Ten Valuation Levels

I determined the effect of finer distinctions of P/E10 levels.

I determined how they affect single-year and two-year data.

Ten Segments

I ordered the 1921-1980 data in accordance with P/E10. I broke them into ten equal segments. I looked at single-year groupings and two-year groupings, both starting with January 1921.

With single-year groupings, I assigned the January value of P/E10 to the subsequent eleven months. Then I assigned the next year's January P/E10 value to the next eleven month and so forth for all of the sequences starting in 1921-1980.

With two-year groupings, I assigned the January P/E10 value to the subsequent 23 months. Then I assigned the P/E10 level of the following month (January, two years later) to the next 23 months and so forth. I did this for two-year sequence beginning with January in all of the odd years from 1921-1979.

Data Collection

I collected an extensive amount of data using the Forsey-Sortino model. It comes with the book, Managing Downside Risk in Financial Markets, by Frank Sortino and Stephen Satchell. Their methods are light-years ahead of traditional Mean-Variance Optimization.

I determined the mean, mean plus and minus one standard deviation, probability of exceeding the Minimum Acceptable Return (MAR) for levels of 0% and 2% (approximately), below target deviation, upside potential and upside ratio for all individual segments.

I have placed these data into my Yahoo Briefcase under the folder for Current Research E and the file 1921-1980 1-yr 2-yr Graphs D4.

Yahoo Briefcase

Results

I plotted Means and the Probability>MAR for a Minimum Acceptable Return (MAR) of approximately 0% versus the percentage earnings yield 100E10/P of each segment. I plotted straight-line graphs using Excel.

Means

Here are the results for the Means versus Percentage Earnings Yield 100E10/P using single-year segments. I have named the segments 1CJan1 to 1CJan10.

y = 2.9436x - 13.57 plus and minus 10%.
R-squared = 0.6446.
When x = 4% (P/E10 = 25), y = -1.80%.
When x = 10% (P/E10 = 10), y = 15.87%.

Here are the results for the Means versus Percentage Earnings Yield 100E10/P using two-year segments. I have named the segments 2BJanL1 to 2BJanL10.

y = 2.7924x - 12.552 plus and minus 10%.
R-squared = 0.6545.
When x = 4% (P/E10 = 25), y = -1.38%.
When x = 10% (P/E10 = 10), y = 15.37%.

In these formulas, x = the percentage earnings yield (100E10/P) and y = the Mean.

Probability of Exceeding the MAR

I set the Minimum Acceptable Return (MAR) approximately equal to 0%.

There was no unusual behavior with the single-year data. The probability of exceeding the MAR increased (roughly) linearly as the percentage earnings yield 100E10/P increased (and prices decreased).

There was a saturation effect with the two-year data. The probability of exceeding the MAR increased (roughly) linearly as the percentage earnings yield 100E10/P increased until the earnings yield reached 8% (and P/E10 = 12.5). From that point on, the probability of exceeding the MAR was level, randomly scattered between 80% and 90%.

I have also collected data with Minimum Acceptable Returns (MAR) of approximately 2%. They are similar to using 0%.

Conclusions

We can use either single-year data or two-year data when using Means. Both produce similar results.

We must distinguish between single-year data and two-year data when examining the probability of exceeding a Minimum Acceptable Return (MAR).

We saw a distinction between single-year results and two-year results previous using three valuation levels. The middle level means were affected.

Have fun.

John Walter Russell
December 16, 2005