The system had a respectable gain this month.
I have added a new metric (rightmost cells) which is the Net Risk Adjusted percentage gain. To calculate this metric, you divide net percentage gain by the exposure. Let’s look at this. The 1% Risk, 10% Stop model had the best risk adjusted performance because it kept more cash on hand (less exposure) than the other models. The 2% Risk, 3ATR model had both poorer net gain and risk adjusted gain. Because that model risks 2% on every trade, it took on more exposure (less cash on hand).
The 2% risk models have averaged about 66% exposure this year. This means that many times you will have 1/3rd of your account in cash, in money markets, whatever.
A note about how the report is generated. The monthly statistics, %P/L (% profit or loss) and %CAR (% compound annual return) are calculated from January 4th (first trading day of 2010) to the present, NOT starting from September 1st to September 30th. The difference is that the system may have been holding open positions going into September that affect that months performance where if one started trading the system on September 1st, there wouldn’t have been any already opened positions.
The rest of the statistics, W/L% , Avg.Trade, and Trades are calculated from September 1st to September 30th in order to give an accurate account of one month’s performance.
I would like to highlight Hawaii FiveO’s comment from Friday where he listed his PDS trades for the month and calculated the percentage gain of his average trade. He has come very close to replicating backtested results (although I believe he may alter an exit every now and again). This is what we want to see for any system- that subscribers can replicate the results in their own accounts.
Year-to-Date Performance As of 9/30/10:
Again, note the exposure levels and Risk Adjusted returns.
Overall, it has been a difficult year, with headfakes left and right. I’m happy to see PDS pulling ahead of the benchmarks.
Woodshedder,
I appreaciate your work, but you should consider switching your data provider (just kidding).
The SPY closed out the last month (September) with a +8.96% gain (not +6.93%), and this systematic error applies to every other month listed above as well.
SPY on AUG 31: 105.31
SPY on SEP 30: 114.13
Div.: $0.6021 (Sep. 17)
(114.13+0.6021)/105.31 – 1 = 8.96%
SPY’s performance in
JAN -3.63%
FEB 3.12%
MAR 6.09%
APR 1.55%
MAY -7.95%
JUN -5.17%
JUL 6.83%
AUG -4.50%
SEP 8.96%
If you’re using Yahoo’s ‘adjusted data’ (gradually – day bay day – accounting for dividend and cash payments): These are hyphotetical prices only, not tradable ones, and will never reflect real performance.
Best,
Frank
@TradingTheOdds
Also, I’m including .01 commissions/share in all the testing, including in the SPY. That is likely the reason for most of the difference.
Frank, I think it probably stems from how I am calculating the month. I use the open of the first trading day and the close of the last trading day of the month. Its not the data. I do this to attempt to replicate what it would be like if one started trading the first day of the month, not the close of the last day of the previous month. In hindsight, maybe that is not a good idea.
Thanks for your help Frank.
Woodshedder,
yes, this will probably be the reason.
But if the SPY serves as a benchmark (buy-and-hold approach instead of market timing), it should be based on closing values only, and one shouldn’t deduct $0.01 from closing prices every day (at the most on the first session – when going long – and on the last, assuming the buy-and-hold position would’ve been closed at the end of the period).
Best,
Frank
As much as possible, I’m am trying to keep all things equal.
The system only buys the open and sells the close. Therefore, when looking at trying to match/compare monthly performance, I have the SPY bought at the open of the first trading day and sold at the close of the last, just as the system performance for that 1 month would be tracked. If I have the SPY bought at the close of the last trading day of the month, there is the overnight period which the system cannot participate in because it buys the open.
Again, in order to keep all things equal, I account for .01/share commission on the open and close of the SPY trade, not $0.01 every day.
Perhaps this is not the best way to do this- I could just track the SPY from the first trading day of the year, account for commissions on that initial purchase, and use the monthly result. Initially, the reason I tracked the SPY for one month, with commissions accounted for on the open and close of the trade, was to make a direct comparison to a month of the system results as many subscribers sign up for one month at a time.
Anyway, these are good considerations. I strive to be transparent about everything and if the way I’m calculating things is confusing, then I’ll change it.