Quantitative financial risk network analysis with sentiment and herd behaviour measures
Sentiment drives the stock market (Shiller, 2000). Over-optimistic and over-pessimistic emotions can lead to great mispricing and excess volatility. The question is no longer whether investor sentiment affects stock prices, but rather how to measure investor sentiment and quantify its effects (Baker and Wurgler, 2007). (1) The proposal firstly plans to improve upon existing measures of investor sentiment by combining financial proxies and textual variables. Then it tries to calibrate the option-pricing model with the investor sentiment measure incorporated to achieve precise pricing. (2) While there has been much work on investor sentiment, there is a lacuna in research that explores sentiment network, in particular the interdependencies of the sentiment indices and their relationship with equity returns. The researcher aims to explore the interconnectedness of sentiment measures among different stocks and identifies which stock plays a crucial role by proposing an innovative semiparametric tail event driven network. (3) The interdependencies and co-movements of investor emotions may lead to herd behaviour in the financial market. One of the difficulties lies in differentiating between a rational reaction to changes in fundamental values and irrational herd behaviour. The proposal aims to detect and interpret the phenomenon considering macroeconomic signals, buy or sell transaction behaviour and investor sentiment. The overall proposal is, therefore, original not just because of employing new investor sentiment measures but for the development of new econometric methods in the first place. Moreover, it potentially contributes to inclusive, innovative and reflective societies in Europe by supporting financial decision-making processes and managing risks for investors and institutions.