Valuation of Securities and Equity Trading

Part A. – EXCEL (Data from Capitaliq.com)

Using historical share prices (in monthly frequency) for the time period 01.01.2011 – 01-05-2017 for the stocks of Standard Chartered, Tesco, British American Tobacco, BP, Ryanair and FTSE Allshare, prepare an investment report with the elements shown below:

 

1. Computation of the average monthly return for the five stocks and the market index, using the formula

𝑆_𝑡 − 𝑆_𝑡−1

𝑅_𝑡 =

𝑆𝑡−1

           where 𝑆_𝑡 is the return index in period t, and 𝑆_𝑡−1 is the return index in the previous period.

[5 marks]

2. Calculation of the compound average monthly return and risk for the 5 stocks.

[5 marks]

3. Express the annualised return and risk of these 5 stocks.

[5 marks]

4. Calculation of the Beta of each of the 5 stocks.

[5 marks]

5. Create charts showing the risk and return of 4 different portfolios of your choice that can be made by combining holdings in two of the 5 companies.

[10 marks]

6. For each of your 4 portfolios calculate proportions, risk and return of the minimum variance portfolio.

[10 marks]

7. Given a risk aversion coefficient A = 5, create charts showing the Utility for the two portfolios made from the following shares:
   1. Standard Chartered and Tesco [5 marks]
   2. British American Tobacco and BP [5 marks]
8. Calculate the combination of the shares in each of the two portfolios that maximises the investor’s Utility.

[10 marks]

 

Part B. 2500 word report

Portfolio diversification is an investment strategy that contributes to mitigation of portfolio loss and volatility. Develop a critical analysis on portfolio diversification and its key benefits for the protection of investors from the unpredictability of markets. Support your answer by academic references and your own analysis. How would you evaluate the case of Standard Chartered, Tesco, British American Tobacco, BP, and Ryanair in the light of your previous analysis? All concepts should be expressed in your own words; any material copied from another source should be clearly indicated as such and referenced. Additional marks will be awarded for original work demonstrating the impact of diversification. [40 marks]

DOES CORPORATE GOVERNANCE QUALITY AFFECT CAPITAL STRUCTURE?

Does corporate governance quality affect Capital structure?

INTRODUCTION

The relevancy of capital structure and the role it plays in capital structure has been a topic for discussion for a period of over sixty decades.  While some authors like Modigliani and Miller (1959) argue that corporate governance quality does not affect capital structure, other authors like Bown and Taylor (2006) argue that a company with a better corporate governance quality affect the capital structure. With the debate as to whether corporate governance quality affect capital structure continuing, it has become important to discuss the effect of corporate governance quality on the capital structure of a firm as this topic seems confusing to most financial researchers. The main reason of the existence of corporate governance is to assist in providing better balances and cheques between the management and the shareholders of a firm (Huang and Song, 2006). This is important as the management acts in the best interest of the shareholders. The theory that mainly explains the importance of corporate governance is the agency theory. According to Driffield et al., (2007) the agency theory mainly seeks to solve the main problems that exists between the principal and the agent in which the agent must act in best interest of the agent.

If a firm ensures that it is governed correctly, then the capital structure is likely to perform well. One way in which the agency theory can be applied in ensuring that corporate governance in a firm is quality is by employing leverage. There are several ways in which the agency problems can be solved by employing leverage. The first way in which the agency conflicts can be reduced is through motivating managers of the firm to increase their ownership. This means that the company will employ debt finance which will displace equity capital. The equity base of the firm will be significantly reduced which will ensure that the management owned equity has increased significantly (La Rocca, 2007). In addition to that, debt usage by firms increases the chances of a firm going bankrupt, Therefore, if the management is aware of such risks, they will significantly increase their efficiency by reducing their perks consumption. Lastly, since the usage of debts usually attract interest payments, the issue of free cash flow problem will be solved. Therefore, this paper will contribute to the growing research of whether corporate governance quality affects capital structure.

LITERATURE REVIEW

Since the introduction of capital structure irrelevance by Modigliani and Miller (1958), several capital structure theories have emerged. The first theory that seeks to investigate the issue of corporate governance quality and if it affects capital structure is the agency theory. Several authors such as La Rocca, (2007) argue that managers always act to their best interest in which they will make investment decisions that will either increase their compensation or decrease the risks that they face with employment. Therefore, this means that the usage of debt financing is an important governing tool that can be employed in the reduction of conflict that exists between the shareholders and the management. Using debt financing will assist in reducing the availability of free cash flow to managers of a firm therefore assist in ensuring that the corporate governance structure affects the capital structure (Antoniou et al., 2008).

The other theory that investigates whether the corporate governance structure affects the capital structure is the pecking order theory. This theory states that a firm will prefer internal financing compared to external financing (Huang and Song, 2006).  However, the theory is based on two main assumptions in which information asymmetry assists between the shareholders and the management and two managers of a firm are likely to prefer internal financing compared to external financing. This implies that if the internal cash flow operations are not enough a firm is likely to source the money from external sources (Huang and Song, 2006). This means that debt will be employed by most managers as it is the safest way in which a firm can acquire capital investment without increasing risks. If debt is not sufficient for the firm, it is likely that the firm will seek the next less risky debt strategy implying that equity will only be employed if there is no reason to use debt as a strategy.

One author who investigated the relationship between corporate governance quality and capital structure is Huang and Song, (2006) who in his investigations found out that the board size of a firm affects the capital structure. The authors also found out that there was no relationship between the duality of the management and the firm’s capital structure. In addition to that, Sotu (2003) who investigated the same topic found out that there was a relationship between corporate governance quality and the capital structure. The author found out that a weak corporate governance system was caused by a firms’ diffused ownership together with a firm finance leverage that is higher. The author suggests that one way in which the conflict between the management and the shareholders can be reduced is through having a centralized ownership. A corporate governance system that is quality will assist in lowering the usage of internal finance and increasing the usage of external financing. This means that there is no relationship between the quality of a corporate governance system and the financial leverage of a firm.

Rehman et al (2010) who also investigated the same topic found out that there was a relationship between the size of the board which greatly influenced its quality and the capital structure. Another author who investigated if corporate governance quality affects the capital structure is Antoniou et al (2008) who found out that firms which operated in both bank oriented and market oriented economies had their capital structure influenced by not only the capital markets exposure but the corporate governance practices. Lastly, Driffield et al., (2007) who also investigated whether there was a relationship between the quality of the corporate governance and the capital structure found out that a positive relationship existed between these two factors. In fact, the size of the board together with its composition and the duality of the CEO greatly affected the capital structure.

RESEARCH DESIGN

The research design assists in describing the methods and the direction in which the research will take in answering the main research question. According to Saunders et al., (2007), the design of a research assists in defining the type of research. This type of research is the exploratory research design. The exploratory research design seeks to generate a hypothesis which will be used in a dataset to assist in examining whether the variables used in this research are connected. In using the exploratory research design, this doesn’t mean that there is lack of knowledge in the area of study. However, the strength of the relationship that exists between the two variables is unknown (Franklin, 2012). The reason why the exploratory research design was considered in this research is because this research type requires less methodological restrictions. In addition to that, the exploratory research design is objective in finding out whether the variables of a research are related and assist in finding answers to the questions being investigated. In understanding whether the corporate governance quality affect the capital structure, this section will describe both the dependent and the independent variables of the study, the hypothesis of the study together with statistical analysis plan and the methods used in data collection.

 

RESEARCH APPROACH

There are various types of research approach that can be employed in a study. However, in order to find out if corporate governance quality is affected by the capital structure, the deductive reasoning was used in this case. The deductive reasoning research approach was employed because one it assisted in reviewing previous empirical studies which were carried out before in order to assist in hypotheses development of its own study (Franklin, 2012). In addition to that, the study employed both statistics and regression model in order to do a resting on the hypothesis which have been proposed in the study. All these steps that have been described are important steps in understanding deductive reasoning (Saunders et al., 2007). Moreover, since the research is quantitative, employing deductive reasoning was important as it enabled the research to be carried out using the given data set for both the corporate governance and capital structure which assisted in making meaningful conclusion for the research. This means that the research will use a given data set to investigate whether the corporate governance affects the quality of the capital structure.

RESEARCH METHOD

The research method that will be used in this study is the quantitative method. The quantitative method mainly deals with statistics and mathematical formula (Berg, 2009). In order to investigate whether corporate governance affects the quality of capital structure, various data sets will be used which will be examined statistically to investigate whether this statement is true or false. Therefore, since quantitative method mainly deals with statistics, various data sets from the FTSE 100 will be used then regressed in order to understand whether there is a relationship between corporate governance and the capital structure. The quantitative method is also important in econometrics as it assists the research to be more objective when dealing with data sets. In this case, since the research will be investigating the relationship between corporate governance and capital structure, various data sets will be collected in relation to the two variables which will assist the research in being more objective. In addition to that, there are several other studies that have been carried out that investigate whether corporate governance quality affects the capital structure. Therefore, by using the quantitative method of study, comparisons will be made with this research and similar study to investigate whether similar results were found out.

