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URL:  http://boards.fool.com/annual-hold-strategy-26231522.aspx

Subject:  Annual Hold Strategy Date:  12/29/2007  4:28 AM
Author:  Zeelotes Number:  205662 of 251806

Introduction

I've been debating whether to employ an annual hold strategy for a particular account. This would be based on holding a fixed # of stocks for exactly one year + one day for tax purposes. The difference between what I did this time and what I've done in the past is that I used the same approach as I've done for building blends employing a monthly rebalance, i.e., sort based on various measures to select the screens to use at the end of each year. Here are the two other posts detailing research I've done on longer than monthly rebalances.

Small Port: Quarterly Rebalance
http://boards.fool.com/Message.asp?mid=23744437

Longer Rebalances: Blends
http://boards.fool.com/Message.asp?mid=23787636

I began by running tests on all screens using various start years each holding four stocks -- 1969, 1986, 1987, 1989, 1997 and those in the SIPRO universe starting in 1997. Each year is based on a single start date so this is far from an exhaustive test, but I believe it is sufficient to guide me to the best solution.

I then set up a backtest where all the various measures were tried based on both an ascending and descending sort. I chose three screens from each universe -- three from VL and three from SIPRO -- resulting in a hold of six screens and 24 stocks. Because SIPRO was included I limited the test to 1999 to 11/7/2007.

The S&P 500 as a Benchmark

The advantage of this period for testing is that the market has not done too well over this period so it is a difficult period for any strategy to significantly beat the market. There are certainly very few mutual funds that have market beating returns. The test period includes three years of a major bear market and nearly six years of a bull. During this time the S&P 500 has a return of just under 2% CAGR without dividends. But more importantly, it has a huge Ulcer Index # and a very high maximum daily drawdown. Even the sharpe is negative.
             S&P 500
CAGR %
1.91%
GSD 19.34
Sharpe -0.01
Ulcer Index 22.76%
Drawdown -46.42%

