The year that wasÉ and hopefully will not see again for awhile.. Thoughts on 2009
I have mixed feelings about the last quarter of 2008. The damage inflicted on my portfolio was real and the job perils that it has created for friends, students and acquaintances were painful, but it was an experience that has changed much of what I thought to be the truth in corporate finance, valuation and portfolio management. I plan to write about what I learned, unlearned and relearned in those three months sometime this year.
However, as I sat down to do my annual data update (my 16th for US companies and my 7th for global companies), I knew that there would be several challenges that I would face and they all came to pass:
1. Market collapse: The biggest factor that plays into this yearÕs numbers is the collapse of equity market prices globally. This is reflected in two facts. The first is the obvious: the market capitalization for most companies is dramatically lower than it was in last yearÕs update. The second is more subtle. For non-US companies, I had used a lower limit of $50 million US dollars, when screening for firms. Since so many firms dropped below that floor, I had to lower the floor to $ 10 million.
2. Accounting data lags: While the market values are updated to reflect prices as of January 2009, most of the accounting data reflects pre-crisis numbers. In fact, the last annual statements for most companies reflect December 31, 2007 statements. Even the trailing 12-month data, where available, is as of September 30, 2008. The net effect of this is that this year, more than most others, will be affected by the timing mismatch, with numbers that combine market and accounting data (like PE ratios or EV/EBITDA multiples) resulting in values that may not quite jell. In particular, there will be firms that are trading at dramatically low (and even absurdly low) multiples of earnings. While there is not much I can do about this right now, I will try to do a May 2009 update that reflects the numbers for 2008.
3. Risk Premiums: This has been a year that has shaken our faith in mean reversion and using long term averages, especially when it comes to equity risk premiums and default spreads. I have done my annual update for historical equity risk premiums for the United States but 2008 has changed the numbers dramatically. The geometric average risk premium for stocks over treasury bonds, going back to 1928, was 4.79% at the end of last year, has dropped to 3.88%, with premiums over shorter periods (10 years) becoming negative. The implied equity risk premium, which was 4.37% at the end of 2007, jumped to 6.43% at the end of 2009. In the datasets that compute cost of equity and capital, I have abandoned my practice of using historical risk premiums and used a higher value (5%). Even that may be too low a number. I would suggest that you up that number towards the current implied equity risk premium, if you want a cost of equity and capital today.
4. Riskfree Rates: The other phenomenon that will affect some of the numbers, especially the costs of equity and capital is the decline in riskfree rates across developed market currencies, with the US dollar riskfree rate dropping to almost 2%. By itself, this will lower the costs of equity and capital, but the accompanying increase in the risk premiums effectively left the costs of capital relatively unchanged.
5. Betas: Of all the inputs into valuation, this is the one that was affected the least by the crises, simply because it is a relative number.
So, what should you do, if asked to compute a cost of capital or do a valuation today? The one thing you cannot do is to act like nothing has happened and revert back to historic norms. Use the updated data numbers that you see in the datasets but feel free to move numbers towards historic values over the long term. In other words, if asked to value a company today, I would use an equity risk premium of 6% for the next 5 years and then move it down to 4% after the fifth year.
Over the years, some of the datasets have included data that I have wanted to change and I used this year to make the transition.
1. Change in data source: For the last 7 years, I have used Bloomberg as my data source for my non-US data but I faced two key problems. The first is that getting data from Bloomberg (at least for me) was painful, since I was restricted to downloading 500 companies at a time, with a maximum of 20 data items per company. In January 2008, getting the data for the 18000 non-US companies took me almost three days and I was not happy about the fact that I could get only 20 data items at a time. This year, I switched to Capital IQ, which I find deliriously easy to work with. I am able to download far more data on every company which also means that I can start reporting numbers for non-US companies that I have hitherto not tried to (including working capital, debt and dividend breakdowns). There is one cost. The industry breakdowns that Capital IQ uses are different and more aggregated than the Bloomberg industry breakdown. I am sorry if you have been using a specific industry in Bloomberg and cannot find it in the new datasets. Note, though, that you can always find your company in the raw dataset that is at the top of the page to see where Capital IQ has put your company.
2. S&P 500 Earnings and Raw data: One of the perils of trying to update data in the first week of every year is that some of the key numbers have to be estimates. For years, this has been an issue when I estimate the earnings and dividends on all stocks to compute both returns and PE ratios for the market. I have generally used three quarters of real data and S&PÕs estimates of earnings and dividends for the last quarter to make my estimates. However, the actual numbers, which come out in March or April, can be different from my estimates. I decided this year to go back and make my estimates of earnings/dividends for prior years into actual numbers. You will notice small changes in the files that contain the historical returns for stocks and the historical PE ratios for the market.
In summary, I hope that you find this update useful. I learned a lot in the process of updating the data and I will try to keep you abreast of anything else that I do to make the datasets more useful. Happy Hunting!