StrategyDesk 1.1: Minor Improvements, Still No Documentation
As John noted in the comments to a previous post, AMTD released the 1.1 version of StrategyDesk over the weekend. The changes are very small, in most cases hardly noticeable, but they are definitely improvements, so we can at least “keep hope alive.”
Let me just say right here- if you develop software of any kind (or hardware, or pretzels for that matter), when you release a new, improved version, for the sake of Judas Priest TELL US WHAT THE FREAKING IMPROVEMENTS ARE!!!. Do you StrategyDesk developers (I’m assuming there’s more than one of you) have any idea how aggravating it is to have to SEARCH for the changes like we’re working that puzzler in the funny papers where the dog’s tail is longer in one picture?? Is it too much to ask for a little info-teaser, like “Hey, try the new SD 1.1; we’ve addressed many issues including 1)this and 2)this and 3)that.”
The changes I’ve noticed include 1) the Screener and Strategy Setup windows (basically the same) are “sectioned” more clearly, making it a little more obvious what’s optional and what’s not 2) the context menus have improved in many places, notably with the options to import/export watchlists from within the Screener, and to Export Data from both the Screener and Backtester. This one seems minor at first, but it makes a world of difference when you start with a long list, say the S&P, and run it through a preliminary “filter screen” to pare it down. Rather than having to TYPE the resulting symbols into a new symbol list, you can now quickly EXPORT them into the new, “lean and mean” watchlist, on which you then apply your more complex criteria.
One other notable item - TDAmeritrade has now added a special email and phone number so we can contact the “StrategyDesk Team” directly. I’m still holding back, but I’m wanting to call and yell, “How can I RTFM if you won’t write me a decent FM?”
Using StrategyDesk to Test the TradingMarkets R2 Method
This is where a tool like StrategyDesk comes into its own. As you may know, TradingMarkets.com sells a tool called the R3/R4 method which claims average annual returns of nearly 260%. Sounds fantastic. Not fantastic as in “wow! great!” but fantastic as in “ludicrous and unrealistic”. Well, I’m here to report that after testing their publicly-published R2 system, I’m inclined to believe them. Not that you’ll make 260% per year (past performance yada yada yada), but that their system, over the specified time period, did in fact achieve that return. What will it return now? I dunno. It costs $8000, which means I can’t buy it unless I feel pretty certain it can make me $8001 over what I can do on my own. Hey, maybe it can. If I ever find out, I’ll let you know.
The R2 system is extremely simple, which is also to say, good. The name comes from the fact that their research on Welles Wilder’s RSI apparently showed that the “normal” 14-bar period didn’t return what they considered significant results, but that a very short 2-bar RSI actually did. The trading method they set up was very straightforward. It’s based on the S&P 500 index (or the related ETF, the SPYders), and simply looks for three consecutive lower-RSI2 days, with the first one being below 65 and as long as the current price is above the 200-day simple moving average. That’s the “buy” signal. The “sell” signal is even simpler: it’s the close of the day where the RSI2 subsequently hits 75. And with a 2-bar RSI, that’s usually within a couple of days.
Setting it up in StrategyDesk: Easy-greasy. Here’s the buy formula:
And here’s that big bad sell formula:
At first I ran the backtest, then ran it via a chart (StrategyDesk has a very neat function where it tags all the “buys” and “sells” the strategy generates on a chart, so you can observe visually whether the signals seem valid… think chart vs. spreadsheet). The results were very disappointing- at first. There seem to be a million buy and sell signals, and none of them catches the big moves. Click the chart and have a look for yourself:
However, I then noticed that the strategy seemed to be doing exactly what they claimed: generating a ton of very- short- term trades where the vast majority of the “sells” were higher than their corresponding “buys”. (I’ve noted, as I’m sure you have, that the last signal generated was a “BUY” and it was prior to last Tuesday. Once it pops up and the RSI2 hits 75, this last trade may knock the stats down for many months back — an even better argument for the 1.00 initial stop I suggest below).
I’m a “need-to-know” kinda guy, so I naturally exported the results into Excel to do some more calcs on them.
One caveat- StrategyDesk data only go back to January of 2000. Why? Hell, I don’t know. I’ve learned by now not to ask that question regarding this software. So the results are for 1/1/00 thru 12/31/06, and you’ll note the first trade triggered was in 2003 if you download the spreadsheet. That’s because May of ‘03 was the first time the price was above the 200ma and we had the three declining-RSI2 days as required by the formula.
The results from Excel are pretty impressive, and do bear out TradingMarkets’ claim about the R2 strategy. Here they are:
Total Trades Triggered: 35
Winners: 28 (80%)
Losers: 7 (20%)
Average gain per winner: 1.15/share (+/- 0.53)
Average loss per loser: 0.64/share (+/- 0.35)
Expectancy: 0.80 (this is an extremely good expectancy, considering that a stop could be placed 1.00 below the entry without decreasing the system’s performance… for an excellent discussion of expectancy, see this great article by TraderMike)
If you want to look at the (short, boring) spreadsheet of these results, grab a copy here.
The Upshot: Would I recommend the R2 method for trading? Nope, although it apparently isn’t too shabby even in this basic form. I would definitely recommend this as an excellent starting point for experimentation. Add rules to go short. Vary the period. See what works with different stocks. I suspect this is what the TradingMarkets folks did with their “R3/R4″ system, and after this little experiment, I think I see why you’ve gotta pay to see that one!