Measuring investors' emotions using econometric models of trading volume of stock exchange indexes

Abstract

Traditional finance explains all human activity on the ground of rationality and suggests all decisions are rational because all current information is reflected in the prices of goods. Unfortunately, the development of information technology and a growth of demand for new, attractive possibilities of investment caused the process of searching new, unique signals supporting investment decisions. Such a situation is similar to risk-taking, so it must elicit the emotional reactions of individual traders. The paper aims to verify the question that the market risk may be the determinant of traders' emotions, and if volatility is a useful tool during the investment process as the measure of traders' optimism, similarly to Majewski's work (2019). Likewise, various econometric types of models of estimation of the risk parameter were used in the research: Classical linear using OLS, general linear using FGLS, and GARCH(p, q) models using maximum likelihood method. Hypotheses were verified using the data collected from the most popular world stock exchanges: New York, Frankfurt, Tokyo, and London. Data concerned stock exchange indexes such as SP500, DAX, Nikkei, and UK100.