A parametric survival analysis of fundamental factors and sentiment index towards future stock returns: a new chapter of global financial crisis 2007

The traditional financial theory was purposely invented to analyze the investment performance with the belief that the rational act of an investor could lead to decision making. Most of the theories developed came up with an assumption that the market is perfectly efficient. However, the evolution of the theory led many researchers to find evidence that the decision making process in investment activities could be influenced by the irrational behavior and psychology of an investor. This is called as Behavioral Finance Theory. In this study, linear regression model was used to investigate the effect of sentiment index and the fundamental factors towards future stock returns. Then a Parametric Survival Model by using Log-logistic and Weibull Hazard Model was used to observe the existence and the size of rational bubbles in the market. A time series analysis was performed by using monthly data of NYSE and NASDAQ from five sectors during Global Financial Crisis period (2007-2009). It was found that only 27% out of 30 companies are significant. The sentiment index showed a weak negative relationship towards future stock return while the fundamental factors showed a strong negative relationship towards future stock returns and remained the major contributing factors. Lastly, small in size of rational bubbles were found during the Global Financial Crisis 2008. 1.0 Introduction Many researchers and practitioners have developed theories and application models to appraise investment performance. Some of the financial theories that have evolved are Capital Asset Pricing Model (Sharpe, 1964), Arbitrage Pricing Theory (Ros, 1976) and Modern Portfolio Theory (Markowitz, 1952). These models are based on the concept of utilizing all the informations available in the market and by considering the rational act of an investor in the decision making process, hence indicating the market is efficient. However, researchers have yet to find the exact answer to reveal the mystery of human psychology, emotion and sentiment in influencing the decision making process. Therefore, another theory is being developed to shed some light into it which is the Behavioral Finance Theory. This theory is being evolved to understand how the investor’s behavior and sentiment could influence the decision making process and to some extent how it can be used as predictor tools. The unending debate among the researchers on whether investor’s sentiment has a predictive ability towards stock returns has opened up many opportunities of expanding the epistemology knowledge of behavioral finance. Thus, many studies have been conducted to enhance their arguments by using several different proxies of sentiment extraction. Some of the Journal of Business and Retail Management Research (JBRMR) Vol. 10 Issue 2 April 2016 www.jbrmr. com A Journal of the Academy of Business and Retail Management (ABRM) 130 sentiment proxies that were used include the surveys of investor confidence, sentiment from market variables, news and social media, and internet message boards. In this paper, we conducted an investigation to see whether investor sentiment could influence future stock return by using a model of sentiment proxies by Baker and Stein (2004) which is the trading volume of an investor. Based on this model, investors can be categorized into two main types which are rational and over-confident investors. They believed that trading volume could be an important indicator of investor sentiment. Overconfident investors will trade more as they belief they will obtain more returns. This will push the price of stock to increase and attract more trading volume. The increase in trading volume in the market reflects the increase in investor sentiment. Therefore, this paper endeavors to investigate whether the fundamental factors and investor sentiment could influence future stock returns. This research paper consists of the analysis of the body of literature relating to the fundamental factors, investor sentiment and future stock returns, hypotheses statement, data and methodology, findings and results and lastly the conclusion. 2.0 Literature Review and Hypotheses Development 2.1 Investor Sentiment A number of past literatures had conducted studies to examine whether investor sentiment has predictability power towards future stock returns. The empirical results varied depending on the choice of the investor sentiment proxy. Previously, Kim and Kim (2012) subdivided four major groups of literatures that generally tested the relationship between investor sentiment and future stock returns based on the source of sentiment information they had extracted. The four major determinants of sentiment are (1) surveys of investor confidence; (2) sentiment from market variables; (3) news and social media; and (4) Internet message boards. For the first group of papers, most of the researchers such as Otoo (1999), Solt