences—shape investor decision-making in these volatile markets. By analyzing both theoretical perspectives and real-world market data, we highlight how investor sentiment can lead to market inefficiencies, increased volatility, and sudden shifts in asset prices. The paper also delves into the potential of artificial intelligence (AI) to enhance sentiment analysis, offering a more accurate and timely understanding of market dynamics. Through AI techniques such as natural language processing (NLP) and machine learning, investors can better gauge sentiment trends and predict market movements, providing a competitive edge in emerging economies. The case studies of India and Argentine illustrate the complex interplay between sentiment and market behavior in environments characterized by political instability, economic uncertainty, and external shocks. Finally, the paper discusses the possibility of building an Investor Sentiment Index for India and Argentine Sovereign Bonds, and the implications for investors and policymakers in managing sentiment-induced volatility, as areas for future research in the integration of AI and behavioral finance in emerging markets.
Key Words: Behavioral Finance, Investor Sentiment, Artificial Intelligence, and Market Behavior