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Subject:  Re: PEG weighting Date:  8/26/2000  12:20 PM
Author:  gelasmus Number:  78109 of 275634

I am interested in exploring the idea of weighting the PEG5 based on it position in the screen. This would be similar to the foolish 4 in Robert Sheard's book where two of the stocks are 33% and two are 17%. If with backtesting we could discover that for example the PEG stock in position 3 has a better historical performance than the other positions, we could weight that stock heavier in our portfolio. Has this ever been researched?

Interesting idea I fiddled with as well, then dropped. (moral is, share negative results, so other folks don't pursue the same dead-ends!) Here's what I've got:

If you datamine and optimize on CAGR, the weights for each of the top 5 of PEG 13 should be

Position 1: 3%
Position 2: 97%
Position 3-5: 0% (CAGR 84, GSD(M) 56)

Optimizing on Sharpe Ratio instead, you get:

Position 1: 14%
Position 2: 35%
Position 3: 15%
Position 4: 4%
Position 5: 6%
Remainder in cash (CAGR 53, GSD(M) 27).

The preference for position 2 and for the top 3 positions are well established in the screen selections chosen by most folks on the board for blends & switches.

You could try these weightings, I suppose. You also might use them to guide rebalance decisions (ex: let your winners run as long as they are moving up toward position 2, trim them when they hit position 1 or drop back 1 position). I wouldn't.

My basic feeling is that while there maybe some underlying structure here, it's mostly datamined nonsense. Guess I feel that way about Sheard's stuff, too. From the asset allocation thread, we know that proper weighting depends a great deal on correlation, and there seems like no theoretical ground for assuming anything about the correlation between stocks in different screen rank positions, regardless of the accidents of history.

I tried extending to more tests: If you run the same Sharpe optimization on the 10-stock PEG13, you get a similar weighting of positions 1-5, 0% on position 6, but position 7 gets weighted the same as position 1. Huh?

PEG13:10 (optimize on Sharpe)
Pos1:13%, Pos2:33%, Pos3:14%, Pos4:3%, Pos5:5%, Pos6:0%, Pos7:13%, Pos8-10: 0%. (CAGR 53, GSD 27)

I also tried similar analysis on RS13:10.

RS13:10 (optimize on Sharpe)
Pos1:7%, Pos2:16%, Pos3:0%, Pos4:16%, Pos5:15%, Pos6:0%, Pos7:0%, Pos8:7%, Pos9:0%, Pos10:6% (CAGR 39, GSD(M) 25).

RS13:10 (optimize on CAGR)
Pos2: 25%, Pos4:13%, Pos5:62%, all other positions 0%. (CAGR 68, GSD(M) 50)

You can see how weird it gets, and how much it shifts around. That's just random statistical noise. The likely underlying structure may be that the top half does better (ie. overlaps and SOS help), and perhaps the very top stock might have a greater exposure to a correction/fall. Otherwise, it's not useful.

Things like LorenCobb's Exp. Growth and BarryDTO's individual stock efficient frontier models strike me as much more robust and theoretically sound mechanisms for applying asset allocation weighting to individual issues. But it's certainly good to pursue all ideas!


P.S. I think Sparfarkle is working on a money management model to pursue a portfolio of "bullets" like the position 2 stocks above; there might be something to that.

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