I wrote the following for the 2012 Baltimore Business Review. When it is publicly available on the web, I will highlight it. For now, I will offer you the unedited version of my paper that will be published there:
Returns on Equity amid the Financial Crisis
From 2005-2010, the change in public company returns on book equity [ROE] was wrenching during the financial crisis. The results were uneven by sectors, and even by geography, for stocks traded in US equity markets. This paper looks at the differences, and attempts to explain why there was so much variation by sector and geography. After that, the paper attempts to explain the correlation between changes in ROE and stock returns, by year, sector, and geography.
Since 2005, equity markets have seen a boom, a bust, and a tepid recovery. Financial stocks seem to have had the worst of it, but is that really true?
This paper attempts to disaggregate the differing effects of geography (countries/US states), and economic sector over time to try to understand how the boom, bust and recovery have affected public companies.
Part 1 – Return on Equity
This study excluded stocks with market capitalizations under $100 million at the end of the study period. It also excluded miscellaneous financial companies such as exchange-traded products, closed-end funds, and special-purpose acquisition companies, because they don’t have operating businesses. That left 3,796 companies that trade on US exchanges available for the analysis.
Given the tendency for businesses in states and countries to be concentrated in one or two sectors, a minimum was imposed for states and countries to be analyzed individually. Countries with fewer than four companies trading on US exchanges were placed in the “other” country category, and states with fewer than four companies trading on US exchanges were placed in the “other” state category.
Over the years 2005-2010, data regarding book equity, net income, market capitalization, market price, share count, and total returns were gathered, and aggregated by geography (Country if non-US, state if US), sector, and year.
Using Ordinary Least Squares Regression, the following relationship was estimated:
- is the set of dummy variables for geography.
- is the set of dummy variables for sectors.
- is the set of dummy variables for the years 2005-2010.
- is the contribution to return on equity due to geography.
- is the contribution to return on equity due to sector.
- is the contribution to return on equity due to year.
- is the net income for a given geographic area, sector, and year.
- is the book equity for a given geographic area, sector, at the prior year end.
- is the error term for a given geographic area, sector, and year.
The reasons for using this sort of equation is twofold: first, by using dollar figures rather than earnings per share and book value per share, large companies are given their proper weight versus smaller companies. Second, it allows for the effects of ROE changes by geography, sector and year to be separated.
In an analysis where there are multiple groups of dummy variables, at most one set of dummy variables can be complete if there is no intercept term, and no set can be complete if there is an intercept term. If not, the regression will fail. The choice of what to omit is arbitrary, and does not affect the relative relationships within a set of dummy variables. For the purposes of this paper the sector dummy variables were left complete, and the coefficients on the first geographic area (Argentina) and the first year (2005) were set to zero.
The R-squared of the regression was 55.7%, which has a prob-value of greater than 99.9%.
Here are the results of contribution to ROE by country:
The United States is included for comparison purposes as the weighted average of the contribution to ROE by states. There was not a separate variable for the US in the analysis.
As Latin America moved toward freer markets, with growing middle classes, their contributions to ROE were relatively high. In general, resource rich nations tended to have higher contributions to ROE.
Mexico’s contribution to ROE was led by communication companies Telmex, America Movil, and Grupo Televisa and consumer-oriented companies like Coca-cola Femsa, FEMSA, and Wal-Mart de Mexico. A growing middle class pushed up demand for these companies.
Chile’s contribution to ROE was led by the utilities Enersis and Empresa Nacional de Electricidad, the banks Banco Santander Chile and Banco de Chile, and chemical company Sociedad Quimica y Minera de Chile. A growing economy boosted demand for electrical power, their banks didn’t make the mistakes made by most of the rest of the developed world, and Sociedad Quimica y Minera was in the “sweet spot” for the chemicals it produced, particularly fertilizers, and lithium which goes into rechargeable batteries.
Brazil’s contribution to ROE was led by the energy giant Petrobras, the diversified mining company Vale, and the banks Banco Santander (Brasil), Itau Unibanco Holding, and Banco Bradesco. Global demand for crude oil, iron ore, and other resources boosted the contributions to ROE with Petrobras and Vale. Brazil’s banks also didn’t make the mistakes made by most of the rest of the developed world.
On the negative side, contributions to ROE in Finland were held down by Nokia, where they fell behind consumer trends with cell phones and other portable wireless devices. Ireland was held back by banking sector, which lent too much on Irish residential property, amid other errors. Luxembourg had ArcelorMittal, which slumped with the global steel industry as prices for coking coal and iron ore rose. South Africa had the worst contribution to ROE as a country because of the heavy weight their economy has in basic materials. Basic materials was a strong sector, but South Africa was concentrated in one the weakest ROE industries in that sector, gold mining.
Here are the results of contribution to ROE by US state:
|District of Columbia|