QFRNA_SH | Quantitative Financial Risk Network Analysis with Sentiment and Herd Behaviour Measures

Summary
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.
Unfold all
/
Fold all
More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/897277
Start date: 01-01-2021
End date: 31-12-2022
Total budget - Public funding: 174 806,40 Euro - 174 806,00 Euro
Cordis data

Original description

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.

Status

CLOSED

Call topic

MSCA-IF-2019

Update Date

28-04-2024
Images
No images available.
Geographical location(s)
Structured mapping
Unfold all
/
Fold all
Horizon 2020
H2020-EU.1. EXCELLENT SCIENCE
H2020-EU.1.3. EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions (MSCA)
H2020-EU.1.3.2. Nurturing excellence by means of cross-border and cross-sector mobility
H2020-MSCA-IF-2019
MSCA-IF-2019