Assessing the Influence of Investor Sentiment on the Performance of the Stock Prices: Analyzing Stock Returns and Volatility During the COVID-19 Pandemic and Periods of Market Fluctuations | ||||
| MSA-Management Sciences Journal | ||||
| Volume 3, Issue 2, April 2024, Page 76-119 PDF (742.08 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/msamsj.2024.263215.1051 | ||||
 View on SCiNiTO | ||||
| Author | ||||
Sarah Sobhy Hassan  
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| Finance and investment, Management sciences, MSA university, Giza, Egypt | ||||
| Abstract | ||||
| The primary objective of this study is to examine how investor sentiment affects stock market performance, with a particular focus on two indicators: stock returns and stock market volatility. The analysis takes into account the impact of the coronavirus pandemic and takes into account two market conditions: upside (bullish) and downside (bearish). Monthly closing prices for ten sector indices were analysed, including information technology, healthcare, financials, consumer credit, telecommunications services, industrials, energy, utilities, real estate, and materials. The study used three GARCH models (GARCH, GJR-GARCH, and E-GARCH) to predict the volatility of these sector indices and understand the impact of investor sentiment. The results indicate a negative impact of investor sentiment on stock returns and stock market volatility in most sectors. The coronavirus pandemic is having a positive impact on the relationship between investor sentiment, volatility, and stock returns. In addition, the results reveal a bidirectional link between investor sentiment and stock volatility across all US sectors. Regarding the market situation, it has been shown that in emerging markets, investor sentiment has a negative impact on volatility and stock returns in the majority of sectors. However, in bear markets, the effect of investor sentiment on stock market returns and volatility is positive. | ||||
| Keywords | ||||
| Stock prices; investor sentiment; stock returns; volatility; GARCH models | ||||
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