 

RESEARCH HYPOTHESIS

A research hypothesis is important in any quantitative study as it assists the research in being more objective and gives the research direction (Adèr et al., 2008). In investigating whether corporate governance quality affects capital structure, the hypothesis that will be investigated in this case is

Hypothesis 1: There is a relationship between corporate governance quality and capital structure

Null hypothesis: There is no relationship between corporate governance quality and capital structure.

The research hypothesis will assist in investigating the main topic of the study and coming to a conclusion as to whether or not there is a relationship between corporate governance quality and capital structure.

 

DATA SOURCE AND DESCRIPTION

In investigating the relationship between corporate governance quality and capital structure, it was important to collect meaningful data. In this study, the FTSE 100 index in which the utility and financial firms were excluded from the London stock exchange was employed. The FTSE 100 index is a collection of companies that perform well in the stock market and was therefore chosen as it will assist in giving out the true nature of whether there is a relationship between corporate governance quality and capital structure.

The data that was used in this study was retrieved from google finance. Although Yahoo Finance has been in the industry for a long time, Google finance was used as a source of data because in the recent past, Google has risen to become one of the most prominent reliable source of information. Therefore, in this case, Google finance will be reliable as a source of financial information for the FTSE 100 index.

The data that was collected in this case consisted of the following. Since the main variables that were being investigated in this study is the corporate governance and the capital structure, the data that was collected was to reflected both the corporate governance and the capital structure. The data that was collected on corporate governance was based on the characteristics of the company in which the companies were retrieved from the FTSE 100 index. The characteristics of the data that was collected to investigate capital structure was the leverage ratio and the stock liquidity. In this case, the leverage ratio that was used the annual reports from the FTSE 100 was collected. The total debt and total asset were collected to calculate the leverage ratio. In calculating the stock liquidity, the data was collected from Google finance in which the daily stock price and the daily trading volumes was used. The data that was collected ranged from 2013 to 2017.

In measuring the variable in order to understand whether corporate governance quality affects the capital structure, the leverage will be used as the dependent variable while the independent variable of interest are the corporate governance variables.

RESEARCH METHODOLOGY

3. Research Design

3.1 Research Approach

The research approach employed in this applied finance project is deductive reasoning, because this research paper first reviewed previous empirical studies and theoretical principles so as to develop its own research hypotheses and subsequently employed statistics and regression models to test the proposed research hypotheses, which fits in line with the definition of a deductive research approach, according to Saunders et al. (2016). In addition, it is also suggested that deductive reasoning is a more suitable research approach for quantitative studies, as it allows the researcher to examine the underlying subject from the particular data sets to the general conclusions (Bryman and Bell, 2015). In this sense, this research project aims to examine the existence of holiday effects in the UK stock market by examining a particular index (FTSE 100), which also corresponds to deductive reasoning.

 

3.2 Research Method

The research method that will be used in this study is the quantitative method. The quantitative method can be described as a research method in which both mathematical and statistics functions are used in order to test objective theories that will assists in examining if a relationship exists between the variables being examined (Saunders et al, 2016). There are various reasons why the quantitative research method was used. Firstly, the quantitative method allowed the research to be more objective and the results to be more accurate (Bryman and Bell, 2015). Since this research seeks to analyse whether there is an existence of any holiday effects in the UK stock market, using the quantitative method will be very useful in examining this factor. The use of quantitate research method allows the generalization of the phenomena under study by using variables. Therefore, by using qualitative research method, the phenomena under study which is to examine the existence of holiday effects in the UK stock market by examining the FTSE 100 index will be generalized by using both pre-holiday, holiday and post-holiday performance in the stock market. Moreover, the use of quantitative research method allows the results of the research to be compared to other studies. This is important as it will assist in authenticating the results of this study.

 

3.3 Propose the Research Hypothesis

A research hypothesis is important as it assists in bringing direction to the study. The research hypothesis of this study will be connected to the research aim and objectives of the study. The research hypothesis that will be investigated will be:

H1: UK stock returns behaved differently around holidays during 2008-2017

Ho: UK stock returns did not behave differently around holidays during 2008-2017

Therefore, in understanding more about the holiday effect, the research hypothesis above will be investigated in order to understand whether the UK stock returns behave differently around holidays and if they do so, what is the reason why these anomalies exist.

 

3.4 Data Sources and Description

3.4.1 What was the data?

The data that was used in this survey was retrieved from the UK stock returns. The index that was used to analyse the existence or absence of anomalies is the FTSE 100 INDEX. The FTSE 100 mainly consist of 100 companies which are listed in the London Stock Exchange. The reason why this data was chosen is because the FTSE 100 is normally used to gauge a company’s success in the UK. This means that the companies listed in the FTSE 100 will greatly reflect on the performance of the companies in the UK after the financial crisis of 2008. The data that was retrieved was based on a 10-year period which is from 2008 to 2017.

 

3.4.2 Where was the data retrieved?

The data which as discussed above was from the FTSE 100 index was retrieved from yahoo finance. The reason why the yahoo finance was used is because Yahoo finance has been in the industry for over twenty years. This means that yahoo finance is a reliable source for retrieving financial information about a company. In addition to that, yahoo finance provides not only current financial information about a country but it also provides a detailed financial information. This means that the site will be useful when it comes to retrieving the FTSE 100 stock returns data from the year 2008 to 2017.

 

3.4.3 Characteristics of the data

The data that will be used will be mainly from the FTSE 100 companies. This data will be based on the daily stock returns of the FTSE 100 companies. Moreover, in order to compare whether the holidays usually perform differently, the main holidays in the UK will be used. In the UK, there are 17 holidays that are documented. Therefore, the data that will be retrieved will be mainly based on the 17 holidays as the investigation of this essay is mainly based on whether the holidays have any effect on the stock daily returns. The image below shows the dates of the holidays in the UK.

 

 

3.4.4 Variable measurement

In analysing whether the holidays have any effect on stock returns, the holiday effect will be used as an independent variable. The holiday effect in this case means “the tendency of stock returns to be higher on any day before a holiday”. The dependent variable that will be used in this study is the daily stock returns. This means that there are higher mean returns of preholiday periods if a comparison is made to other trading days.

 

3.5 Model Estimation and Hypothesis Testing

3.5.1 Data Analysis

The data that was collected will be analysed using three main methods. They include the descriptive statistics, correlation and regression analysis. The descriptive statistics will be mainly used to describe the main characteristics of the data that was collected. The data was mainly partitioned surrounding the main holidays. That is the pre-holiday a day before the holiday. In analysing the days, the close to close basis and the open to close basis of the day was used.

The first step of the data analysis mainly consisted of the daily stock return data which ranged from 1^st January 2008 to 1^st January 2017. The data was a 10-year period in which the years that were put in to consideration mainly happened after the financial crisis. The daily stock returns were analysed in the absence of the main holidays in the United Kingdom. In comparing the mean returns, respective mean return of 1.12 was observed. However, the main issue that was arising is the difference that existed between the pre holidays and the daily stock return. However, the data is not shocking as the days happened to be 28 times more than the trading days. Moreover, the standard deviation of the pre-holiday returns seemed to be lower than that of the daily stock returns.

After the descriptive analysis of the results in which the daily trading stock and the pre-holiday were considered, the correlation and regression analysis were considered. The correlation was used to investigate whether there the pre-holiday and the daily stock returns were related. This was important as it assisted in showing that the two data sets were related.  The regression analysis that was used in this study was mainly employed to show whether there was a relationship between the preholiday variable and the daily stock returns variable. This was important in assisting us to determine whether there was an existence of the holiday effect after the financial crisis in the UK.

Intellectual property 3D Bicycle parking design

1. Introduction

In many countries the legislatures have drafted and made into law some guidelines on intellectual property. This is as result of the benefits that this aspect draws to companies, inventors, and business people. Intellectual property can be best defined as the intangible conceptions of the human mind that encompasses patents, trademarks, as well as copyrights. It is basically a grouping of property (Greenhalgh and Rogers, 2010). The law of intellectual property gives the owner of the property exclusive rights to exploit and benefit from his creation since it has commercial value attached to it (Ponce et al., 2016)

Therefore, protection of intellectual property is for the purposes of encouraging people to think and come up with new thoughts that will benefit all as the owner enjoys monopoly of exploitation. There is a very pertinent need to come up with a good protection plan by the original creator for efficiency and complete enjoyment of the intellectual ownership rights (Roberts, 2016). This report discusses the 3D bicycle parking concept that will serve as a solution to parking of bicycles and enhanced use of available space for parking. Due to the indiscriminate challenges posed by bicycles, one being parking, the thought of 3D will improve this issue. Included in this report is the practicability of this concept. In addition to this, the report will discuss appropriate issues on intellectual property like the digital copyrights and the available solution for their protection

 

2. Competitors of the bicycle parking concept

Currently, there are several ways of bicycle parking. However, issues of illegal parking are still very high in many countries in the current dispensation across the globe. This means that new ideas on parking have a niche in the market that they can serve and actually make people’s lives better. The 3D technique is a unique design that will be both time and space effective. In the current bicycle parking industry, people use the following bike rack designs for parking. First, there is the U-rack (also called Sheffield rack), which is a simple stand mostly used in the urban areas as it takes small space (Cochran, 2017). With this design, a relatively larger space is left for the pedestrians. Another competitor is the wave design, also called serpentine. This is also a kind of U- rack design which has been extended. With the serpentine design, it holds more bicycles (Yu, 2007). The limitation of this design is that it only links with the frame of the bicycle by one point instead of two. The main challenge associated with this kind or rack is that the bicycles are prone to falling very easily (Cochran, 2017).

