Capitalisation-weighted indexes provide the basis for passive investment strategies designed to capture market performance. However, these cap-weighted indexes are claimed to be sub-optimal because of their tendency to overweight overvalued shares and underweight undervalued shares. U.S. evidence suggests that fundamental indexes, which select, rank and weight stocks according to fundamental measures of size such as book value and revenue, outperform cap-weighted indexes. This study examines fundamental indexation in an Australian context over the period 1995 to 2006 and finds support for the U.S. results. However, we also find that the superiority of fundamental indexation is largely explained by its inherent bias towards value stocks, which raises the question as to whether a more overt value tilt may not provide a superior means for exploiting mispricings in markets.

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This paper is the first to conduct an event study on the market response to exploration, resource and reserve announcements made by mining firms. Results from an event study using a matched firm approach that suggest that markets react positively to both the exploration and the resource announcements at the time of their release but find information value in the reserve announcements possibly because all of the information in these announcements have been anticipated by the market. In fact, there is evidence to suggest a high level of anticipation of all three types of announcements which should be a matter of concern for the regulators. The other major surprising finding in the study is that in every instance the market seems to have been overly enthusiastic about the announcements, as share prices turns down almost immediately afterwards and trends downward for an extended time. This leaves open the question as to why does the market get them so horribly wrong.

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The study compares the performance of alternative implementations of both time-series and cross-sectional momentum strategies across 24 markets. We find that over our sample period, both types of momentum strategies generate positive returns under the majority of implementations evaluated but that time-series momentum is clearly superior. An important difference between the two momentum strategies is that with time-series momentum, the number of stocks included in the winner and loser portfolios vary with the state of the market. As a consequence, cross-sectional momentum digs deeper to select winning stocks when markets are weak and deeper to select losing stocks when markets are strong. As the information in the momentum signals is concentrated in the tails of the return distribution, it is not that surprising that momentum is best implemented using time-series momentum.

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We explore the rapidly changing social and news media landscape that is responsible for the dissemination of information vital to the efficient functioning of the financial markets. Using the sheer volume of social and news media activity, commonly known as buzz, we document three distinct regimes. We find that between 2011 and 2013 the news media coverage stimulates activity in social media. This is followed by a transition period of two-way causality. From 2016, however, changes in levels of social media activity seem to lead and generate news coverage volumes. We uncover similar evolution of lead-lag pattern between sentiment measures constructed from the tonality contained in textual data from social and news media posts. We discover that market variables exert stronger impact on investor sentiment than the other way around. We also find that return responses to social media sentiment almost doubled after the transition period, while return responses to news-based sentiment almost halved to its pre-transition level. The linkage between volatility and sentiment is much more persistent than that between returns and sentiment. Overall, our results suggest that social media is becoming the dominant media source.