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esting the Modiglianni & Miller against green business data The essay title for your course work assignment is: using UK green business data to test Modiglianni and Miller’s (M&M’s) debt irrelevance hypotheses. The balance between borrowing and other sources of finance is a long running debate in finance (see lecture notes, text books etc). My personal view is that borrowings are a bad idea for a growing business, but theoretical discussion of the topic (M&M) has concluded that borrowings make no difference, and can even be beneficial if they reduce taxation. I want you to collected data from twenty UK green business companies (broadly defined) and test the impact of borrowings on share prices. You will find a list of suitable companies in my document ‘Window on green business research’. You must select any twenty but be aware that some companies are smaller and less well established than others. Chose your companies to maximise the reliability and relevance of conclusions. I want you to access, through the MMU library, the financial analysis made easy (FAME) database and down load the profit and loss account and balance sheet for 2010, 2009, 2008 (go back to 2007 if 2010 data is unavailable). From yahoo finance I want you to down load the monthly share prices of the same three years. Many companies have similar sounding names, so take great care to ensure that you download the right company’s data. You can access the company’s website to double check that you have the right data. At this stage it is worth making a note of the company’s year end as this will be useful when calculating the share price percentage data. I will be checking that you have handled all this data correctly and, in order to do this, I want you to set out the data in a single spreadsheet. Each company’s FAME data should be in a single work sheet, and therefore you will have twenty worksheets within a single spreadsheet file. To ensure consistency place the Profit and loss account in row 1 and balance sheet in row 75. Make sure that every company’s results are fully downloaded and that consistent cell references are imposed e.g. every companies sales figure for 2010 should be in cell b7, 2009 sales will be in c7 etc. Have a look in my green business data 12.xls spreadsheet and you will see what I mean Put all the share price data in another worksheet, one column for each company using the same order as the FAME downloads. Put all your results in a results work sheet. In total your spreadsheet should contain 22 worksheets. Make sure the worksheets are all named clearly so I can find them and check them.
To get an estimate of company size, one approach that I have used in the past is calculating an index of size by first calculate sales * 1% and then calculate profit before taxation * 10% and then calculate Shareholder funds * 5%. The average of the three figures gives you a summary statistic which robustly measures the size of the company. If this size measure takes a negative value double check the calculations. Again use formula here, do not input the data manually and once the formula is established in the first company, copy into the second company, and so on. Calculate a size index as follows: Put this data in row 200. In addition, to give a feel for the relative size of the companies involved, using the 2010 data, put the companies in size order, biggest company first, smallest company last. The ranking should be in the results worksheet.
Gearing ratio can be calculated as: (Loans divided by shareholders funds)*100 = Gearing ratio
Set out the gearing ratio calculation for every company as follows: Make sure you pick up the right borrowings figure. Last year many students were confused about ‘provisions’ and ‘creditor due in more than one year’. You may need to look in the company’s full report and accounts to identify the correct borrowings figure. Make sure you reference these sources if you have used them and explain any decisions you have made.
Repeat the process using both long term and short term borrowings I will leave it up to you to decide which gearing ratio to work with. Transfer all your gearing ratio data into the results worksheet using formula
In a separate worksheet download monthly share price data for 2007, 2008, 2009, 2010 if it is available. Check that you have 48 observations per company. If the companies you have chosen have a year end of December (not all of them will), the share price percentage can be calculated as shown below: However, if the year end date is not December, say for example March year end, the percentage should be calculated as follows:
2008 2009 2010 In the case of 2008 the March 2008 share price will be compared to the April 2007 share price. You may need to download more data to make sure you have all the share price data you need. Use a formula, and do not calculate the percentage manually. Again using formula, transfer all your share price changes data into the results work sheet. You will now be in a position to bring together all the evidence you have collected. This is what I want you to do next:
1. Produce a table of the final results showing the gearing ratio in a given company and year and the share price movement in that year. Make sure you match up the gearing ratio of the company and year with the right share price change. A suggested structure for the essay is as follows: introduction; short literature review of M&M; size ranking results; check digit results; limitations of the data available; summary table of gearing results; summary table of share price results; graphical presentation; correlation results; discussion of results; conclusions. In addition to the essay I want you to email your spreadsheet to me so that I can check your figures and link them to the results in your essay. M&M theories have played a major role in finance and I am looking forward to seeing if this type of evidence can determine the validity or other wise of the theory. My instinct is that the theory is wrong, but what does the evidence show? The marking scheme will identify the following points
o Setting out downloaded data from FAME in your spreadsheet#p#分页标题#e# Do not write more than 3,000 words. The deadline for submission is Thursday 19th January 2012.
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