and Statman (1988) and Brown and Cliff (2004) agreed that there were no relationship between sentiment index and future returns. The second group of papers which extracted sentiment from market variables such as Neal and Wheatley (1998), Baker and Wurgler (2006), Baker, Wurgler and Yuan (2011) and Edelen, Marcus and Tehranian (2010) generally reported that there was a negative relationship between investor sentiment and future stock returns. The third group of papers which used sentiment proxies from news and social media such as Clarke and Statman (1998) and Fisher and Statman (2000) reported there was no relation between sentiment and future returns. However, Tetlock (2007), Tetlock, Saar-Tsechansky, and Macskassy (2008) and Chen, De, Hu, and Hwang (2011) reported that there was a negative relationship between sentiment and future stock returns where negative news could forecast firms stock returns. The fourth group of papers used internet message board as the proxies for their sentiment. Wysocki (1998), Antweiler and Frank (2004) Das and Chen (2007) found that the sentiment from internet message boards could predict stock return such as abnormal, positive and negative return. However, the focus of this paper is to extract the investor sentiment index by using trading volume as the proxy. Several researchers defined sentiment in many sensible ways. Smidt (1968) said that sentiment could lead towards speculative bubbles, Zweig (1973) stated that sentiment comes from investor’s biased expectations towards asset values, Black (1986) said that sentiment is the noise in the financial markets, Lee, Shleifer and Thaler (1991) defined it as biased expectation of the investor towards stock return that is unjustifiable by fundamental values and lastly Baker and Stein (2004) defined sentiment as investor’s optimism or pessimism towards stocks. In this paper, Trading Volume Index (TVI) was used as a measure of the sentiment. TVI can be defined as the average change of the trading volume per unit of time. Previous literature suggested that trading volume is the best measure for sentiment because of Journal of Business and Retail Management Research (JBRMR) Vol. 10 Issue 2 April 2016 www.jbrmr. com A Journal of the Academy of Business and Retail Management (ABRM) 131 two main reasons; (1) it can explain the investor overconfidence’s movement in the market as stated in Baker and Stein (2004) framework. (2) Smidt (1968) and Brown and Cliff (2004) suggested that the investor sentiment’s formation occur through the process of time. This study emphasizes on conducting a preliminary test in five different sectors in which different sizes of company is taken as the sample of works during the period of Global Financial Crisis (20072009) as the influencing event towards the movement of investor sentiment. 2.2 Book-to-market ratio In this study, sentiment index is not the only concern in predicting the future stock returns. There are several other variables that is believed to have predictability power towards future stock returns. Many researchers believed that book-to-market ratio is one of the dominant determinants to predict future stock returns. Some of studies which found that book-to-market ratio can predict the market returns are Fama and French (1992) which showed that the book-tomarket ratio of individual stocks had the ability in explaining the variations in stock returns and Kothari and Shanken (1997) was used a Bayesian framework to investigate the ability of bookto-market ratio to predict the market returns and found that book-to-market ratio can predict negative expected return. In contrast to those finding, Fama and French (1995) came out with another finding by which they did not find any causal link between book-to-market equity ratio as factors in earnings and returns. 2.3 Market Capitalization Other than book-to-market ratio, market capitalization is another determinant that can be used as controlling variable in predicting the future stock returns. Crain (2011) found that smaller firms can predict higher return than the larger ones. Banz (1981) reported there is a relationship between the total market value of the common stock of a firm and its return and found that for the period 1936-1975, the common stock of large firms might be a proxy for risk, therefore, a potentially important return predictor. Smaller firms, in general, are much more risky compared to larger firms, leading to lower prices and higher returns. 3.0 Data and Methodology 3.1 Data collection The data was collected from Yahoo! Finance and Morningstar (independent investment research) databases. The data consists of Future Stock Returns of company (dependent variable), Market Capitalization, Book-to-Market ratio and Sentiment Index (independent variables). The sentiment index was measured by calculating the changes in trading volume twice. The data comprised of five companies from five different sectors NASDAQ and NYSE market comprises of Consumer goods, Technology, Healthcare, Services and Financial sectors. The d