The Energy Sector's Value Opportunities
At Euclidean, we do not focus on the energy sector, but instead devote our attention to investing in good companies at great prices. There is, however, a lot of attention being paid to energy companies whose shares have plummeted along with the rapid fall in commodity prices. Because of this interest, last year we did an analysis that looked at whether buying the most discounted energy companies at other times in the past might have been good investment strategy. You can see that post here.
The takeaway was that, across long-periods, it appears that it would have been fruitful to own energy companies comprising the least expensive decile, as ranked by any one of these four simple value factors.
Given the continued declines in energy-related stocks, we decided to look at how today's energy companies measure up. The table below shows the constituents of the energy sector's cheapest decile as ranked by earnings yield. Earnings yield measures the inexpensiveness of a company by dividing its past 12-months earnings before interest and tax, to its current enterprise value (enterprise value = market value + debt – cash). A good way to think about this measure is that a company with twice the earnings yield as another is half as expensive.
If you are interested to see the rest of the domestic energy sector and how each constituent measures up against each value factor, please continue on to the tables below.
Historical simulated results presented herein are for illustrative purposes only and are not based on actual performance results. Historical simulated results are not indicative of future performance.
Throughout, earnings yield is equal to trailing twelve month operating income (EBIT) divided by total enterprise value, price to book is equal to the price per share divided by the most recent quarter's book value per share, price to earnings is equal to the price per share divided by trailing twelve month earnings per share, and price to sales is equal to the price per share divided by the trailing twelve month revenue per share. All calculations in the ranking tables are effective as of market close on February 2nd, 2016.
In the simulations, Standard & Poor’s COMPUSTAT database was used as a source for all information about companies and securities for the entire simulated time period. The S&P 500 return is the total return of the S&P 500, which refers to the Standard & Poor's 500 Index with dividends reinvested. Simulated returns also include the reinvestment of all income. In each simulation, NYSE, AMEX, and NASDAQ companies that have a GICS sector code of 10 (Energy) were ranked according the stated criteria such as earnings yield.
In the simulations, non-US-based companies, trusts, and companies with a market capitalization that, when adjusted by the S&P500 Index Price to January 2010, was less than $400M were excluded.
For the tables that show the rankings of the current cheapest energy companies, non-US-based companies, trusts, and companies with a market capitalization less than $500M on February 2nd, 2016 were excluded.
The simulation results reflect assets-under-management (AUM) at the start of each month that, when adjusted by the S&P500 Index Price to January 2010, is equal to $10M. Portfolios were constructed by investing equal amounts of capital in the top decile of companies represented by each value factor and then rebalancing monthly to equally weight the evolving constituents of the top decile. The amount of shares of a security bought or sold in a month was limited to no more than 10% of the monthly volume for a security. During the period 1983 to present, the purchase and sale price of a security was based on volume weighted daily closing price of the security during the first ten trading days of each month. Prior to 1983, when daily pricing is not available for all securities, the purchase and sale price of a security was based on the monthly closing price of the security.
Transaction costs are factored as $0.02 per share plus an additional slippage factor that increases as a square of the simulation’s volume participation in a security. Specifically, if participating at the maximum 10% of monthly volume, the simulation buys at 1% more than the average market price or, conversely, sells at 1% less than the average market price. Other than these transaction costs, the simulated results do not reflect the deduction of any management fees or expenses.