Undergraduate Research Project xi Faculty of Business and Finance Table 4.2.7: Ordinary Least Squares Findings for. Undergraduate Research Project xii Faculty of Finance and Finance Table 4.3.1.10: Correlation coefficient of independent variables and.
RESEARCH OVERVIEW
Background of the study
Following the Dow Jones Industrial Average, the S&P500 has become the most followed index in the world. However, the New York Stock Exchange only allows large and established companies to trade on the market so that investors have a viable investment alternative.
Problem Statement
Something more than the CAPM market beta and Fama and French (two factors - book-to-market and firm size ratios) may be needed to capture the cross-sectional variation of stock returns. Thus, there is an inevitable need to explore fundamental factors that explain the cross-section of stock price with current data.
Research Question
In addition, Fama and French (1992) introduced and found that two variables, size and book-to-market equity, could be applied to explain much of the cross-sectional variation in average stock returns. Chan, Hamao, and Lakonishok (1991) proved that book-to-market shares perform well in explaining the cross-sectional average returns on Japanese stocks.
Research Objective
- Specific Objective
Undergraduate Research Project Page 47 of 114 Faculty of Business and Finance Ho: There is no significant relationship between company size and equity returns. Undergraduate Research Project Page 70 of 114 Faculty of Business and Finance, the higher the expected equity return.
Hypotheses of the Study
Significance of Study
Chapter layout
Previous studies on stock returns and the four independent variables are discussed, as well as the development of the research hypotheses. In addition, research design, which talks about how the research is conducted and methods of data analysis, is also explained.
Conclusion
An analysis is performed to obtain the findings for the research questions and the hypothesis for the main research objective.
Introduction
Reviews of the Literature
- Book-to-market equity
- Firm Size
- Price to earnings ratio
- Leverage
- Earning Volatility
- Liquidity
The results of their research have revealed that there is a negative relationship between firm size and stock returns. But, it is important to explain and predict the return of stocks in the long run.
Theoretical Model
- Arbitrage Pricing Theory (APT)
Most researchers have succeeded in obtaining the same empirical results that are consistent with the CAPM statement. Black (1972), Fama and MacBeth (1973) conducted research that found a significant positive relationship between systematic risk and expected return on securities.
Theoretical Framework
- Book-to-market equity ratio
- Leverage
- Price to earnings ratio
- Earning volatility
- Liquidity
From our a-priori expectations, according to the high level of the ratio in the market that is proving that the company is undervalued, it is enough evidence to show its impact on the stock. Undeniably, higher leverage will tend to be riskier to invest in the company. This is because investors would not gain confidence to invest in the company that takes the lows.
Because investors looking for high returns will choose to invest in a company that has high earnings volatility. Obviously, higher liquidity is associated with a higher ability of the company to repay short-term debt. It means high liquidation of the company and that the assets in the company are greater than the liabilities in the company.
Conclusion
Undergraduate Research Project Page 91 of 114 Faculty of Business Administration and Finance Table 4.1.2: Rotated component matrix for the year 2001. Undergraduate Research Project Page 93 of 114 Faculty of Business Administration and Finance Table 4.1.3: Rotated component matrix for the year 2002. Undergraduate Research Project page 95 of 114 Faculty of Business Administration and Finance Table 4.1.4: Rotated component matrix for the year 2003.
Bachelor research project Page 101 of 114 Faculty of Business and Finance Table 4.1.7: Rotated component matrix for the year 2006. Bachelor research project Page 103 of 114 Faculty of Commerce and Finance Table 4.1.8: Rotated component matrix for the year 2007. Undergraduate Research Project Project Page 111 of 114 Faculty of Business and Finance Table 4.3.2.1: Jarque-Bera normality test results.
RESEARCH METHODOLOGY
Research Design
University Research Project Page 45 of 114 Faculty of Business and Finance Table 4.2.2: Correlation coefficient of independent and dependent variables. University Research Project Page 55 of 114 Faculty of Business and Finance Table 4.3.1.2: Correlation coefficient of independent and dependent variables. University Research Project Page 56 of 114 Faculty of Business and Finance Table 4.3.1.3: Correlation coefficient of independent and dependent variables.
Undergraduate Research Project Page 57 of 114 Faculty of Business Administration and Finance Table 4.3.1.4: Correlation coefficient of independent variables and dependent variables. Undergraduate Research Project Page 58 of 114 Faculty of Business Administration and Finance Table 4.3.1.6: Correlation coefficient of independent variables and dependent variables. Undergraduate Research Project Page 99 of 114 Faculty of Business Administration and Finance Table 4.1.6: Rotated component matrix for the year 2005.
Data Sources and Description
- Data Cleaning
Economic Model
Econometric Method
- Factor Analysis
The next part of the research examines how they affect returns of S&P 500 index through the ordinary least square (OLS) method. Principal component is one of the extraction methods applied to form uncorrelated linear combinations of the variables. A scree plot helps us decide the number of factors to keep, as it is a plot of the variance against the number of factors.
The function of Varimax is to maximize the variance of the squared factors loading on each factor. However, the function of Quartimax is to maximize the variance of the squared factors loading on each variable. In Equamax, maximizing or minimizing the variance of squared factors loading on each variable is ruled out.
Diagnostic Checking
- Jarque-Bera
We allow the missing values to keep the default as cases in the options window are excluded from the list. Based on the P-value result, reject H0 if the P-value is <0.01, which means that the error term is not a normal distribution. On the other hand, do not reject H0 if the P-value is >0.01, which means that the error term is normally distributed.