A comparison between consumer confidence and investor confidence indices in Cross-sectional returns

3.0. AFP RESEARCH METHODOLOGY:

3.1 Research Approach

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.

 

3.2 Research 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

3.4.1 What was the data?

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.

 

3.4.4 Variable measurement

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

3.5.1 Data Analysis

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

 

EVENT ANALYSIS

 

1. Background

Read S&P news announcement ‘AT&T Inc. (NYSE: T) entered into a definitive agreement to acquire Time Warner Inc.’ (NYSE:TWX)’ (S&P case study enclosed in Appendix 1). Perform the following tasks of analysis and write up your finding and research in a report format, firstly with your group for Coursework 1, and secondly, write your individual report for Coursework 2. You are encouraged to conduct research on the effects of the news on share price and outline your analysis of the event.

This is an ongoing case of M&A. The study should emphasize the state of the play, valuation and trading strategy going forward. Students are encouraged to take a forward-looking view on the future of acquisition event. Corporate announcements can be found on Time Warner website below:

http://www.timewarner.com/investors/-w66%269%23%24Gf2%2525wUvPC_8QRY3%2APKFFYd%24p

 

2. Objectives

The assessment is made up of two parts with the weight and word count shown below.

• Coursework 1: Group Work Report (40%), Word Count: 1,500 Words
• Coursework 2: Words Individual Report (60%), Word Count: 2,000 Words

Group members are randomly assigned and cannot be changed representing real work setting where you can’t choose who you work with. Students are required to complete both parts.

Coursework 1: Group Work Report (40%)

This assignment is in the form of a group coursework report based on a case study of Merger and Acquisition (M&A) event based on the above case study of AT&T acquisition of Time Warner. The purpose of group work report is to develop relevant Excel templates to provide valuation and interpret price impacts following the event.

• Conduct in-depth background research to enhance the analysis of the acquisition event. Such research should demonstrate in-depth understanding on the working of the sector. You should set up a timeline (see Section 3 below) to reflect the chronicle of events and key dates. (20%)
• Conduct comprehensive valuation on AT&T and Time Warner prior to the acquisition announcement. Your valuation should use relevant valuation technique(s) to arrive at an appropriately discounted present value (per share) for BAT and Reynolds. (40%)
• Evaluate the extent of price impacts on AT&T and Time Warner following the news announcements on acquisition. Does the movement of share price reflect the insights from Efficient Market Hypothesis (EMH)? (40%)

Coursework 2: Individual Report (60%)

This assignment is the form of an individual coursework report based on the same case study albeit with a different focus on event analysis and trade. The purpose is to develop relevant Excel templates to conduct event studies to test market efficiency. Based on the result of event studies, trading strategies and instruments are to be applied to exploit price efficiency/inefficiency during the process of acquisition to arrive at appropriate conclusion and recommendation for the deal.

• Conduct event analysis to test EMH and derive your trading profit from the event. An event analysis template is provided separately based on Chapter 14 contents of Simon Benninga textbook ‘Financial Modelling (4th edition)’. (40%)
• You are required to demonstrate trading strategies and instruments that would be appropriate to exploit price efficiency/inefficiency during the process of acquisition. Your analysis should forecast possible trading profit going forward until the appropriate cut-off date. (40%)
• Conclusion and Recommendation. Conclude your analysis based on the above analysis and recommend appropriate course of action for trading on this M&A event (10%)
• Award for Class Participation (10%)

Class participation grade is in based on your seminar tutor’s discretion for your attendance and participation in class. Research and originality award research and original thinking that go beyond standard analysis and template to derive new insights.

3. Timeline

The announcement of the above event by S&P Capital IQ occurred on 22 October 2016. The cut-off or last date of your analysis should be 1 October 2017.

Respectively, your estimation window* should run at least one year before the event announcement date, e.g. 22 October 2015.

Your event window should have a cut-off or last date on 1 October 2017. You can also simulate price behaviours for both companies going forward passing 1 October 2017 if you want to but this should have no bearing on the result of the assessment.

*See Chapter 14 Simon Benninga’s textbook for the definition of ‘estimation window’.

If in need of the paper please inbox the page.

 

 

King Ferdinand and Queen Isabella 1 of Spain and the reason why they financed Columbus journey

 

King Ferdinand and Queen Isabella 1 of Spain and the reason why they financed Columbus journey

There are two main reasons why King Ferdinand II and Queen Isabella 1 decided to finance the journey of Columbus. The first one is Trade. The two royals believed that there was a shorter route from Spain to Asia (Landau, 18). The problem with the current route that they were using is that they would probably need to use the Mediterranean route which was governed by Muslims. By avoiding Muslims and not trading with them due to the nature of their crusades, they would have access to Asians directly without an intermediary. Both Ferdinand and Isabella realized that if Columbus would find a shorter route that would avoid the Mediterranean Sea and actually a route existed through the Atlantic Ocean to Asia, then Spain would become a world power and be able to control their trade with the Asians without involving the Muslims (Landau, 18).

The second reason is the spread of Christianity. As much as the main aim of Columbus was to make profit by finding a route through the Atlantic Ocean, both Ferdinand and Isabella realized that if a new route was found, this would be a good opportunity to spread Christianity (Landau, 19). During their reign, the Christianity was wide spread in Spain and had become one of the largest religion especially Catholicism. Since both Isabella and Ferdinand were Christian believers and supported the spread of the gospel, they wanted their religion to spread across the world as far as possible. At that time, Native Americans who did not convert their religion to Christianity were killed which led to a mass genocide. If Columbus would find a new route, this meant that there would be a direct contact between the Asia and Spain implying that spreading Christianity would be an easy task (Landau, 19). If both Asians and Europeans would be Christians, this meant that they would be more powerful than the Muslims therefore being able to control the world trade including the Mediterranean trade.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

BIBLIOGRAPHY

Landau, Elaine. Celebrating Columbus Day. Enslow Publishers, 2012

 

ONLINE LENDING

INTRODUCTION

The information technology wave has hit all sectors in which the banking sector has not been left behind. With online industry becoming more convenient and helpful, many users are turning to online banking to provide for their needs (Bouteille and Coogan, 2013). One platform that has become popular in the online banking sector is the online/marketplace platform in which lenders and borrowers are linked through an online platform. This platform has proved useful as it is not only innovative but provides a new method to fund borrowers with credit (King, 2010). This service has become widespread as it not only impacts the borrowers but provides a lending experience that traditional banking do not offer. However, this platform is different from the traditional banking system and offers great possibilities for the future. This paper is going to discuss the new model of online marketplace and how different it is from conventional banking together with the financial risks involved. In addition to that, the paper will analyse whether such a system can weather a downturn and offer recommendations on some regulatory frameworks that can be helpful in online/marketplace lending practices.

1. Describe the new market model of online/marketplace lending, as discussed in the article. What are the major differences from conventional bank lending?

The online /market place lending is a new lending system in which borrowers and lenders can access and provide loans through an online platform in which their profiles can be viewed (King, 2010). After borrowers have made their requests, different lenders can fund the project since the amount the borrower has requested is displayed on the platform more like online shopping in which one picks the item that has attracted them the most (Wack, 2015).  Companies which provide the platform organize the entire process in which the application of loans is screened together with the risk associated with the borrower. In addition to that, such platforms ensure that the money borrowed is sent back to the lenders in due time.

In addition to that, some online/marketplace lending do not offer the investor the chance to select the type of loans they would like to invest in. Such platforms offers a general guideline in which the loans are already classified based on the risk tolerance. These platforms offer loans which are in turn paid back with a certain amount of interest (Zhang et al, 2016). Therefore, such a platform can be considered as one which matches borrowers with loans that lack security from their prospective lenders. The borrower will receive their money after the platform has carried a borrower assessment. This means that unlike other businesses which rely on the difference on the amount of money collected from the borrower, the platforms mainly rely on the services they provide as they generally link up borrowers and lenders.

The other characteristic of the online/market place lending is the credit scoring techniques that are used by the platform coupled with their operations which are based online (Bouteille and Coogan, 2013). Their credit scoring is mainly applied in the extension or improvement of credit that is offered to both the businesses and individuals.  The main application process for these online/marketplace lending platforms. The first step which is the loan application and credit evaluation is one in which potential borrowers fill in both their personal and financial information that is provided by the platform (Bouteille and Coogan, 2013). After the form is fully filled and sent through the internet, the company will review the information provided and gauge whether the borrower is worthy of credit and verify the information given through screening. The screening process involves using information from employers. In a scenario where information from employers is not available, then they will turn to other sources such as previous credit score used (Wack, 2015).   If a borrower is found eligible, then the interest rates are sent out to them. In some cases, the rates are negotiable to both the borrower and the lender. It is important to note that the interest rate that the borrower receives includes the service charge of the online platform (King, 2010). This is because such platforms only make money through the services they provide and not through the interest rates like banks. If the borrower is satisfied with the terms and conditions that are given to them, the loan is then disbursed to them.

