Each year, as with the market portfolio, all the portfolios we tested were formed on 16 June. We chose 16 June as most European companies have a December year-end and by this date all their previous year-end results would be available in the database. The annual returns for our back test portfolios were calculated as the 12-month price change plus dividends received over the period. Returns were compounded on an annual basis. This means each year the return of the portfolio (dividends included) would be reinvested (equally weighted) in the strategy the following year. The portfolios were all constructed on an equal-weighted basis.
In order to test the effectiveness of a strategy, we divided our back test universe into five equal groups (quintiles), according to the factor we were testing. For example, when testing a low price-to-book (PB) value strategy, we ranked our back test universe from the cheapest (lowest PB) to the most expensive (highest PB) stocks.
The cheapest 20% of companies were put in the first quintile (Q1), the next in the second, and so on, with the 20 % of companies with the highest price-to-book value in the fifth quintile (Q5).
We defined a good factor or strategy as one where:
So, in summary, we are looking for factors that increase the probability of positive returns, beat the market, and how strong or weak this probability is.
In order to determine if the size of the company has any effect on the effectiveness of a one factor test, we divided the back test universe into three groups based on of market capitalization:
Compared with US studies, our Small Cap group can also be classified as Nano capitalization companies, and our Mid Cap group equivalent to US small capitalization companies.