Abstract
This research explores emerging trends in the global stock market after the COVID-19 pandemic, emphasizing economic recovery, investor behavior, market volatility, and regulatory influences. The pandemic resulted in significant financial turmoil, leading to both market crashes and subsequent rapid recoveries. This study investigates how markets have adapted to post-pandemic realities, analyzing the role of fiscal stimulus, monetary policies, and technological innovations in stabilizing and shaping stock market trends. A mixed-method research design is used, incorporating both qualitative and quantitative approaches. Macroeconomic indicators, financial statements, and stock indices—including S&P 500, Nasdaq, FTSE 100, NIFTY 50, and Nikkei 225—are analyzed to evaluate performance trends. Predictive models such as GARCH and ARIMA assess market volatility, while sentiment analysis using NLP examines investor behavior. Regression analysis identifies relationships between stock performance and key economic indicators like GDP growth, inflation, and interest rates. The study primarily relies on historical stock market data, which may not fully capture future uncertainties. Sentiment analysis, while insightful, may be influenced by biases in data interpretation. Additionally, predictive models such as ARIMA and GARCH estimate future trends but cannot account for unforeseen economic disruptions. The implications suggest a need for adaptive investment strategies, improved financial regulations, and enhanced risk assessment frameworks to strengthen market resilience in the face of uncertainty. Keywords: Stock Market Trends, Post-Pandemic Economy, Investment Behavior, Market Volatility, Behavioral Finance, Financial Technology, ESG Investments
Published Version
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