There are various differences that exist between conventional banking and online/marketplace lending. The first difference is that banks have specialized to act as an intercessor between the borrower and the saver (Zhang et al, 2016). They mainly focus on lending money to borrowers and paying interest to savers and depositors. However, for online/marketplace lending, their main work is to link up the lender and borrower through their online platforms (PWC, 2015).

The second difference is the way in which conventional banks generate their income. Conventional banking mainly put all their risks on their balance sheet in that they balance between the money deposited and the money that they have received as interest (Wack, 2015). However, for thee online platforms, they mainly rely on an external party to take the risk as they do not have the money to lend. They only act as a platform as they do not earn any interest therefore incurring no profit or losses.

The third difference is the fact that conventional banking requires capital all the time in order to absorb the losses that they acquire while for online/marketplace lending, they mainly rely on the amount that they charge for services (Zhang et al, 2016).  The last difference is that depositors have limited access and know-how of how the funds they have deposited is used while in online/marketplace lending, the usage of money is transparent to the lenders.

1. What kind of financial risks are present in online lending? What could be the effects on an economy’s financial stability, if the practice of marketplace lending substantially increases?

Within the last ten years, there has been numerous discussions on online lending industry, a growing industry which provides end to end loan experience via online delivery (King, 2010). Much has been on its use of technological innovations to expand and simplify the access of capital by consumers, its standpoint on regulation and the threat it possess to the tradition financial firms.  One of the financial risks presented include the ability to scale. One of the key financial risk is credit risk through bias recognition (King, 2010).  The manner in which online credit institutions provide loans to lenders is quite different from the traditional methods. However, this is not the case with online lending as the consumers are just given loans without much consideration which leads to risk of not paying back and eventually potential liquidity risk.

In addition to that, there exists a volatile investor confidence.  Often, an investor driven lensing model depends on the capability of the online lender to attract funning from institutional vendors, financial institutions and venture capitalists (PWC, 2015). However, as the online lending industry has matured and continues to attract funding   from the online investment communities, the industry is relatively growing. However, there is concern on investor retention and its effects on an economy’s financial stability, if the practice of marketplace lending substantially increase.  Investors are reluctant s there lacks predicable cash flow, increasing competition from the traditional markets and untested credit risk assessments. In addition to that, funding challenges arise from the current activities in pricing and the downgrade reviews of securitization transactions.

Another key factor is that there lack internal control and oversight on the online lending industry (Bouteille and Coogan, 2013).  A number of online lenders can easily change the information on their loans so as to make themselves look more attractive.  Incidents as such greatly affect investor confidence and the ability of the industry to stabilize due to manipulation. There lacks ways of preventing and monitoring fraud as most of the transactions are carried out online (Bouteille and Coogan, 2013). It is possible for individuals and corporations to put up a fake profile which fits into the credit requirements especially through identity theft. Therefore, this indicates that majority of the online lending companies can be subjected to borrower fraud meaning that it is not a fraud proof business

Risks as such could have effects on an economy’s financial stability, if the practice of marketplace lending substantially increases. This can be attributed mostly to the unregulated and unprotected market. Traditional financial lending firms relied on government regulations and protections which greatly helped them in case of a repeat of the 2007/2008 global financial crisis. (King, 2010).

Therefore, with no regulations, the interest rates could easily go high. When consumers pay less in their interest rates they have more money to spend in the economy and this can easily lead to increased spending in the economy. Eventually productivity and output is increased generally. On the other hand, higher interest rates show that consumers cut on spending as they don’t have a lot of disposable income (King, 2010). In cases when higher interest rates go with increased lending standards from financial institutions there are fewer loans. Consumers cut back on spending which means decreased productivity and the general economy. This can easily lead to the banks crashing and the general economy through the ripple effect. Therefore, this could either go two ways, a good performance on the economy or decreased performance on the economy. Nevertheless, if measures are put in place to control the online lenders, then a positive effect is expected.

 

 

iii. As it is stated in the article, the market place bosses believe that “…they can weather a downturn because they do not own the loans they originate”. What is your view of this statement?

In the case of a downturn, the most likely event that the central bank will do is to reduce significantly the interest rates. However, this will have a negative effect on the p2p as most of these online lending platforms have rates that range around 5 percent (King, 2010). This means that they do not have the capacity to move to smaller rates. Since the online lending platform is entirely based on the supply and demand of credit in which the borrowing and lending rates can be altered as one desires, this means that if the platform moves towards zero rates, they will attract money. Such a move is impossible and can only be achieved by the Central Bank in case of a downturn. This means that such platforms are unlikely to survive in the case of a downturn (HM Treasury, 2014).

In addition to that, in a case whereby a downturn would be experienced, this means that the marketplace and online lenders would have to deal with the issue of debt restructuring (King, 2010). Compared to banks, the platform lacks sufficient information about lenders in the banking system. Therefore, for such online lenders to be successful, they have to have such a system in place which is quite a new task to them. This means that banks would flourish in such a scenario since it has in place a permanent system which deals with a downturn. Despite the fact that lenders in the platforms undergo through a vigorous credit check before they are given money, this system does not seem to be as resilient as the bank sector. The transformation of the industry in to as table platform is taking long and seems to be far from reality (HM Treasury, 2014). This is despite the fact that underwriting in the online lending platform is strict and more data options for lenders are being explored.

The rate of growth for online lenders is stagnant and in case of an economic downturn, the lenders would suffer. However, to prepare for this they have to position themselves well in the market with regulatory frameworks that protect both the lender and the creditor (HM Treasury, 2014). This is in terms of the way in which they can handle the evolving financial instability together with building a stable portfolio performance. Unlike banks which have proved to be profitable, these p2p lending platforms have proved to be unstable therefore in the event of a downturn, the pressure would significantly increase (Bouteille and Coogan, 2013).

The last issue to be addressed on why a downturn would significantly affect the p2p lenders is due to the nature of lending in the banking world. Since the financial crisis of 2008, banks have become more careful in relation to who they lend their loan and have significantly cut down their funding (PWC, 2015).  This means that as more banks have become strict, borrowers are turning to p2p lenders as a source of credit in which the rates are likely to be pushed up due to the attractiveness of the platform. However, majority of these p2p lenders and online platforms mainly rely on banks for lending. Therefore, in downturn case, banks are likely to pull back from sectors that are more vulnerable like the P2P lenders because they are trying to reduce the risk exposure that they suffered in 2008 (Bouteille and Coogan, 2013). Therefore, such a system would likely collapse in the event of a downturn since the platforms are lending businesses that have existing overdrafts and do not have the ability to survive in the case of a downturn. They may in turn end up struggling if there is lack of fund access.

Lastly, in the case of an economic downturn, liquidity might end being the biggest issue that might need to be addressed. P2P lenders might extend the loan maturity or loans might be hard to access (King, 2010). This will greatly affect lenders that might want to diversify and extend their businesses. In the end, due to the liquidity issues, a downturn means that there will be lack of enough funds to withdraw or reinvest therefore affecting the entire p2p platform.

1. How would you decide to incorporate such online/marketplace lending practices within a regulatory framework? Provide some practical recommendations.

There should be increase on the regulatory scrutiny in the online lending marketplace. . Recent concerns show that there lacks a compliance surveillance gap which leads to the increased attention on the regulators (Wack, 2015). Although online lenders often comply with the federal and state regulations, they rarely focus on regulatory litigations more so on their sublime lending practices and tax compliance standards.  Regulatory framework will also help deal with compliance costs which erode the on the low margins through use of surveillance which will help highlight violations just in time.

This means that the client lending experience needs to be enhanced. Upton date, majority of the traditional lending institutions have been able to go into the online lending platform through partnerships. Recent partnerships include firms such as Santander’ s  partnership with  JPMorgan Chase &    Co. ’ s with On Deck Kabbage  partnering with Santander (PWC, 2015). This enhances the experience of online lending as the approval time and the work of accessing a consumer’s credit risk profile is minimized and also at the same time made effective.

An additional way of incorporating such online/marketplace lending practices within a regulatory framework is through consolidating. There exists more than 200 lenders in the online lending industry who are competition for the 1 percent market shares while banks and other financial institutions are competing for the remaining 99 percent of the market (PWC, 2015). Therefore, by consolidating and differentiating themselves by following in   the regulatory framework the market can increase on the trust in the industry.

Retention by addressing the holistic financial needs of the clients (King, 2010). Majority of the traditional financial firms are entering the online market place through their current capabilities of lending. This means that three is room for other firms who don’t offer lending to succeed. Wealth managers and retirement providers can also do well through offering their holistic services mortgages and student loans can also increase retention as they have a longer and increased payout rate period.  Online borrowers infect provide   superior and better experience to their consumers through institutions as such which are within the regulatory framework (King, 2010).

CONCLUSION

In conclusion it is evident that online/marketplace platform offer a financial platform that link both borrowers and lenders who are looking for unsecured loans. Such online/marketplace platforms offer borrowers and lenders a platform can access and provide loans through an online platform in which their profiles can be viewed. Such platforms are different from banks as banks have specialized to act as an intercessor between the borrower and the saver. Moreover, banks requires capital all the time in order to absorb the losses that they acquire while for online/marketplace lending, they mainly rely on the amount that they charge for services. A downturn would negatively affect the system as there are no set regulations that govern the p2p system.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

REFERENCES

Bouteille, S., & Coogan, D. (2013). The Handbook of Credit Risk Management: Originating, Assessing, and Managing Credit Exposures. Wiley Finance.