Conclusion
DATA ANALYSIS
Factor Analysis
Undergraduate Research Project Page 41 of 114 Faculty of Business and Finance Market-to-Book : The value of company by comparing the book value with. Current assets: All assets can be converted for cash within one year. Looking at the rotation sums of squared loadings cumulative percentage, the results show that more than 83% of the variance is accounted for by the factors in each year.
Undergraduate research project Page 42 of 114 Faculty of Business and Finance Table 4.1.15: Explained result of the total variance for the year 2003. Undergraduate research project Page 43 of 114 Faculty of Business and Finance Table 4.1.19: Explained result of the total variance for the year 2007.
Ordinary Least Square (OLS)
From the results obtained above, we found that there is only one significant variable in the model, which is Earnings II. Undergraduate Research Project Page 46 of 114 Faculty of Business and Finance Table 4.2.3: Findings of the Ordinary Least Squares Method for Company Size I. Undergraduate Research Project Page 48 of 114 Faculty of Business and Finance Table 4.2.5: Findings of the Ordinary Least Squares Method for Income i.
Undergraduate Research Project Page 49 of 114 The Faculty of Business and Finance The P-value for the years 2000 and 2001 for accrual I is significant. The results show that there is a positive correlation between extraordinary items and inventory returns this year and 2009. Undergraduate Research Project Page 52 of 114 Faculty of Business and Finance Table 4.2.10: Ordinary Least Square Method's Findings for Cash Flow.
Diagnostic Checking
- Normality Test
Undergraduate research project Page 59 of 114 Faculty of Business and Finance Table 4.3.1.7: Correlation coefficient of independent and dependent variables. Undergraduate research project Page 60 of 114 Faculty of Business and Finance Table 4.3.1.8: Correlation coefficient of independent and dependent variables. Undergraduate research project Page 61 of 114 Faculty of Business and Finance Table 4.3.1.9: Correlation coefficient of independent and dependent variables.
Undergraduate Research Project Page 62 of 114 Faculty of Business and Finance Table 4.3.1.10: Correlation coefficient of Independent Variables and Dependent. Undergraduate Research Project Page 63 of 114 Faculty of Business and Finance Table 4.3.1.11: Correlation coefficient of Independent Variables and Dependent.
Conclusion
DISCUSSION, CONCLUSION AND IMPLICATION
Inferential Analysis
- Ordinary Least Square (OLS)
Discussions of Major Findings
- Stock Return and Firm Size
- Stock Return and Earnings
- Stock Return and Market-to-Book Equity
- Stock Return and Cash Flow (Current Asset)
University Research Project Page 73 of 114 Faculty of Business and Finance has been proven to be the main factor in explaining the average return of stocks. University Research Project Page 74 of 114 Faculty of Business and Finance, which reveals information about such a relationship. Faculty of Business and Finance before the official declaration of bankruptcy status.
Undergraduate Research Project Page 76 of 114 Faculty of Business and Finance caused inconsistencies in data and prevented us from conducting a comprehensive research. Bachelor research project Page 107 of 114 Faculty of Business and Finance Table 4.1.10: Rotated component matrix for the year 2009. Bachelor research project Page 109 of 114 Faculty of Business and Finance Table 4.1.11: Rotated component matrix for the year 2010.
Implication of the Study
- For the Fund Manager
- For the Speculator
- For the Hedger
- For the Regulators
Limitations of the Study
Most of the time, journal articles are not free for us to review and most of the previous researchers around the world have conducted their respective research with time series approach instead of cross-sectional approach, hence it is time consuming and challenging. for her. search for journal articles relevant to this study and there is little information to support the analysis process. It is time and inconvenience for us to carry out our data collection process within our schedule. A number of company records were unable to search and download from the data stream such as 3M Co.
In addition, there are some missing values in the company data set, which may be due to standard disclosure practice controls. According to the e-view results shown in Chapter 4, we obtained the same result for the standard error for each year for all independent variables. The reason may be only a relatively small change in the standard error and cannot be fully displayed in the eView table due to the limitation of decimal places.
Recommendations for Future Research
Undergraduate Research Project Page 77 of 114 Faculty of Business and Finance underlying company and it can be affected by any other new factors in today's rapidly changing world. There is also a possibility that prior relationship between one fundamental factor and stock return will change from insignificant to significant relationship with the introduction of new factor. Other than that, future researchers can also focus on non-financial characteristics of company instead of treating only financial characteristics as factors to explain stock return.
Since most previous researchers have focused their stock return research with time series data, there is a strong need for future researchers to conduct more research based on cross-sectional data. By doing this, more people are able to better get a real and clear picture of the stock market, since the cross-sectional method only considers one year's data and it is useful to find the explanatory variable. Additionally, prospective researchers are advised to download the complete S&P 500 Companies data set from other available data sources in order to increase the accuracy and consistency of the research.
Conclusion
A reexamination of firm size, book-to-market, and earnings in the cross-section of expected stock returns. Fundamental variables and the cross section of expected stock returns: the case of Hong Kong.
Rotated Component Matrix for Year 2000 89
Rotated Component Matrix for Year 2001 91
Rotated Component Matrix for Year 2002 93
Rotated Component Matrix for Year 2003 95
Rotated Component Matrix for Year 2004 97
Rotated Component Matrix for Year 2005 99
Rotated Component Matrix for Year 2006 101
Rotated Component Matrix for Year 2007 103
Rotated Component Matrix for Year 2008 105
Rotated Component Matrix for Year 2009 107
Rotated Component Matrix for Year 2010 109
Jarque-Bera Normality Test Results for
