Investor Psychology and Behavioral Finance - Lab Report Example

of Investor Psychology and Behavioral Finance Introduction Different s have different positions in the market. In preparation for financial analysis, they employ strategies that can best fit their business model. In general, there are two kinds of analysts; buy-side and sell-side. Buy-side analysts, also known as buyers, identify valuable opportunities for their company. Buy-side analysts help to improve the portfolio performance using strategies such as “buy low sell high”. In most cases, Buy-side analysts work for firms like hedge funds, pension funds, and mutual funds (Wall Street Wannabe, 2014). On the other hand, sell-side analysts, also known as sellers, mainly evaluate future earnings growth of a company. Also, they focus on equity research so as to provide a recommendation for investment decision (Buyside Media, 2014). Most of the time, they work for brokage firms. Since buyers have to make an investment decision, they need certain experience before becoming buy-side traders. Thus, most analysts start as sell-side traders for several years in order to gain experience and switch to the buy-side. According to Yang, buy-side performance is relatively the same as compared to the sell-side performance. In this case, the performance is relatively the same in terms of number of coverage. In this report, coverage is defined as the number of stocks that sell-side analysts covered before they leave their sell-side job. Summary In the report, one will focus on the relationship between the coverage number and the buy-side job by developing two hypothesis tests. The first hypothesis test determines the impacts of the number of coverage to the analysts. The test will determine on which side the analysts will go to after resigning their first sell-side job. For instance, the analysts can either choose buy-side or sell-side. The results indicate 95% confidence that the number of coverage is equal. As a result, coverage does not affect the analysts’ choice of a job after their first sell-side job. The second hypothesis test determines whether if analysts resign their sell-side job for the buy-side job after attaining coverage of 15. In turn, the results demonstrate 95% certainty that analysts do not have to achieve coverage of 15 for them to quit their jobs. Data Collection Indeed, 38 random samples of analysts were collected to conduct the hypothesis tests. Initially, their information was retrieved from LinkedIn Website. There was observation made on their choice of a job after quitting their first sell-side job. Later on, two columns were created; sell-side and buy-side. For the analysts who wanted sell-side jobs, their coverage number was recorded in the sell-side column. Subsequently, the buy-side column was filled with coverage number of analysts who chose buy-side jobs. Hypothesis Testing Hypothesis I The goal of this test is to examine whether the number of coverage will have any impact on the analysts’ choice of jobs. In this hypothesis test, 38 random samples were used. The type of t-test used is the two tail sample. Most importantly, the samples were assumed to have unequal variances. The hypothesis is as follow: Ho= Null hypothesis: the means for going to sell-side and buy-side are the same after analysts quitted their first sell-side job. Ha= Alternative hypothesis: the means for going to sell-side and buy-side are not the same after analysts resigned their first sell-side job. Ho = Ha Ho ≠ Ha Sell Buy Mean 6.95 10.5625 Variance 40.78684211 63.72916667 Observations 20 16 Hypothesized Mean Difference 0 Df 28 t-Stat -1.472049843 P(T Read More