King, B. (2010). How Customer Behavior and Technology Will Change the Future of Financial Services. Marshall Cavendish International Asia Pte Ltd.

Zhang, B., Baeck, P., Ziegler, T., Bone, J., & Garvey, K. (2016). Pushing Boundaries: the 2015 UK Alternative Finance Industry Report. Retrieved on 8^th October 2017 from https://www.nesta.org.uk/sites/default/files/pushing_boundaries_0.pdf

Wack, K. (2015). Shift Away from Retail Investors Heightens Risks in Online Lending. American Banker. Retrieved on 8^th October 2017 from http://www.americanbanker.com/news/marketplacelending/shift-away-from-retail-investors-heightens-risks-in-online-lending-1078534- 1.html

HM Treasury. (2014). Competition in banking: improving access to SME credit data – Consultations. Retrieved October 8, 2017, from https://www.gov.uk/government/consultations/competition-in-banking-improvingaccess-to-sme-credit-data

PWC. (2015). Peer Pressure: How Peer to Peer Lending Platforms are Transforming Consumer Finance. Retrieved on 8^th October 2017 from http://www.pwc.com/us/en/consumerfinance/publications/peer-to-peer-lending.html

 

 

 

 

 

TESCO AS A DIGITAL FIRM

TESCO AS A DIGITAL FIRM

Introduction

In this digital era, information technology plays an important part in running organizations. This is because information technology greatly assists in running the firm both effectively and efficiently. Majority of the firms who have digitally enabled their business relationships are known as digital firms (Leahy, 2012).  Some of the business relationships that are usually digitized in a firm involve the customer, suppliers and employees. This implies that the operations of the firm are mainly carried through digital networks in which the entire organization is linked. One of the main advantages of being a digital enabled firm is that information is available all the time and at any place (Diasio and Agell, 2009).  This is advantageous to the firm because unlike traditional firms in which the reaction to information was reactive, digital firms’ reaction to information provided is proactive. Such flexibility of responding to information immediately has enabled digital forms to be successful in their operations. One major firm that can be classified as a digital firm is Tesco. Not only has Tesco revolutionalised the supermarket chain industry but it has been on the forefront of adopting to new technologies in the market. This paper will seek to discuss Tesco as a digital firm and how the adoption of information technology has enabled the firm to be effective at its operations.

Background of Tesco

Tesco can be classified as one of the largest grocery retailer in the UK (Simms, 2007). Known for its ability to account for forty three percent of its sales online, Tesco has progressively moved its processes from the normal grocery shopping in which an individual had to come to the store physically to shop. Tesco was the first grocery store in the UK to go online through its website Tesco.com commonly known as Tesco Direct through which customers can be able to access goods that are in the store without physically going to the store (Simms, 2007). The online company Tesco.com became so successful for the firm such that in the year 2000, it was created as an entire subsidiary although Tesco is fully responsible for its operations. Separating Tesco.com from Tesco has been very beneficial to the company as the firm on its own is able to adopt to the changes that exist in the online retail business as a single entity. This has enabled Tesco.com to not only stay ahead of the game by being innovative but to maintain a larger share of the online grocery store.

 Information System Usage In Tesco

The integration of information system in any organization is very important in order to ensure that the processes of a company are carried out efficiently and effectively. Information system can be described as a combination of integrated components that is used to gather, process, store and distribute information in a firm that will assists in making decisions in the firm (Leahy, 2012).  Information systems assists in mainly four areas of operations in the firm. The four areas include communication, operations, records and decisions. This means that an effective information system should be able to assist the firm to carry out tasks in those four key areas. In relation to communication, the information system installed should be able to assist in communicating quickly and effectively in order for both employees and managers to receive real time data. This assists in dealing with any issues that arise immediately (Nash, 2006).  When it comes to operations, an effective information system should enable to assist the firm with the latest information about the firm in order to create a competitive edge. The third task of information system is to assist in decision making. Since the information system delivers information about the firm real time, this means that better decisions will be made as the information system will assist in showing the key indicators that will assist in making better decisions. The last task of an effective information system is to assists in record keeping. By keeping records of all the activities of the firm, the system can be able to locate where a certain problem is originating from and handle it based on the information that they have recorded (Diasio and Agell, 2009).

Figure 1; information system in Tesco(Diasio and Agell, 2009).

In any organization, there are several types of information systems that can be employed. They include The Decision Support System (DSS), Decision Support Systems (DSS), Executive Support Systems (ESS), Business Intelligence Applications, Customer Relationship Management Systems (CRM), Supply Chain Management Systems (SCM), Knowledge Management Systems (KMS), Enterprise Resource Planning Systems (ERP), Human Resource Management Systems (HRM) and E-commerce/M-commerce applications. In analysing Tesco and its application of information system, the first type of information system that will be analysed is the E-commerce/M-commerce applications.

Customer Relationship Management Systems (CRM)

Customer relationship management (CRM) can be referred to as the application of information technology through strategies in order to analyze the interactions of customers with the business and use the data collected in order to improve the relationship between the customer and the firm (Reinartz, Krafft and Hoyer, 2014).  In the end, this helps with increasing the sales of a firm and retention of customers. The main purpose of creating CRM systems is to combine any customers’ information using different channels in which the clients interact with the firm. Moreover, CRM assists in collecting more personal information about the customer together with what they prefer and what are their concerns about the firm (Reinartz, Krafft and Hoyer, 2014).

As discussed above, Tesco.com is an online platform whereby shoppers can purchase their groceries at the store at the click of their palm. Tesco.com was designed in such a way that customers who want to shop online can directly access the website from their desktop. Tesco.com was based on the fact that majority of their customers want to save time by shopping online and not driving to the store (Diasio and Agell, 2009).   The process of going to the store to pick up groceries has proved to be tedious and long as one is not only supposed to drive to the supermarket but also find a parking, manually go and pick up the items that they wanted, queue for payment processes and unload grocery shopping from the car. The system that Tesco has created has enabled the users of their platform to have a communication point in which they are able to order their items and have them delivered at their door step. This shows that the user experience at Tesco is unmatchable as it can be witnessed from the 43% of total sales which come from online shopping (Simms, 2007). When a customer wants to register to be a member in the site, they can upload photos and be able to send messages across the board in which Tesco uses the information collected to increase the users experience at the firm. Such information is linked to an individual store from which the firm is able to increase the user experience.

Tesco.com has redesigned their website over time. Since social media has become an important component of today’s world, Tesco understood the importance of social media as a key driver in enhancing the users’ experience therefore replicating the in store experience for all consumers. This was successfully managed by building a platform in which all aspects of Tesco were integrated in the system. Through tis, customers were able to interact with one another, with all employees of Tesco and the suppliers thereby building a large online community in which Tesco was able to gather more information about their store and what they need to improve (Diasio and Agell, 2009).   This system that Tesco created achieved all the main tasks of an information system which include communication, operations, records and decisions. In addition to that, Tesco has uploaded all the items they have at their store online implying to the customer that they can meet all their demands through online shopping.

The other way in which Tesco uses CRM effectively is through the use of the Tesco Club card. The Tesco club card is mainly used to reward loyal customers and also retention of clients by rewarding them for shopping with Tesco (Simms, 2007).   The Tesco Club card is important to Tesco as it assists in fathering more information about their users for example their name, the average amount of money they spend when shopping and what they prefer. The main purpose of the Tesco loyalty club card is to measure the loyalty of the customer by applying three main factors which include the value, preference and the frequency. Therefore, the customers’ loyalty is mainly measured using these three criteria.

Tesco’s club card can be described as one of the most innovative IT advancements applied by the firm. According to Reinartz, Krafft and Hoyer, (2014) the usage of loyalty cards is important to any firm as it assists the firm in converting the preferences of the customers in order to form not only trust but loyalty and mutual understanding. This means that by Tesco applying the usage of Tesco loyalty card, the firm is able to gain a competitive advantage over the rest of the stores. Some of the competitive advantage that Tesco has is knowing the current trends of the customers, which stores are more preferred than the others and the negotiating power of the clients. Tesco’s loyalty card is known as one of the most successful loyalty scheme ever witnessed with Britain alone having over eleven million active users and millions of others spreading across their many branches across the world (Tavana et al, 2013).

 

 

Decision Support System (DSS)

One component of the information system that Tesco has greatly applied is the Decision Support System (DSS). The DSS can be described as an information system that uses the data presented to it in analyzing the operations of the firms and assist in making better and faster decisions for the firm (Sprague and Carlson, 2012).  Mainly focused on collecting information, the DSS is used in collecting information in the daily business operation of the firm. There are various ways in which Tesco uses information to make decisions in the firm. The first way in which Tesco uses information system in making decisions is through which they introduced a system in which all the managers and employees could use a database in which they would check to see which items would need restocking instead of using employees to go to the store manually and check what is in store for them. This was important as it assisted the managers to make timely decision on what needed to be restocked immediately and what would not need restocking. This type of service saved time on both the employees and the customers of the store as items at the stores are available in real time.

