Research Paper: Testing Bender and Ward Model on UK green companies
Introduction
In their book, Corporate Financial Strategy, Bender and Ward proposed a new financial theory where they postulated that the gearing ratio of the company affects its market value, which is indicated in the stock prices throughout the life cycle. Accordingly, it is very important for the company to use defined funding source at each stage of life cycle to balance the financial and business risk. In the book, the authors had also described each stage of company’s product life cycle, effect of financial elements such as debt, dividend, profit, PE and risk throughout the stages of the life cycle and how the entity should raise finance through each life cycle to balance the business and financial risk.
The financial concept proposed by the authors brought in massive criticism from the financial community, primarily because it challenged the widely accepted MM Theory (Modiglani-Miller Theory) where the eminent finance professors proposed that level and the type of financing makes no difference on the market value of the company because as the company increases its debt proportion, the cost of equity tend to rise as shareholder bear higher risk of financial risk in the company. Thus, it is of no use for a company to decide what proportion of debt and equity is used by the company as once.
Accordingly, in this paper, we will test the validity of Bender and Ward model against UK green companies by analyzing the effect of borrowing on the share prices of the company through examination of financial parameters such as, Earnings per Share(EPS), Current Ratio and Gearing Ratio using the following equation:
Research Methodology
For conducting the research, we aimed to select 10 UK green companies listed on London Stock Exchange or Alternative Investment Market. However, in order to bring comprehensiveness in our approach of selecting the companies, we selected near 15 companies, and then evaluated them on the basis of following checklist:
Genuine green companies such as one involved in the business of wind power, solar power, organic food, sustainable agriculture, healthy lifestyle, recycling et cetera. We did not considered oil or construction companies that try to project an image of green credentials.
Companies that have passed their launch stage and have showed growth in their sales and profit figures.
Companies with positive shareholder funds.
Companies that are listed on LSE or Alternative markets, so that all the financial statements that we need to conduct the research work, should be available.
Finally, after employing the checklist on the list of companies short-listed by us, the following 10 companies were selected as they passed all the selection parameters:
Accsys Technology plc (AIM code, AXS.L)
Active Energy Group plc (AIM code, AEG.L)
Ceres Power Holdings plc (AIM code, CWR.L)
Eleco (AIM code, ELCO.L)
Helius Energy plc (AIM code, HEGY.L)
PV Crystalox Solar (LSE code, PVCS)
Alkane Energy PLC ( LSE Code, ALK.L)
Renewable Energy Holdings (LSE code, REH)
TEG group plc (AIM code, TEG.L)
Wynnstay plc (AIM code, WYN.L)
All the financial data related to the above companies. i.e, their balance sheet, profit and loss statements were downloaded for the period of 5 years (2008-2012) from FAME database. The stock prices and EPS were sourced from the credible source of Yahoo Finance. Subsequently, the data was out under the microscope of our research work and was used for calculation of various set parameters that we had designed for this research work.
Size Index: Ranking
Size index for each of the selected company was calculated as the average size for the five years, i.e. from 2008-2012. Size index for each year was calculated using the following formula:
Size Index= (Turnover*0.01+ Profit before taxation*0.01+ Shareholder funds*0.05)/ 3
Further, on completing the size index calculations, we ranked each of the above stated companies in ascending order. Below is the table illustrating the size index of each company, followed by their alignment according to size index rank:
List of companies arranged according to size index:
Green Business Share Price, FTSE 100 Index and Oil Price
Next, we calculated the average monthly stock prices of the green companies using the average function(AVERAGE) in excel, while the line graph was built using the same average monthly share price data of green business companies. Referring to the graph below we can see that during 2008-2009, share prices plummeted significantly and the same can be attributed to the financial crisis during the same period. Post that period, i.e from 2010-2012, stock prices were seen to be having a steady walk. However, the explanation and understanding of the average price for the whole time period, i.e. from 2008-2012, could be provided through the correlation coefficient between stock prices, FTSE 100 Index, and oil prices.
Hence, in order to understand the trend in the factors that could impact the share price of the companies, we introduced graph for oil price and FTSE 100 index. Important to note, the graph for oil prices was made from the data of oil prices during 2008-2012, which we sourced from Federal Reserve Economic Database. Similarly, graph for FTSE 100 Index was made from the prices of the index during 2008-2012 that we sourced from Yahoo Finance. As we can closely see that except for the financial crisis of 2008-2009, when the oil prices, FTSE 100 index and the stock prices were declining(which was very obvious at the time of recessionary grip in the world economy), the movement in the stock prices thereafter was just opposite to what we witnessed in the trend line of oil prices and FTSE 100 index prices. In other words, while the oil prices were increasing, stock prices of green business companies was on declining trend and this contradicts the logical situation that an increase in the oil prices should lead to surge in the stock prices of green business companies as during that time, consumers look for cheaper energy alternatives. The correlation coefficient between each of the variables is also calculated in the excel spreadsheet, while the result summary is disclosed hereunder:
Share price growth, Current Ratio, Gearing and Total EPS
The above table represents all the parameters that we required for testing the model such as share price growth, average current ratio, average gearing ratio and Total EPS. All the calculations are available in the last sheet of the excel work.
