Crash and Jump: The Impact of Social Media Coverage on Stock Prices in the Pakistan Stock Exchange
Abstract
This quantile regression model and event research show that social media sentiment influences the volatility and movement of stock prices on the Pakistan Stock Exchange (PSX). In order to gauge investor attitude regarding market movement during significant financial events, the study builds a daily sentiment index using Facebook posts and Twitter tweets. Stock prices are more impacted by negative sentiment than by positive sentiment, and market events associated with crises result in significant volatility and significant losses. The quantile regression model indicates that low-volatility stocks are less responsive to investor sentiment, whereas highly volatile stocks are more vulnerable. OLS robustness tests show that sentiment movements on social media can forecast declines in the stock market. These results imply that risk management and sentiment-based trading may enhance the ability of investors, market analysts, and financial regulators to make sound financial decisions. The findings demonstrate the growing prevalence of behavioral finance in stock market operations, particularly in developing markets like the PSX, where speculative trading and social media forums impact investor behavior. Future studies could enhance financial forecasts and risk assessment models by utilizing machine learning and big data analytics in sentiment analysis.
Keywords:
Social Media Sentiment, Quantile Regression, Idiosyncratic Volatility, Behavioral Finance, Pakistan Stock Exchange (PSX).