Figure 2;DSS in Tesco  (Tavana et al, 2013).

The other way in which Tesco applied the decisions support system is through the usage of the RFID tagging system in which all the system was used in the distributions centers. The main purpose of the system was to monitor the inventory level of the firms and know what was out of stock or needed restocking both at their distribution centers and the stores (Tavana et al, 2013). This meant that the employees of the firm could order items that needed restocking in real time as the firm would be aware of the products that were running low. This system was very effective in decision making compared to the previously used system of guess work to know which products are in store and which ones were not.

The usage of information technology to assist in decision making is the use of in store video cameras. One famous in store video cameras that Tesco has applied is known as the broccoli camera which is responsible for detecting when vegetables in the store have depleted and need restocking (Nash, 2006).  The information is sent to the management to ensure that they are restocked immediately. In addition to that, the store has electronic shelf edge labels which are very useful in knowing the stock. In addition to that the labels assist the employees in saving valuable time that would be used in changing the paper labels that were previously used in the store. In addition to that, the electronic labelling allow instant changes in prices throughout the store at any time of promotional activities. Moreover, every employee in the store is provided with a portable smart badge. The main usage of the badge is to provide the staff of the store with more information about stock when an item is scanned. This assists the staff to answer any questions that the customers might be having.

This can only imply that all the decisions of the firm are carried out with the assistance of technology which is applied throughout the store. As seen from the analysis above, it is evident that majority of the decisions system at the operational level is done with the help of transactional processing systems such as the electronic shelf labelling discussed above. The main objective here is to carry out transactions with no uncertainty and ensure timely delivery and availability of goods (Nash, 2006). The transactional processing system is used to ensure that the activities of the firm are carried out in an accurate and speedy manner.

Moreover, the decision making at the operation level is assisted with the information system that is used in understanding the daily sales occurrence together with the cash sales and the cash tills (Tavana et al, 2013).  It also assists with automatically notifying the employees when an item is out of stock so that they information can be directly sent to the suppliers. The DSS system applied at Tesco has greatly assisted in managing the inventory and in processing transactions at the store effectively and quickly.

In addition to that the RFID technology which Tesco applies greatly assists in ensuring that the correct quantity of item is available at the shelf and is well stocked. In addition to that, there is a system which is applicable in monitoring the number of customers that are shopping at a specific time (Humby, Hunt and Phillips, 2010). The system greatly assists in decision making as it is useful in predicting whether there is need for extra checkouts so that clients can avoid queuing in the store. Additionally, more information technology is applied as heat sensing technology whereby the till lines are monitored

The decision support system is also applied at the managerial level assists the managers in controlling, monitoring and making decision and administrative level. At the administrative level, the decision support system that is in place shows the stock cards together with the sales that have been sold weekly in each store for every product (Humby, Hunt and Phillips, 2010).  This is very useful as it assists in identifying both the week performers so that they can be advertised more or given more promotional activities and the strong performers so that they can be restocked more. Such a system assists the managers an effective decision is made on which products need to be continued and which ones need to be discontinued.

In times when there are promotional activities at the store, sales become difficult to predict. This means that reports at specifically done at that time that alert the management on items that are on stock that are low therefore enabling managers to order for more items before they ran out of stock. The Decision Support System is also employed at the human resource level to predict the number of hour’s employees’ work and the time in which they report to work. Such a clocking system that monitors employees is important as it assists he managers to make the decision on the payroll depending on the hours at work.

It is important to note that since all the information of the employees is stored electronically, it is easy to access employee information based on their performance and the hours worked. Decision Support System is also applied at the executive level in which the long term strategy plans of the firms are applied (Sprague and Carlson, 2012).   The decisions that are carried out here are usually long term and affect the way the company operates. They are mainly concerned with creating a competitive advantage for the firm and understanding and creating current market trends in the marketplace. The decisions made at the executive level is usually based on all the information collected internally at the firm and externally. The main objective of the decision support system at this level is to ensure that the future trends are evaluated and not missed using the data that has been collected at the operational level. Tesco’s management is responsible for ensuring that long terms strategies are beneficial to the store. The information collected assist the management in making decisions such as which store is not performing well according to the set levels and which locations need new Tesco store (Sprague and Carlson, 2012).  This decisions assist in knowing which stores need to be closed down due to underperformance. This shows that the decision support system is applied at all levels of operation at Tesco which has ensured that Tesco remains competitive and marketable throughout all the years.

Conclusion

In conclusion, it is evident that Tesco has greatly applied the usage of information system to ensure that they remain the leading grocery store in the UK. This paper has analyzed information system in two main areas which is the customer relationship management and the decision support system. Tesco has greatly use customer relationship management system in understanding their customers and ensuring that the relationship between the customer and the firm has improved which in the end, this helps with increasing the sales of a firm and retention of customers. Some of the customer relationship management system that Tesco applies include the Tesco loyalty club card and Tesco direct which is an online store that allows customers to shop online and assists in collecting meaningful information about the customer.  In using the decision support system as an information system, Tesco has managed to gain a competitive advantage as the data collected from the operational level is used to make important decisions in restocking, queue lines, closing of poor performing stores and opening of new stores.

 

 

 

 

 

 

 

 

 

 

 

 

References

Diasio, S., & Agell, N. (2009). The evolution of expertise in decision support technologies: A challenge for organizations, CSCWD, pp. 692–697. 13th International Conference on Computer Supported Cooperative Work in Design, 2009.

Humby, C., Hunt, T. & Phillips, T. (2010). Scoring points: How Tesco continues to win customer loyalty. London & Philadelphia: Kogan Page.

Leahy, T. (2012). Management in 10 Words. London: Random House

Nash, B. (2006). Fair-Trade and the growth of ethical consumerism within the mainstream: an investigation into the Tesco consumer. Leeds: University of Leeds.

Reinartz, W. Krafft, M. Hoyer, W. D. (2014). The Customer Relationship Management Process: Its Measurement and Impact on Performance. Journal of Marketing Research. 41 (3): 293–305.

Simms, A. (2007). Tescopoly: How one shop came out on top and why it matters. London: Constable.

Sprague, R. H. & Carlson E.D. (2012). Building effective decision support systems. Englewood Cliffs, N.J., Prentice-Hall.

Tavana, A., Feizbakhsh. F., Saeed.; T., Alireza V., & Kakouie, S. (2013). Theoretical Models of Customer Relationship Management in Organizations. International Journal of Business and Behavioral Sciences. 3 (11).

 

 

AHP FRAMEWORK USAGE

INTRODUCTION

After the financial crisis of 2008, investors have become more concerned with the way they invest their money. The financial crisis forced a lot of banks to close down which proved that the banks were becoming more risky to handle money. This has forced a lot of investors to look for alternative options on where they will invest their money instead of leaving the money laying idle in the bank. The stock market has become quite attractive as a source of investment as the returns have proved to be attractive. However, according to Gavalec, Ramík & Zimmermann (2015), the higher the return, the more risky the invest is. As investors are not interested in loosing investment, it has become crucially important to analyse the stock that one is investing in before making a decision. An investment in the stock should neither produce a loss for the investor nor make high returns that in the end will only turn to losses. There are various ways in which an investor can use to know whether the investment they are making is viable or not. One of the most credible method is the Analytic Hierarchal Process commonly referred to as AHP. The AHP can be described as a measurement method which is used in analyzing and assisting in making complex decisions (Kabir and Ahsan, 2011).  In analyzing the bank stock market of Australia, this paper will use the AHP method to assist the investor in deciding which investment decision to make. The three companies that will be analysed include HSBC, Bank of Queensland and Westpac. The three companies that were chosen are all in the Australian Bank Stock.

BACKGROUND OF THE THREE COMPANIES CHOSEN

One of the most lucrative sectors to invest in is the banking sector. This is because banks are protected by central banks in case of any financial crisis. In addition to that, banks have proved to be perform well and have good returns for investments. The banks that will be analysed include the HSBC bank of Australia, the Bank of Queensland and Westpac bank of Australia. They will be analysed below.

HSBC

The HSBC bank which was previously known as the Hong Kong Bank since 1965 operated as a finance company before being given a license to operate as a bank in 1986. The bank belongs to the HSBC Group bank which operates worldwide. The HBSC Bank operates like any other bank in Australia offering services to both retail and commercial sectors. In total, the bank has thirty six branches in Australia. Some of the services that the bank offers include cash management, payments, financial market analysis, financial planning and treasury services.

BANK OF QUEENSLAND

The Bank of Queensland commonly referred to as the BOQ is an Australian owned bank specializing in retail with its main headquarters stationed in Brisbane. Known as one of the founding financial institutions in Australia, the bank has opened over two hundred and fifty two branches all over Australia. Some of the major achievements of the bank include being recognized in the role that it has played in Australia in the past century and the role it plays in the Australian Economy.

WESTPAC BANK

The Westpac bank, registered as the Westpac Banking Corporation is a financial service Australian bank with its headquarters in Sydney. It has been ranked on the same level as the Bank of Queensland as they are both ranked as the big four banks in Australia. Westpac Bank has the biggest numbers of branches in Australia with one thousand, four hundred and twenty nine branches operating all over the country. In terms of assets, Westpac Bank can be categorized as the second largest. In addition to that, the bank has performed well in New Zealand as it is ranked as the second largest bank in New Zealand.

