Teorías de los hábitos de estudio

For many years, as discussed above, researchers found supportive evidence for the notion that a common time-varying sentiment component exerts market-wide effects on stock prices.2 Given the crucial influence of investor sentiment in stock markets, it is important to price investor sentiment appropriately in the asset-pricing process, as it affects both asset returns and other risk premiums.

Precedent literature showed that there exists a wide range of financial market anomalies that still remain unsolved by conventional finance theory. These market anomalies, however, have been proved by recent studies to have a close relationship with investor sentiment. For example, Neal and Wheatley (1998) examined the fore- castability of three sentiment measures of stock returns and found that discounts on closed-end funds, one of their proxies for sentiment, predict size premiums. Brown and Cliff (2005) considered the impact of sentiment on cross-sectional size portfolios by regressing long-horizon returns on economic explanatory variables as well as lagged sentiment and found that returns of large stocks tend to be more exposed to investor sentiment than small stock returns. Besides, referring to the value effect, extant 2_{As a reminder, important literature that addresses the issue of market-wide sentiment includes}

De Long et al. (1990), Shleifer and Summers (1990), Lee et al. (1991), Barberis et al. (1998), Shiller (2000a), Brown and Cliff (2004, 2005), and Yuan (2005).

22 Literature Review

literature suggests mixed results on the impact of investor sentiment on stocks with different book-to-market ratios. For example, Lakonishok et al. (1994) argued that the high rates of return associated with securities with high book-to-market ratios are contributed by investors who mis-extrapolate the past earnings growth rates of firms. Specifically, they asserted that for stocks with high book-to-market ratios, investors are overoptimistic regarding firms with the good previous-year performance but overpessimistic regarding firms that performed poorly in the previous year. In addition, Lakonishok et al. (1994) argued that stocks with low book-to-market ratios ‘charm’ investors, and thus, investors push prices far above the fundamentals, which results in lower subsequent returns. Despite the wide spectrum of results offered by existing studies, the vast majority of these draw a common conclusion: that investor sentiment has strong predictive power in terms of cross-sectional variations in security returns.

Apart from the evidence above, Baker and Wurgler (2006) collected and rephrased the scattered results from earlier empirical work to provide more intuitive inferences on the relationship between sentiment and cross-sectional stock returns. In particular, they tested the relationship between investor sentiment and a set of cross-sectional characteristics and found that small, young, high volatility, low profitability, non- dividend-paying, extreme growth and distressed stocks are more exposed to investor sentiment. Moreover, they indicated that firms with opaque characteristics earn lower subsequent returns in high-sentiment periods, and this pattern attenuates and reverses in low-sentiment periods. In extension to Baker and Wurgler (2006), Berger and Turtle (2012) also found consistent results. Specifically, they tested the conditional relationship between cross-sectional stock returns and investor sentiment via multiple risk factor models and found the predictive power of investor sentiment on security returns remains after controlling for additional systematic risk factors. Hence, based on these two studies, my research further explores the coherent relationship between investor sentiment and cross-sectional variations in stock returns with respect to firm opacity, for more intuitive inferences.

There are two possible explanations for the relationship between cross-sectional variations in opaque stock returns and investor sentiment. First, the higher level of firm opacity increases information asymmetry between investors and firms and consequently enhances the difficulties in valuation. Ravi and Hong (2014) argued that when the information asymmetry between investors and a particular firm is higher, all

2.3 Literature Related to My Study 23

investors are largely uninformed. Hence, to capture the nature of cross-sectional firm opacity, I select a set of firm characteristics including size, risk, profitability, dividends, tangibility and growth opportunity, where all these variables are suggested as indicators of information asymmetry by the existing accounting literature.3 For example, Chari et al. (1988) argued that firm size is an important proxy for information asymmetry and found higher abnormal returns around the earnings announcement date for small firms but no abnormal returns for large firms. Aboody and Lev (2000) found a close relationship between research and development and insider gains. In particular, they found firms with intensive research and development exhibit more massive insider gains and thus research and development significantly predict information asymmetry. 4 Another source of the widespread cross-sectional variations in opaque stock returns is the short-sale impediments in financial markets. Stambaugh et al. (2012) argued that institutional constraints, arbitrage risk, behavioural biases of traders and trading costs contribute to the huge short-sale impediments and thus limit the ability for arbitrage. Numerous studies have argued that limited arbitrage causes mispricings. For example, Shleifer and Summers (1990) argued that it is, in fact, risky, not riskless, to arbitrage against irrational investors in financial markets. The fundamental risk and risk from irrationals increase the total risks for arbitraging activities and thus limit the ability for arbitrage. Shleifer and Vishny (1997) indicated a similar risk that might limit financial market arbitrage: that traders who short a stock in the belief that the stock is currently overvalued and thus its price will eventually fall in the future. However, if future prices increase further, traders suffer huge losses when liquidating. In addition, Baker and Wurgler (2006) concluded that mispricing results from the interaction of an uninformed demand shock and limits to arbitrage. Based on these two propositions, it may be advantageous to investigate the relationship between cross- sectional variations in stock returns with respect to firm opacity and investor sentiment.

3_{Tangibility includes two variables (property, plant and equipment and research and development)}

and growth opportunity is measured by book-to-market ratio and sales growth rate.

4_{Krishnaswami and Subramaniam (1999) indicated the volatility of stock returns as a proxy for}

information asymmetry. Aboody and Lev (2000) suggested the relevance of property, plant and equipment but indicated a weaker predict power relative to research and development. Earning as a proxy for information asymmetry was introduced by Collins et al. (1997), Francis and Schipper (1999), and Ely and Waymire (1999). Venkatesh and Chiang (1986) documented the effect of earnings and dividends, while Richardson (2000) suggested the relevance of book-to-market ratios and sales growth rate.

24 Literature Review