Timothy Clontz
04-22-2012, 11:23 AM
Condition Bear Market Rally
S&P Target 1240
Small Portfolio IAU & XLF 12.72%
Hedge XLU -1.96%
Position Date Return Days Call
GCI 7/14/2011 4.17% 282 Hold
CSGS 10/3/2011 14.87% 201 Hold
NLY 10/25/2011 4.44% 179 Hold
DD 10/27/2011 16.06% 177 Hold
KBR 10/27/2011 18.35% 177 Hold
VG 10/27/2011 -37.39% 177 Buy
TTM 11/30/2011 79.08% 143 Hold
BT 1/4/2012 12.82% 108 Hold
PDLI 3/7/2012 2.30% 45 Hold
CLF 3/19/2012 -6.57% 33 Hold
S&P Annualized 2.78%
Small Portfolio Annualized 14.25%
Mousetrap Annualized 18.56%
Hedged Annualized 16.36%
I’ve mentioned the problem of periodicity a few times, so today I’ll include a couple of graphs I’m using to track the performance of the model. The first graph is generated from the adjusted prices of all stocks invested into the Mousetrap since 5/31/2011 – continuing PAST the time I sold them. That is, instead of closing the stock, I let the prices run in the graph to find out just when the correct holding period should have been.
13909
I know the numbers aren’t readable. What this translates to is the average annualized return of all stocks from 8 to 325 calendar days. I’ve superimposed a polynomial trend line to estimate the maximum annualized return on investment, minus trading costs and taxes.
Next is a smoothed curve comparing two hypothetical accounts with the S&P. The S&P averages an 8.25% annual return over the course of the past 60 years:
13910
The IRA account is adjusted for trading costs, but not taxes. The “Return Rate” line adjusts for both trading costs and taxes. The bump at the 1 year point reflects the current difference between long and short term capital gains.
Although the first graph indicates we may be near the apex of the return rate at 325 days, I’m hoping that the returns will hold into a full year to take advantage of long term capital gains.
You’ll note that my own returns are not as good as the returns reflected in the graphs. The cause is common to all traders: I traded too frequently.
These are a few steps to any trading system:
1) Determine a way to beat the S&P in backtests
2) Test in real time (where we are now)
3) Fine tune
Fine tuning will adjust some of the parameters to conform to the natural holding period, which has yet to be determined. I suspect from the first graph that we are getting close, and if it is at least a year this will be a successful investment system.
If the ideal holding period turns out to be 400 days, for instance, it would mean that I would trade once every 40 days as I rotate between 10 stocks, or 20 days if I rotate between 20 stocks. The longer the ideal holding period turns out to be, the easier it will be to increase the number of stocks in the portfolio – and the position sizes as well (i.e. the model will be more scalable).
In terms of broad market money flow, the sector model is still mixed, and the hedge in utilities remains in place – even after an annoying week where it popped back up a couple of percentage points as the market faltered.
Finally, these are the DDRL scores I’m using to determine ideal position sizes for a margin account”
DDRL Leverage
All Long 2.91 96%
Closed Long 2.35 68%
All Hedged 1.71 35%
Closed Hedge 1.45 23%
Median 2.03 52%
I will not be reporting margin adjusted returns, but this is the theoretical amount of margin the model can withstand, which appears to be reasonable. Again, the idea is to rotate at regular intervals in order to cancel out short term market gyrations through dollar cost averaging. This is not a timed system, but a rotation system.
Tim
S&P Target 1240
Small Portfolio IAU & XLF 12.72%
Hedge XLU -1.96%
Position Date Return Days Call
GCI 7/14/2011 4.17% 282 Hold
CSGS 10/3/2011 14.87% 201 Hold
NLY 10/25/2011 4.44% 179 Hold
DD 10/27/2011 16.06% 177 Hold
KBR 10/27/2011 18.35% 177 Hold
VG 10/27/2011 -37.39% 177 Buy
TTM 11/30/2011 79.08% 143 Hold
BT 1/4/2012 12.82% 108 Hold
PDLI 3/7/2012 2.30% 45 Hold
CLF 3/19/2012 -6.57% 33 Hold
S&P Annualized 2.78%
Small Portfolio Annualized 14.25%
Mousetrap Annualized 18.56%
Hedged Annualized 16.36%
I’ve mentioned the problem of periodicity a few times, so today I’ll include a couple of graphs I’m using to track the performance of the model. The first graph is generated from the adjusted prices of all stocks invested into the Mousetrap since 5/31/2011 – continuing PAST the time I sold them. That is, instead of closing the stock, I let the prices run in the graph to find out just when the correct holding period should have been.
13909
I know the numbers aren’t readable. What this translates to is the average annualized return of all stocks from 8 to 325 calendar days. I’ve superimposed a polynomial trend line to estimate the maximum annualized return on investment, minus trading costs and taxes.
Next is a smoothed curve comparing two hypothetical accounts with the S&P. The S&P averages an 8.25% annual return over the course of the past 60 years:
13910
The IRA account is adjusted for trading costs, but not taxes. The “Return Rate” line adjusts for both trading costs and taxes. The bump at the 1 year point reflects the current difference between long and short term capital gains.
Although the first graph indicates we may be near the apex of the return rate at 325 days, I’m hoping that the returns will hold into a full year to take advantage of long term capital gains.
You’ll note that my own returns are not as good as the returns reflected in the graphs. The cause is common to all traders: I traded too frequently.
These are a few steps to any trading system:
1) Determine a way to beat the S&P in backtests
2) Test in real time (where we are now)
3) Fine tune
Fine tuning will adjust some of the parameters to conform to the natural holding period, which has yet to be determined. I suspect from the first graph that we are getting close, and if it is at least a year this will be a successful investment system.
If the ideal holding period turns out to be 400 days, for instance, it would mean that I would trade once every 40 days as I rotate between 10 stocks, or 20 days if I rotate between 20 stocks. The longer the ideal holding period turns out to be, the easier it will be to increase the number of stocks in the portfolio – and the position sizes as well (i.e. the model will be more scalable).
In terms of broad market money flow, the sector model is still mixed, and the hedge in utilities remains in place – even after an annoying week where it popped back up a couple of percentage points as the market faltered.
Finally, these are the DDRL scores I’m using to determine ideal position sizes for a margin account”
DDRL Leverage
All Long 2.91 96%
Closed Long 2.35 68%
All Hedged 1.71 35%
Closed Hedge 1.45 23%
Median 2.03 52%
I will not be reporting margin adjusted returns, but this is the theoretical amount of margin the model can withstand, which appears to be reasonable. Again, the idea is to rotate at regular intervals in order to cancel out short term market gyrations through dollar cost averaging. This is not a timed system, but a rotation system.
Tim