USING AHP FRAMEWORK IN ANALYSING THE THREE BANKS CHOSEN FOR STOCK

In selecting a stock portfolio, there are three main factors and objectives that will influence which firms will be selected in the portfolio. The factors that will be used in the analysis of the three banks include extrinsic factors, intrinsic factors and the objectives of the investors. The extrinsic factors include the external factors that affect the performance of the firm. The intrinsic factors include the operational factors that is the internal factors that affect the performance of the bank. The last factor which is the objectives of the investors include the values that the investors considered important when undertaking an investment in the stock market. In using the AHP framework, it is important to consider the risk associated with the future which might affect the performance of the firm.

EXTRISTIC FACTORS ANALYSIS

In analyzing the extrinsic factors of the firm, there are four main factors that will be considered in the analysis. They include the PEST analysis which include the political factors, the economic factors, the social factors and lastly technological factors. Under economic factors, several factors that influence the performance of the firm will be considered. They include the interest rate charged, the elasticity of demand and the elasticity of supply together with the conditions of employment of the firms. In relation to the political factors that influence the performance of the firm, several factors that were considered include the regulations of the government, the exposure internationally and lastly the employment conditions involved. Under the social extrinsic factors, some of the factors that will be considered include the age distribution of the employees and firms, educational achievement of the community involved, the age distribution of the community and lastly the family disintegration. The last factor that will be analysed is technological extrinsic factors which will include government involvement and the state of technology.

PAIRWISE COMPARISON OF EXTRINSTIC FACTORS

In analyzing the extrinsic factors mentioned above namely the political factors, economical factors, social factors and technological factors, a pairwise comparison will be made. The importance of carrying out a pairwise comparison is to determine which factors operate in a high risk, medium risk or low risk environment. The analysis for the banking industry for the extrinsic factors depending on the risk level has been shown on the table below:

 

	High Risk				Medium Risk				Low Risk
Firm	E	P	S	T	E	P	S	T	E	P	S	T
Economical	1.00	5.00	3.00	0.33	1.00	7.00	5.00	3.00	1.00	7.00	0.20	5.00
Political	0.33	1.00	5.00	0.20	0.20	1.00	3.00	4.00	0.20	1.00	0.33	3.00
Social	0.33	0.25	1.00	0.11	0.13	0.14	1.00	7.00	5.00	5.00	1.00	2.00
Technological	5.00	8.00	9.00	1.00	1.00	5.00	7.00	1.00	0.20	0.33	0.14	1
Total Sum	6.66	14.25	18.00	1.64	2.33	13.14	16.00	15.00	6.40	13.33	1.68	11.00

 

 

PRIOROTIES FOR DIFFERENT RISK LEVELS

	PRIORITIES FOR DIFFERENT RISK LEVEL
	Normalized Comparison
High Risk	Economic	Political	Social	Technological	Average Row Sum
Economic	0.22	0.50	0.30	0.33	0.34
Political	0.33	0.11	5.00	0.20	1.41
Social	0.33	0.25	1.00	0.11	0.42
Technological	0.30	0.80	0.90	0.10	0.53
	Normalized Comparison
Medium Risk	Economic	Political	Social	Technological	Average Row Sum
Economic	0.50	0.40	0.30	0.33	0.38
Political	0.33	0.11	0.60	0.20	0.31
Social	0.33	0.25	0.18	0.11	0.22
Technological	0.42	0.55	0.65	0.43	0.51
	Normalized Comparison
Low Risk	Economic	Political	Social	Technological	AverageRow Sum
Economic	0.22	0.70	0.45	0.33	0.43
Political	0.33	0.11	0.45	0.20	0.27
Social	0.33	0.25	0.11	0.11	0.20
Technological	0.56	0.43	0.77	0.20	0.49

 

PRIORITIES FOR EACH RISK LEVEL

	PRIOROTIES FOR EACH RISK LEVEL
Risk	Economic	Political	Social	Technological
High Risk	0.34	1.41	0.42	0.53
Medium Risk	0.38	0.31	0.22	0.51
Low Risk	0.43	0.27	0.2	0.49
Average	0.383333	0.663333	0.28	0.51

 

Based on the three risk level analysed, it is clear to see that one type of future is more attractive compared to the other. From the table shown above, the average which can be equated to the weighted comparison shows the following

Economic risk factor for the banking industry is 0.38

Political risk factor for the banking industry is 0.67

Social risk factor for the banking industry is 0.28

Technological risk factor for the banking industry is 0.51

 

INDIVIDUAL EXTRINSTIC FACTORS ANALYSED

Economic	E C	ED	ES	IE	IR
Employment conditions	1.00	5.00	0.25	0.14	0.20
Elasticity of demand	0.33	1.00	7.00	9.00	0.33
Elasticity of supply	5.00	0.33	1.00	0.33	0.20
International Economy	7.00	0.20	0.17	1.00	5.00
Interest rates	3.00	5.00	0.11	9.00	1.00
Total Sum	16.33	11.53	8.53	19.48	6.73
Political	GT	IE	EC
Govt Regulations	1.00	3.00	4.00
International Exposure	0.14	1.00	5.00
Employment Conditions	9.00	7.00	1.00
Total Sum	10.14	11.00	10.00
Social	FD	AD	EA	EC
Family Disintegration	1.00	0.14	9.00	3.00
Age Distribution	0.33	1.00	3.00	5.00
Education Achievement	3.00	0.14	1.00	0.20
Employment Conditions	0.33	5.00	7.00	1.00
Total Sum	4.67	6.29	20.00	9.20
Economical	ST	GI
State of Technology	1.00	4.00
Govt Involvement	5.00	1.00
Total Sum	6.00	5.00

 

PRIORITIES FOR DIFFERENT ECONOMICAL FACTORS

Economical	Employment Conditions	Elasticity Of Demand	Elasticity of Supply	International Economy	Interest rates	Weighted
Employment Conditions	0.2	0.8	0.55	0.7	0.9	0.63
Elasticity of Demand	0.34	0.5	0.67	0.5	0.33	0.468
Elasticity of Supply	0.78	0.65	0.56	0.43	0.45	0.574
International Economy	0.55	0.76	0.56	0.9	0.76	0.706
Interest Rates	0.78	0.88	0.54	0.45	0.88	0.706
Political	Govt Regulations	International Exposure	Employment Conditions	Weighted
Govt Regulations	0.9	0.77	0.55	0.74
International Exposure	0.5	0.4	0.43	0.443333333
Employment Conditions	0.76	0.43	0.5	0.563333333
Social	Family Disintegration	Age Distribution	Education Achievement	Employment Conditions	Weighted
Family Disintegration	0.6	0.7	0.88	0.98	0.79
Age Distribution	0.76	0.55	0.65	0.78	0.685
Education achievement	0.55	0.67	0.65	0.87	0.685
Employment conditions	0.54	0.33	0.3	0.56	0.4325
Technological	Technology State	Government Involvement	Weighted
Technology State	0.6	0.5	0.55
Government Involvement	0.55	0.76	0.655

 

FINAL WEIGHTED INDIVIDUAL EXTRINTIC FACTORS

Economic		Weights	Final Weights
0.38	Employment Conditions	0.63	0.2394
	Elasticity of Demand	0.468	0.17784
	Elasticity of Supply	0.574	0.21812
	International Economy	0.706	0.26828
	Interest Rates	0.706	0.26828
Political
0.67	Govt Regulations	0.74	0.4958
	International Exposure	0.44	0.2948
	Employment Conditions	0.56	0.3752
Social
0.28	Family Disintegration	0.79	0.2212
	Age Distribution	0.685	0.18424
	Education achievement	0.685	0.18424
	Employment conditions	0.4325	0.1218
Technological
0.51	Technology State	0.55	0.2805
	Government Involvement	0.655	0.33405

 

LIST OF EXTRINSTIC CRITERIA

All the weights mentioned above are all the individual extrinsic factors that influence all the weights. To calculate the normalized weights, each weight will be divided by the total of the list mentioned below. This list will be used as the final extrinsic criteria

 

LIST OF EXTRINSTIC FACTORS CONSIDERED
	Weights	Normalized weights
State of Technology	0.28	0.20438
Employment Conditions	0.43	0.313869
Elasticity of Demand	0.18	0.131387
Interest Rates	0.26	0.189781
Family Disintegration	0.22	0.160584
	1.37	1

 

Technology	HSBC	BOQ	Westpac	Weights
HSBC	0.65	0.77	0.89	0.77
BOQ	0.45	0.56	0.34	0.45
Westpac	0.66	0.45	0.7	0.603333
Employment Conditions	HSBC	BOQ	Westpac	Weights
HSBC	0.6	0.98	0.45	0.676667
BOQ	0.3	0.77	0.37	0.48
Westpac	0.54	0.54	0.45	0.51
Elasticity Of Demand	HSBC	BOQ	Westpac	Weights
HSBC	0.88	0.2	0.32	0.466667
BOQ	0.45	0.6	0.44	0.496667
Westpac	0.54	0.3	0.66	0.5
Interest Rates	HSBC	BOQ	Westpac	Weights
HSBC	0.54	0.65	0.56	0.583333
BOQ	0.45	0.87	0.65	0.656667
Westpac	0.66	0.78	0.76	0.733333

 

Family Disintegration	HSBC	BOQ	Westpac	Weights
HSBC	0.34	0.51	0.71	0.52
BOQ	0.76	0.71	0.84	0.77
Westpac	0.67	0.88	0.7	0.75

 

Weights of Firms for Extrinsic Criteria

The table below shows the weights for the three banks for each individual extrinsic criteria chosen.

