قدرت بد: تأثیر منفی اطلاعیه تمایلات مصرف کننده در استرالیا بر بازده سهام

This paper examines the equity market reaction to the monthly release of Australian consumer sentiment news. Our results indicate that consumer sentiment has valuable information content. Further, we document a version of the “negativity effect” (from the psychology literature) in which, upon announcement of bad (good) sentiment news, the equity market experiences a significant negative (no) announcement day effect. Notably, we find that the market recovers from the bad news shock relatively quickly post-announcement. The results are robust to a broad range of additional tests.

The issue of whether sentiment affects stock prices is enduring and has taken on renewed significance in the context of dramatic rises and falls observed in the stock market over the past decade. Earlier studies have explored the impact of United States (US) sentiment measures on various securities such as ADRs (Grossmann et al., 2007), closed-end country funds (Bodurtha et al., 1995), and individual stocks (Baker and Wurgler, 2006). We contribute to this literature by exploring the aggregate Australian stock market reaction to periodic announcements of consumer sentiment from the Westpac-Melbourne Institute of Applied Economic and Social Research. The Australian setting is ideal for such a study because the sentiment index is released only once each month, whereas in markets such as that of the US, there is often a progressive release of sentiment information over the month.1 This blurred release of information makes reliable measurement of the impact of consumer sentiment announcements on the stock market problematic in the American context. Examining the direct linkage between investor sentiment and market reaction would be preferred, but the absence of a reliable measure of investor sentiment with a sufficiently deep history makes such an analysis unappealing. However, while exogenous measures of investor sentiment are difficult to identify, Qui and Welch (2006) provide evidence that the University of Michigan US consumer sentiment index (CSI) is a good proxy for investor sentiment in the US. As such, we expect that our Australian CSI is similarly a good proxy for investor sentiment in Australia. We also address whether positive and negative sentiment announcements impact stock prices equally and, given that we find they do not, we further explore in what form such asymmetry exists. As Baker and Wurgler (2007, p. 130) state: “Now, the question is no longer, as it was a few decades ago, whether investor sentiment affects stock prices, but rather how to measure investor sentiment and quantify its effects.” We address this issue by considering whether sentiment announcements reflect the psychological bias of “negativity.” The negativity effect gives greater value to negative information than for positive information. The effect embraces a wide range of empirical phenomena as well as theoretical concepts advanced in order to explain them (Peeters and Czapiński, 1990). The negativity effect can be defined as a situation in which there is a greater impact of negative versus positive stimuli on a subject. The basic logic follows Kanouse and Hanson (1971), and Peeters (1971), and is explained by Beach and Strom (1989). Assume that there is a creature that lives solely on fungi; mushrooms are abundant and edible, and toadstools may or may not be abundant but they are poisonous. The creature holds as its working hypothesis that every fungus is a mushroom. However, if a fungus has one or more attributes of a toadstool, that working hypothesis is quickly rejected. The reverse logic does not apply: a fungus that has many of the attributes of a toadstool must not be eaten even if it has one or more attributes of a mushroom. Hence, the negative attributes of a particular fungus determine the decision about its edibility. Assuming that perfect discrimination is not possible, the screening strategy is safest because it favors false negative decisions (rejection of edible mushrooms that have attributes of inedible toadstools) over false positive decisions (acceptance of inedible toadstools that have attributes of edible mushrooms). 2 In the context of financial markets, consider a group of investors who can shift their holdings between risky investments (stocks) and relatively safe investments (bonds). Assume that the default position adopted by investors is to view all information as good. Thus, if the information has no attributes of bad information, the investor leaves the portfolio largely unchanged. However, if the information represents negative news, it is acted upon vigorously. That is, in this scenario, investors reject the (“good news”) assumption quickly and rebalance their portfolio from risky stocks to safe bonds. Again, in a world of uncertainty, perfect discrimination is not possible—the screening strategy is safest because it favors false negative decisions over their false positive counterparts. That is, if the information is correct, i.e., the new information is truly bad news, then the investor has appropriately moved to a safer haven. Conversely, if the information is incorrect, i.e., it is actually not bad news, then they bear a cost—they have missed out on the risk premium due to the lower risk of the bonds relative to stocks over the period, but their portfolio can be rebalanced back towards riskier stocks later. The foregoing description thus applies the negativity effect to the financial markets setting.3 Of course, the literature extensively explores asymmetric security market reactions to various types of news announcements; a partial list consists of Busse and Green, 2002, Chan, 2003, Chen et al., 2003, Chuliá et al., 2010, Jain, 1988, Kurov, 2010, May, 2010 and McQueen et al., 1996.4 However, to our knowledge, this is the first paper to explore the negativity effect on stock returns in the context of consumer sentiment announcements. At a more general level, our robust evidence of the negativity effect has implications for much of the theoretical work based on Grossman and Stiglitz, 1980 and Kyle, 1985 that assumes symmetry in the effect of information on stock returns. The remainder of the paper is structured as follows. The next section reviews the background literature and develops testable hypotheses. Section 3 overviews the data collection process and the characteristics of that data. Section 4 documents the method and results of the tests. Section 5 concludes.