Organisations as organisms Many of us find finance difficult to learn. We often don’t have firsthand knowledge of financial operations of organisations. We often don’t have intuition about financial concepts. But we are very familiar with our daily lives. Just think organisations as organisms. Finance and many other subjects will be much easier to connect. You might protest. Organisations are not organisms. Organisms will grow, mature, decline and die. Organisations, if well managed, can last forever. However, if you look at statistics, most companies also grow, mature, decline and die. One way to measure the health of a company is its credit rating. An individual company’s credit rating can improve over time, just like an individual’s health condition can improve over time, even when one is old. However, statistically, the average credit rating of a cohort of companies will decline over time, as these companies age. We will leave the detailed discussion on statistics to the appendix. Once we treat organisations as organisms, many problems in finance become very easy to understand. One problem is the mode of financing. There are two main methods of financing: equity financing and debt financing. We also need to decide whether we shall retain earning or distribute earning as dividend. These questions are unfamiliar to most of us. We find them difficult to understand. But we can learn a lot from the financing methods of our own lives, which are more familiar to us. When we are small children, are we financed by parents or by bank loans? When you are five years old, your parents are entitled to think you as a future billionaire. But a bank won’t be persuaded to loan you a million dollar because of your future prospect. You have to be finance by your parents’ money, or equity. You can’t be finance by loans from a bank, or debt. As you grow older and have a steady income yourselves, you can get mortgage for your home purchase. You can get debt financing. When you have a family and settle down, you have kids and distribute your earning to your next generation or other people. You distribute your incomes as dividends. This is the financing life cycle for individual persons. From the evolution of financing methods at different ages, you can understand corporate financing much easier. When a company is young, it requires heavy investment and has little earning. Few banks are willing to lend it money. It has to rely on owners’ equity financing. As a company starts to generate earning, banks and capital markets will be confident enough to loan it funds for further expansion. This is debt financing. As a company matures and generate steady streams of earning, it will distribute its earnings as dividends to fund growth opportunities elsewhere or other needs. This is the financing life cycle for individual companies. It is very similar to the financing life cycle for individual persons. Finance literature piles up many papers to explain why and how companies choose different modes of financing. Personally, I find the explanation of financing life cycle most illuminating. Once we think organisations as organisms, finance and other subjects will be less remote. They will be easier to understand. Appendix: Transition probability matrix of debt ratings Each year, rating companies, such and Standard & Poor and Moody’s, will summarize the changes of credit rating of companies into a table. This table is called transition probability matrix. A typical transition probability matrix, taken from Standard & Poor, looks like this.
| AAA | AA | A | BBB | BB | B | CCC | Default | AAA | 0.908 | 0.083 | 0.007 | 0.001 | 0.001 | 0.000 | 0.000 | 0.000 | AA | 0.001 | 0.912 | 0.079 | 0.006 | 0.001 | 0.001 | 0.000 | 0.000 | A | 0.009 | 0.024 | 0.900 | 0.054 | 0.007 | 0.003 | 0.001 | 0.001 | BBB | 0.000 | 0.003 | 0.059 | 0.869 | 0.053 | 0.012 | 0.001 | 0.002 | BB | 0.000 | 0.001 | 0.007 | 0.077 | 0.805 | 0.088 | 0.010 | 0.012 | B | 0.000 | 0.001 | 0.002 | 0.005 | 0.065 | 0.827 | 0.041 | 0.059 | CCC | 0.002 | 0.000 | 0.002 | 0.013 | 0.023 | 0.129 | 0.606 | 0.225 | Default | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 1.000 |
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| sum of column | 0.920 | 1.024 | 1.057 | 1.025 | 0.955 | 1.060 | 0.659 | 1.300 |
The above table requires some explanation. In general, a company’s credit rating can be from AAA to default. AAA is the highest credit rating, then AA, A, BBB, BB, B, CCC. Default is the lowest rating when a company defaults on its debt payment. This table is called the transition probability matrix. It has eight rows and eight columns. The number at first row, first column is 0.908. On average, there is a 0.908 probability that a AAA bond will remain AAA the next year. The number at first row, second column is 0.083. On average, there is a 0.083 probability that a AAA bond will become a AA bond the next year, one slippage in credit rating. The number at second row, first column is 0.001. On average, there is a 0.001 probability that a AA bond will become a AAA bond the next year, an enhancement in credit rating. The sum of all numbers in each row is one, since the probabilities sum up to one. We want to extract information about the long term health of companies from the transition probability matrix. First, we look at transition probabilities between AAA and AA bonds. Every year, there is a 0.083, or 8.3% probability a AAA bond is downgraded to AA bond. Every year, there is a 0.001, or 0.1% probability a AA bond is upgraded to AAA bond. From these data, it seems that there is a trend of declining health of companies every year. Then we look at transition probabilities between BBB and BB bonds. Every year, there is a 0.053, or 5.3% probability a BBB bond is downgraded to BB bond. Every year, there is a 0.077, or 7.7% probability a BB bond is upgraded to BBB bond. From these data, it seems that there is a trend of slightly improving health of companies every year. From the transition probability matrix, we can’t be certain whether the overall health of companies decline every year. To obtaining clearer picture, we can multiply transition probability matrix multiple times to see the long term results. It is easy to perform matrix multiplication with Excel. We can use the mmulti command. The result of the sixty fourth power of the matrix is
| AAA | AA | A | BBB | BB | B | CCC | Default | AAA | 0.029 | 0.117 | 0.224 | 0.159 | 0.078 | 0.064 | 0.010 | 0.318 | AA | 0.024 | 0.098 | 0.198 | 0.146 | 0.073 | 0.062 | 0.009 | 0.389 | A | 0.022 | 0.085 | 0.174 | 0.130 | 0.066 | 0.056 | 0.009 | 0.458 | BBB | 0.017 | 0.067 | 0.139 | 0.107 | 0.056 | 0.048 | 0.007 | 0.559 | BB | 0.011 | 0.044 | 0.093 | 0.073 | 0.038 | 0.034 | 0.005 | 0.702 | B | 0.006 | 0.024 | 0.053 | 0.042 | 0.022 | 0.020 | 0.003 | 0.829 | CCC | 0.004 | 0.014 | 0.030 | 0.024 | 0.013 | 0.011 | 0.002 | 0.903 | Default | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 1.000 |
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| sum of column | 0.113 | 0.450 | 0.911 | 0.682 | 0.346 | 0.294 | 0.045 | 5.157 |
From the above table, we can find the values are highly concentrated at the last column, the default column. The last row is the sum of each column. From the iteration results, after sixty four years, the majority of the companies from that cohort will default. Of course, we can’t interpret it too literally. It is possible that some companies, due to poor performance, have been acquired by other companies. Some companies, due to low credit rating, are unable to obtain, or choose not to seek further funding from the debt markets. But the overall deterioration of the health of companies toward default is unmistakable. It is the birth and spinoff of new companies that keep rejuvenate the overall economy. Similarly, the overall deterioration of the health of any cohort of population toward death is unmistakable. It is the birth of new people that keep rejuvenate the overall society. For Excel calculations related to the transition probability matrix, please refer to http://web.unbc.ca/~chenj/course/rating%20migration.xlsx
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