	0.20	0.31	0.13	0.18	0.16
Firm	State of Technology	Employment Conditions	Elasticity of Demand	Interest Rates	Family Disintegration
HSBC	0.77	0.67	0.46	0.58	0.52
BOQ	0.45	0.48	0.49	0.65	0.77
WESTPAC	0.6	0.51	0.5	0.73	0.75

 

Overall Prioritised List of Firms

In order to calculate the overall prioritized list of the banks listed, multiplication was done for the individual weights criteria of the firms chosen with the individual weights of the individual extrinsic factors.

 

Firm	State of Technology	Employment Conditions	Elasticity of Demand	Interest Rates	Family Disintegration	Weights
HSBC	0.154	0.2077	0.0598	0.1044	0.0832	0.12182	0.348795
BOQ	0.09	0.1488	0.0637	0.117	0.1232	0.10854	0.310771
WESTPAC	0.12	0.1581	0.065	0.1314	0.12	0.1189	0.340434
						0.34926	1

 

 

So from the analysis done, it is evident that if the extrinsic factor is to be considered, the HSBC bank is performing better compared to the BOQ and Westpac bank.

INTRISTIC FACTORS

The next analysis that will be carried out is on the internal factors that affect the operation of the firm. Intrinsic factors greatly influence how the firm operate. Some of the intrinsic factors that will be considered include innovativeness, management quality, Research and development and finally sales.

LIST OF INTRISTIC FACTORS

INTRISTIC FACTORS	Innovativeness	Management Quality	Research and Development	Sales	Weighted
Innovativeness	0.7	0.81	0.76	0.56	0.7075
Management Quality	0.77	0.64	0.68	0.71	0.7
Research and Development	0.8	0.5	0.6	0.84	0.685
Sales	0.87	0.66	0.76	0.65	0.735

 

 

Intrinsic factors	Standardized weights	Normalised weights
Innovativeness	0.7	0.24822695
Management Quality	0.7	0.24822695
Research and Development	0.69	0.244680851
Sales	0.73	0.258865248
	2.82	1

 

 

Innovativeness	HSBC	BOQ	Westpac	Weights
HSBC	0.8	0.5	0.77	0.69
BOQ	0.56	0.66	0.85	0.69
Westpac	0.65	0.8	0.78	0.743333
Management Quality	HSBC	BOQ	Westpac
HSBC	0.5	0.66	0.67	0.61
BOQ	0.6	0.7	0.58	0.626667
Westpac	0.76	0.85	0.7	0.77
Research & Development	HSBC	BOQ	Westpac
HSBC	0.76	0.78	0.61	0.716667
BOQ	0.55	0.8	0.88	0.743333
Westpac	0.67	0.6	0.87	0.713333
Sales	HSBC	BOQ	Westpac
HSBC	0.7	0.67	0.78	0.716667
BOQ	0.5	0.77	0.8	0.69
Westpac	0.67	0.76	0.81	0.746667

 

 

	INTRISTIC FACTORS
	0.25	0.25	0.24	0.26
Firm	Innovativeness	Management Quality	Research & Development	Sales
HSBC	0.69	0.61	0.71	0.71
BOQ	0.69	0.62	0.74	0.69
Westpac	0.74	0.77	0.71	0.74

 

 

Firm	Innovativeness	Management Quality	Research & Development	Sales	Weights
HSBC	0.1725	0.1525	0.1704	0.1846	0.17
BOQ	0.1725	0.155	0.1776	0.1794	0.171125
Westpac	0.185	0.1925	0.1704	0.1924	0.185075

 

Overall Prioritised List of Firms

In order to calculate the overall prioritized list of the banks listed, multiplication was done for the individual weights criteria of the firms chosen with the individual weights of the individual intrinsic factors.

Firm	Weights	Normalized weights
HSBC	0.17	0.323071076
BOQ	0.171125	0.325209046
Westpac	0.185075	0.351719878
	0.5262	1

 

From the analysis done on the intrinsic values, it is evident that Westpac bank is performing better than BOQ and HSBC. BOQ bank is performing better than HSBC

 

INVESTORS OBJECTIVES

The last analysis that will be conducted is on the investors objectives. The four factors that will be investigated under investors’ objectives include profit, control, Security and excitement.

LIST OF INVESTORS OBJECTIVES FACTORS

INVESTORS OBJECTIVES
Profit	HSBC	BOQ	Westpac
HSBC	0.3	0.5	0.75	0.516667
BOQ	0.4	0.66	0.54	0.533333
Westpac	0.55	0.46	0.67	0.56
Control	HSBC	BOQ	WestPac
HSBC	0.6	0.7	0.5	0.6
BOQ	0.69	0.65	0.4	0.58
WestPac	0.51	0.54	0.9	0.65
Security	HSBC	BOQ	WestPac
HSBC	0.8	0.75	0.78	0.776667
BOQ	0.3	0.5	0.6	0.466667
WestPac	0.4	0.44	0.76	0.533333
Excitement	HSBC	BOQ	WestPac
HSBC	0.76	0.78	0.67	0.736667
BOQ	0.56	0.45	0.69	0.566667
WestPac	0.56	0.44	0.54	0.513333

 

	INVESTORS OBJECTIVES
Firms	Profit	Control	Security	Excitement	Weighted
Profit	0.67	0.45	0.87	0.66	0.6625
Control	0.5	0.7	0.77	0.71	0.67
Security	0.8	0.5	0.7	0.4	0.6
Excitement	0.87	0.56	0.6	0.78	0.7025
	INVESTORS OBJECTIVES FACTORS STANDARDIZED
	Weighted	Normalised weights
Profit	0.6625	0.251423
Control	0.67	0.254269
Security	0.6	0.227704
Excitement	0.7025	0.266603
	2.635	1

 

 

Overall Prioritised List of Firms

In order to calculate the overall prioritized list of the banks listed, multiplication was done for the individual weights criteria of the firms chosen with the individual weights of the individual intrinsic factors.

INVESTORS OBJECTIVES
	0.25	0.25	0.23	0.27
Firm	Profit	Control	Security	Excitement
HSBC	0.516667	0.6	0.776667	0.736667
BOQ	0.533333	0.58	0.466667	0.566667
Westpac	0.56	0.65	0.533333	0.513333
Firm	Profit	Control	Security	Excitement
HSBC	0.129167	0.15	0.178633	0.1989	0.164175
BOQ	0.133333	0.145	0.107333	0.153	0.134667
Westpac	0.14	0.1625	0.122667	0.1386	0.140942
	Firm	Weighted	Normalized weights
	HSBC	0.164175	0.373309
	BOQ	0.134667	0.306211
	Westpac	0.140942	0.32048
		0.439783

 

From the investors objectives factors considered, it is evident that HSBC is performing better compared to BOQ and Westpac.

FINAL WEIGHTS OF THE FIRM

In order to calculate the portfolio, it is important to use each criteria used which is the extrinsic factors, intrinsic factors and investors objectives factors.

 

Limitations of AHP and the need to represent investment criteria using ANP framework and fuzzy logic

There are various limitations that are involved when using the AHP method. The first one is that there are several assumptions that for instance consistency. This means that repeating the evaluation process for the intrinsic values and investors objectives is cumbersome and tiring. The second limitation is that the AHP process becomes hard to evaluate if the number used is higher than 7 (Kabir and Ahsan, 2011).   In addition to that, since the criteria is fixed, then it is hard to add a new one. The last limitation is that it is hard to subtract any criteria used as both the best and worst alternative might be different (Kabir and Ahsan, 2011).

In order to combat the disadvantages associated with the AHP framework, it is important to work with other investment criteria. In using the ANP framework and Fuzzy logic, one of the main advantage of using this process is that this process can use two types of uncertainties which will assist in avoiding vagueness and indiscernibility (Kabir and Ahsan, 2011). In addition to that, the fuzzy logic method assists in expanding the approximations in the environment.

CONCLUSION

In conclusion, it is evident that the AHP is suitable for using in investment portfolio analysis. This is because it assists the investor in understanding which is the best alternative to use when it comes to stock investment. From the analysis done, the extrinsic factors, intrinsic factors and investors objectives were considered in the analysis of the banking portfolio. The firms analysed include the HSBC bank, BOQ and Westpac. On the weighted framework, it is evident that HSBC is the most considered investment option.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

REFERENCES

Gavalec, M. Ramík, J. & Zimmermann, K. (2015). Decision Making and Optimization. Vol. 677 of Lecture Notes in Economics and Mathematical Systems, Springer.

Kabir G. & Ahsan M. A. H. (2011). Comparative analysis of AHP and fuzzy AHP models for multi-criteria inventory classification. International Journal of Fuzzy Logic Systems, vol. 1, no. 1, pp. 1–16.