The Best Predictive Measure for Annual Holds

The first thing that is clear is that the best measures for annual holds are not necessarily the ones that were best for monthly rebalances. Downside Deviation pops right to the top when the sort is UI, which for me, is the optimal means of selecting the best measure in this case. In fact, Sharpe and UI pick the same measure as best.
        Based On         Sort   CAGR   GSD   Sharpe  Ulcer Index  Troughs  Sortino  Yrs >= Index  Yrs >= 0  Drawdown
Downside Deviation ASC 22.75% 15.9 1.22 4.08% 3 1.78 100.00% 100.00% -17.13%
Ulcer Index ASC 19.04% 15.9 1.02 4.85% 2 1.47 88.89% 88.89% -21.02%
Sleep Ratio ASC 19.10% 16 1.01 4.93% 3 1.47 88.89% 88.89% -21.02%
Sharpe/(GSD^x) DESC 23.01% 18.4 1.10 4.95% 5 1.63 88.89% 100.00% -18.53%
GSD ASC 17.68% 14.6 1.00 5.30% 3 1.46 88.89% 100.00% -18.20%
Upside Potential ASC 15.79% 13.7 0.93 5.30% 3 1.33 88.89% 88.89% -19.82%
Normalized Trough Count ASC 18.47% 14.9 1.03 5.67% 4 1.49 88.89% 100.00% -18.79%
CAGR/(UPI^x) ASC 19.24% 20.6 0.84 7.22% 5 1.22 88.89% 77.78% -30.09%
Correlation DESC 26.46% 24.3 1.02 7.47% 10 1.53 77.78% 77.78% -25.54%
Treynor DESC 16.85% 18.9 0.78 7.49% 8 1.12 88.89% 100.00% -21.20%
GSD Ratio DESC 24.80% 23.5 0.98 7.84% 10 1.56 100.00% 100.00% -24.95%
Treynor/(GSD^x) DESC 12.36% 17.6 0.58 8.61% 7 0.82 77.78% 88.89% -25.32%
Treynor/(Beta^x) DESC 14.30% 18.9 0.65 9.12% 5 0.93 77.78% 77.78% -26.16%
Upside Potential Ratio ASC 19.07% 21.3 0.82 9.72% 5 1.19 77.78% 77.78% -29.23%
Upside Potential Ratio DESC 17.78% 27.4 0.64 12.26% 11 0.97 77.78% 77.78% -38.59%
Beta ASC 17.99% 23.8 0.71 12.85% 8 1.08 66.67% 66.67% -38.46%
Correlation ASC 12.81% 22 0.53 13.32% 11 0.76 77.78% 77.78% -39.07%
Ulcer Performance Index ASC 23.94% 27.3 0.86 13.45% 9 1.28 88.89% 77.78% -35.39%
Sortino DESC 20.73% 30.4 0.71 14.55% 14 1.04 77.78% 77.78% -49.77%
CAGR/(SF^x) DESC 11.03% 24.7 0.42 16.20% 9 0.62 66.67% 77.78% -43.05%
Sharpe DESC 19.04% 29.3 0.67 16.47% 13 0.99 88.89% 88.89% -49.77%
Sortino ASC 21.90% 28 0.78 16.60% 10 1.15 88.89% 77.78% -39.99%
Sharpe/(GSD^x) ASC 21.73% 27.7 0.78 16.93% 10 1.15 88.89% 77.78% -39.99%
CAGR/(UI^x) DESC 14.52% 26 0.55 17.23% 11 0.80 77.78% 77.78% -43.05%
Upside Potential DESC 18.33% 33.4 0.60 17.29% 15 0.88 66.67% 55.56% -47.57%
Normalized Trough Count DESC 23.49% 34.3 0.74 17.94% 14 1.08 77.78% 66.67% -50.43%
CAGR/(GSD^x) DESC 15.74% 28.7 0.56 18.21% 13 0.83 88.89% 88.89% -49.77%
GSD Ratio ASC 26.22% 34.7 0.81 18.68% 16 1.20 88.89% 77.78% -53.95%
Treynor/(Beta^x) ASC 19.74% 27.4 0.72 18.82% 10 1.04 88.89% 77.78% -42.63%
Jensen ASC 19.48% 26.3 0.73 18.99% 10 1.06 88.89% 77.78% -46.42%
CAGR/(GSD^x) ASC 20.66% 26.8 0.76 19.13% 9 1.12 88.89% 66.67% -44.92%
GSD DESC 14.24% 33.3 0.48 19.20% 12 0.70 66.67% 55.56% -50.15%
Alpha ASC 18.39% 27 0.68 19.23% 11 0.98 88.89% 77.78% -46.42%
Ulcer Performance Index DESC 14.12% 26.6 0.53 19.60% 11 0.77 77.78% 77.78% -43.47%
Sharpe ASC 20.15% 27.8 0.72 20.07% 9 1.07 88.89% 66.67% -47.12%
Calmar ASC 20.44% 28.2 0.73 20.11% 9 1.07 88.89% 66.67% -47.12%
Downside Deviation DESC 18.22% 32.6 0.61 20.60% 14 0.89 77.78% 66.67% -52.41%
Treynor ASC 20.06% 28.9 0.71 21.13% 10 1.04 88.89% 88.89% -48.47%
Treynor/(GSD^x) ASC 17.97% 29.2 0.63 21.18% 14 0.91 77.78% 66.67% -50.03%
Calmar DESC 12.74% 28.5 0.46 21.73% 12 0.69 66.67% 77.78% -56.04%
CAGR/(UI^x) ASC 18.35% 26.5 0.68 22.02% 10 1.01 88.89% 77.78% -46.81%
Jensen DESC 20.64% 33.3 0.67 22.89% 15 1.00 88.89% 88.89% -59.06%
Sleep Ratio DESC 13.36% 31.2 0.47 22.95% 13 0.67 66.67% 66.67% -53.29%
Alpha DESC 20.27% 33 0.66 23.58% 16 0.99 88.89% 88.89% -59.06%
CAGR/(SF^x) ASC 17.89% 27.6 0.65 24.94% 10 0.96 77.78% 55.56% -53.21%
CAGR/(UPI^x) DESC 14.82% 26.7 0.55 28.11% 10 0.79 88.89% 77.78% -56.33%
Ulcer Index DESC 14.06% 33.6 0.47 36.24% 15 0.69 77.78% 66.67% -68.01%
Beta DESC 8.62% 32.9 0.31 39.45% 16 0.44 77.78% 77.78% -68.19%

If the highest CAGR is your goal, according to this test, Correlation is best with a descending sort. What this means is that screens that are most highly correlated with the overall market do better than those that are not correlated. In fact, correlation has one of the biggest spans between the two sorts.

As you can see, no matter what method you employed you'd have beaten the market easily. This is more due to the nature of the screens selection for inclusion in the weekly ranks than in their potential to win in the future IMO. Which is all the more reason why it is important to have a good strategy for screen selection going forward. Choosing a blend of screens for annual holds based on just one snapshot is not advisable in my view. It is better to test it as I've done here -- employing a strategy for screen selection that is used at the end of each year and seeing how it worked out over the full test period.

The only problem with this whole approach is that for measures like Downside Deviation, you have very little turnover in the screens employed over the full history -- just 16% in this case. For this reason alone I'm tempted to select a measure that ranks very high, but has a much higher turnover rate -- Normalized Trough Count and Correlation fill the bill in that case.
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