| dc.description.abstract | This study examines sentiment from routine financial news and outlines the impact of the media content on three main index futures contracts of Hong Kong Exchanges and Clearing Limited, Bursa Malaysia and Singapore Exchange. The sample selection is based on high a percentage of English usage, thus enabling cross-country comparison. I generate several news factors from routine financial news and find that factors that represent pessimistic market sentiment are more prevalent. Highly pessimistic news factors (Pessimism, Negative and Weak) predict lower returns on the same day, while the negative impact will reverse within the next five days. The finding is consistent with the noise trader theory that investors initially overreact to negative market news and drive the price lower, before the price corrects itself. Since investors are only obligated to pay maintenance margin when trading futures contracts, the trading strategy based on this finding becomes more economically significant compared to paying full price in the spot market. The second part of this thesis examines the role of sentiment in predicting the mean-variance relationship. I argue that sentiment will affect returns volatility. Risk-averse rational investors require higher returns for holding risky assets, which implies positive mean-variance relationships. During a high sentiment period, noise traders dominate the trading activities, leading to a weaker mean-variance trade off. Evidence points to negative mean-variance relationships during a high sentiment period, but the results are mixed during a low sentiment period. The finding suggests that sentiment can be incorporated into the index futures pricing model, through its interaction with returns volatility. | en_US |
