3.0. AFP RESEARCH METHODOLOGY:
Deductive reasoning was applied as a research approach in comparing between consumer confidence and investor confidence in cross sectional returns. According to Silverman, (2011), the deductive approach is a method in which a review of previous studies carried out on the topic is done then a research hypothesis is developed in which a statistical method is carried out to analyses the data set collected. In addition to that, since the nature of this study, the deductive reasoning was used because it was necessary to use a given data set in order to come in to a conclusion when making a comparison between consumer confidence and investor confidence indices in cross sectional returns (Howell, 2013; Berg, 2009). Therefore, the deductive reasoning research approach will be applied greatly in this research therefore being the most suitable research approach method.
The quantitative research method will be applied in this research as a research method. According to Silverman (2011), quantitative research method employs the use of statistical method and mathematics model in order to understand if a relationship exists between two given variables. In this case, the main aim of this research paper is to compare consumer confidence and investor confidence in cross sectional returns. This means that the quantitative research method was suitable in this research. There are various reasons why this research approach was the most suitable to be used. The first reason is that the quantitative method uses generalization in order to understand the hypothesis under study (Ndira et al., 2009; Saunders et al, 2016). Since this paper is comparing consumer confidence and investor confidence indices in cross sectional returns, generalization of the US stock market will be very useful thus the reason why the quantitative research method will be employed. The second reason why the quantitative research method was suitable in making a comparison between consumer confidence and investor confidence indices in cross sectional returns is because the method is not only objective but also it assists in improving accuracy of the research results (Saunders et al, 2016; Franklin, 2012; Ndira et al., 2009). Lastly, according to Joubish (2009), the quantitative research method relies in comparing results of similar studies which have been carried out in order to validate the results of this study. Therefore, since in this case a comparison is being made between consumer confidence and investor confidence indices in cross sectional returns, it will be helpful in assisting to validate the results of this research therefore ensuring that the results are authentic.
3.3 Propose the Research Hypothesis
Research hypothesis formulation is important in any results as it assists in ensuring that the research remains objective as the research hypothesis is mainly formulated from the research aim and the research question of this study. Therefore, since this research’s main aim is to make a comparison between consumer confidence and investor confidence indices in cross sectional returns, the following hypothesis has been formulated:
Alternative hypothesis: There is a difference between consumer confidence and investor confidence indices in cross sectional returns.
Null Hypothesis: There is no difference between consumer confidence and investor confidence indices in cross sectional returns
3.4 Data Sources and Description
In making a comparison between consumer confidence and investor confidence indices in cross sectional returns, collecting the correct data set is important as it will assist in ensuring that the data is authentic. In measuring both the consumer confidence and the investor confidence indices, the US stock market was considered. From the US stock market, several characteristics of the firms on the US stock market were used. The characteristics were divided in to four main groups which include the age and size of the firm, the asset tangibility, the profitability and lastly the dividends. The age and size of the firms were measured using the market equity characteristics. The age of the firm in this case was considered as the number of years the firm was in the market since it was listed in the stock exchange while the size of the firm in this case is the market equity. The other characteristic is the asset tangibility in which the property plant and equipment of the firm were considered. The profitability measure of the firm was used using the ROE (Return on Equity) in which firms which were profitable were categorized as positive while firms that were not profitable were categorized as negative. The dividends characteristics that were used include the dividends to equity. Moreover, in order to estimate the consumer confidence, the closed end stock fund share was considered mainly in this research. The NYSE share turnover which reflects the US stock was also collected. The IPO is mainly used to gauge whether both investors and consumers are willing to invest in the company. The initial public market offering was used to measure the confidence that the investors and consumers have in the market. The IPO and the first day returns will be used to measure the confidence that both the consumer and investor have in the market. The data that was mainly used was retrieved from the year 2007 to 2017.
3.4.2 Where was the data retrieved?
The data that was used in this study was retrieved from both google finance and yahoo finance. Both databases are authenticating and have been in the industry for over ten years. In addition to that, the data being collected from both yahoo finance and google finance were readily available thus the reason why it was used. The characteristic of the data that was retrieved from google finance and yahoo finance included the age and size of the firm, the asset tangibility, the profitability and lastly the dividends which was available on both yahoo finance and google finance
3.4.3 Characteristics of the data
In order to estimate both the investor and consumer confidence indices in cross sectional returns, a composite was formed on the common variation. The closed end stock fund share were considered mainly in this research. The NYSE share turnover which reflects the US stock will be mainly used. The initial public market offering will be used to measure the confidence that the investors have in the market. The IPO and the first day returns will be used to measure the confidence that both the consumer and investor have in the market.
In making a comparison between consumer confidence and investor confidence indices in Cross-sectional returns the consumer confidence will be used as an independent variable. The dependent variable that will be mainly used is the US stock market data. The US stock market data that will be used is the characteristics of the US stock market that was stated above.
3.5 Model Estimation and Hypothesis Testing
There are three main methods that will be used in data analysis. The methods that will be used in this research include the descriptive statistics, the correlation analysis and lastly the regression analysis. In the category of descriptive statistics, the characteristics of the data that was collected will be described. The US stock market data that was collected will be analyzed together with the mean and standard deviation will be used to describe the nature of the data. The data that will be analyzed in this category will include the age and size of the firm, the asset tangibility, the profitability and lastly the dividends. Moreover, the data that was collected on the consumer and investor confidence will be analyzed in order to find the true nature of the data. This will be based on the IPO and the first day of returns as the mean and the standard deviation of the data will be collected.
The correlation analysis is the second category that was used. The correlation was used to analyses whether there are two variables that was used were correlated in order to determine whether the data is suitable for analysis. The last category that was used is the regression analysis. The regression analysis was used to analyses the main hypothesis of the research which is whether there is a difference between consumer confidence and investor confidence indices in cross sectional returns or there is no difference between consumer confidence and investor confidence indices in cross sectional returns. The regression analysis will greatly assist in understanding the main research objectives of the research.
3.5.2 Regression models
The regression model that was constructed in this research was based of the linear model construction in which the cross sectional predictability patterns was used. The impact of the investor and the consumer confidence on the stock market together with the impact on the selected time period. The cross sectional predictability was based on the research by Baker and Wurgler (2006). The regression model was constructed as follows:
In which
i= index firms
t=time
T=proxy for confidence
X=vector characteristics while
a1=effect of consumer and investor confidence
b1= effect of characteristics of the firm
b2=should be non-zero as it assists in showing cross-sectional factors.
REFERENCES
Berg, B. L., (2009). Qualitative Research Methods for the Social Sciences. Seventh Edition. Boston MA: Pearson Education Inc
Franklin, M.I. (2012). Understanding Research: Coping with the Quantitative-Qualitative Divide. London and New York: Routledge
Howell, K. E. (2013). Introduction to the Philosophy of Methodology. London: Sage Publications.
Joubish, F. (2009). Educational Research Department of Education. Federal Urdu University, Karachi, Pakistan
Ndira, E. Alana, Sl. T. and Bucknam, A. (2011). Action Research for Business, Nonprofit, and Public Administration – A Tool for Complex Times . Thousand Oaks, CA: Sage.
Saunders, M., Thornhill, A. and Lewis, P. (2016) Research Methods for Business Students, Pearson Education.
Silverman, D. (2011). Qualitative Research: Issues of Theory, Method and Practice, Third Edition. London, Thousand Oaks, New Delhi, Singapore: Sage Publications
Hire the best seo article writer 