The calculations for share price growth were conducted by taking out the average share price for each stock during 2008 and 2012, while the difference between them was marked as growth in the stock price. Interestingly, as we may notice from the data above, all the companies except for Wynnstay PLC and Alkane PLC have experienced negative growth in the share price during the period of our analysis.
As for current ratio and gearing ratio, the multiples were calculated using the following formula:
Current Ratio= Current Assets/ Current Liabilities
Gearing Ratio: Long term borrowings/ Shareholder funds
For the current ratio, we found that on an average each of the company was having strong liquidity with current ratio multiple above the threshold limit of 2:1. However, the most important parameter for this study is the average gearing ratio. While many of the company produced gearing ratio of 0, this we attribute to lack of data related to long-term borrowings of these companies in the FAME library. However, majority of the remaining companies are having gearing ratio of less than 30% indicating that green companies generally rely on owner funds, and do not use debt borrowing aggressively.
As for EPS, the same was sourced from the income statement of each company, and we then summarized the multiple for each year to come up with Total EPS multiple.
Regression results and analysis
The table below represents the results of multiple regression that we conducted for the dependent variable(share price increase) and the independent variables, i.e. Average Current Ratio, Average Gearing Ratio and Total EPS. The multiple regression was conducted using the excel function available in the Analyst Tool Pack
The results are explained as follows:
Share price increase= a + b(Total EPS)+ c(average current ratio)+ d(average gearing ratio)
= -26.78+ 4.406(0.85) -9.33(3.72)+ 49.28(0.10)
The R-square of the model is 17.28%, showing that this much percentage of the calculated coefficients of the model explains the dependence and change of sharpe prices from the independent variables. Important to note, R-square defines the strength and quality of the model. Hence, higher is the R-square multiple, stronger is the model output. Therefore, figure of 15.82% indicates that the model is very weak and its accuracy is questionable.
The determination of the force of impact of each independent variable on the share price is ascertained using the T-statistic and standard error. As a general rule, any variable with the t-statistic of 2.0 signified that it is statistically significant. Hence, as per the above regression result, none of the variable seems to have significant impact on the share price increase. Looking at the most important variable of the study, i.e. average gearing ratio, the variable have lowest t-statistic of 0.141, which indicates that it has the lowest impact on the share price increase, and shows a positive correlation.
Discussion and Limitation
The testing model has a number of limitations, and this may invalidate the accuracy of the results derived by us. Most of all, the core limitation of the testing model is the use of data for only 10 companies to represent all of the green business companies as smaller is the number of companies, lower is the scope of data which decreases the possibility of revealing the significant interactions between variables of the model.
Another limitation of the model is the pre-selection process where we selected each of the 10 companies under the checklist requirements of:
Genuine green companies such as one involved in the business of wind power, solar power, organic food, sustainable agriculture, healthy lifestyle, recycling et cetera. We did not considered oil or construction companies that try to project an image of green credentials.
Companies that have passed their launch stage and have showed growth in their sales and profit figures.
Companies with positive shareholder funds.
Companies that are listed on LSE or Alternative markets, so that all the financial statements that we need to conduct the research work, should be available.
Thus, selecting only those companies that satisfy the above requirements eventually lead to exclusion of some important companies in the green industry from the scope of analysis. Hence, the model could have been more valid if we would have relaxed the checklist requirements and by including the companies that represent ‘real’ green industry.
Finally, the time period of our model, i.e. 2008-2012 was a period of economic crisis that significantly influenced the stock prices of companies and green business companies were part of it. This somewhat distorted correlation analysis between the variables.
Suggestion and Recommendations
Considering the limitations involved in the testing mode, we would like to recommend some suggestions that could improve the outcome of the testing model:
Increasing the sample size: The sample size as we discussed earlier is too small to validate the outcome of the research model. Thus increasing the sample size from 10 to 100 can significantly strengthen the model.
Relaxing checklist requirements: The second recommendation is related to relaxing or at least shortening of the checklist requirements for the selection of the green companies to be included in the mode. As we had already discussed in the limitation section that the small set of conservative requirements forces us to eliminate some important green companies that could significantly change the outcome of the model. Furthermore, small scope of statistical data resulted in model’s inefficiency highlighted by the low influence of the independent variables on the share price. Hence, the checklist can be relaxed to include some small green business companies that are neither listed on London Stock Exchange(LSE) nor Alternative Investment market. However, these companies do arrange borrowing from banks and other financial institutions. Hence, their inclusion into the sample size can make significant contribution to the research work.
Adding new variables: In this research we compared the stock price to only two variables, i.e. FTSE 100 and Oil prices. However, there are other variables such as technological advances, political regulations, economic factors, et cetera that also influence stock price. Thus, these variables should also be included in the model.
Conclusion
The paper was framed with the objective of testing the Bander and West model by determining the effect of borrowings on the share price. However, with multiple calculations and regression output, we have found that there is no strong evidence to support the view of the authors as there was least influence of the gearing ratio on the share price of the company.
However, we do understand that the sample size of 10 companies is really small to question the validity of the author’s view. Moreover, adopting analysis period that includes financial recession from 2008-2009 was also another primary limitation of our testing model. Therefore, we have also include some recommendation to improve the outcome of the testing model by increasing the sample size, adding real green business companies by relaxing checklist requirement, et cetera.
