I was recently watching a short video hosted by Market Club. This particular video was a presentation on their “Perfect R Portfolio”. The Perfect R Portfolio is a portfolio of four ETFs (SPY, USO, GLD, and FXE) that are traded based upon Market Club’s “Trade Triangles” technology. The system rules are simple and clear. For each trade you dedicate 25% of your trading capital. Go long when you see a green Trade Triangle and close the position on the red Trade Triangle. These green and red signals are actually price levels that allow you to place your buy stop and sell stop orders and wait for the market to fill your orders. These values are updated weekly. It does not get any easier than that. Such a simple greenlight/redlight system can be very appealing. In short, the Perfect R Portfolio is a complete trading system that provides you with exact entry and exit levels.
Because the portfolio contains ETFs, does not trade very often and only takes long positions (there is no shorting in the Perfect Portfolio) it seems suitable for trading in retirement accounts such as a 401K. In fact, I do believe this is what the creators had in mind when developing the system.
How Do They Do It?
When I examined the entry and exit signals over time I came to the conclusion that the Trade Triangles are nothing more than a classic breakout indicator. That is, they simply take the highest high over the past N days to determine when to go long and then determine the lowest low over the past N days to determine when to close that same long position. More specifically in the case for the Perfect R Portfolio, they use a three month channel of price extremes to determine market direction (trend) and use a three week channel to determine entry/exit price levels. Trend trading based upon price channels is well documented and continues to be a valid trading method.
Trend: Three month price extreme.
Signal: Three week price extreme.
The trend component of the system is used to filter out bearish market conditions since the system only goes long. So, during bearish times we are in cash or cash equivalents waiting for the trend change to bullish.
For example, given an ETF we first determine the overall trend. This is done by determining the price extremes based on a monthly chart of the last three bars. A closing price on a daily chart above or below these levels would determine the trend either bullish (daily close above threshold) or bearish (daily close below threshold).
Once the trend is determined a three bar price extreme based on a weekly chart is used to determine when to exit and when to initiate new trades.
When the trend changes from bullish to bearish all trades are closed and we don’t open new long positions until the trend becomes bullish.
It’s that simple. Below is a trade example. Click the image to enlarge it.
But how well has the Perfect R Portfolio performed over the years? Well, the portfolio is rather new so they don’t provide much backtesting data. However, I created my own trading system called the TriFrame Portfolio using TradeStation’s EasyLanguage. Now I can backtest and see how well it did in the past. TradeStation’s ability to access several timeframes on a single chart will be required to make this trading system. First, all trades are executed on a daily chart, buy/sell price levels are determined on a weekly chart and trend is determined on a monthly chart. All three of these timeframes can be placed within one chart and accessed by a single TradeStation strategy.
Programmer speaking coming up so be warned.
First I’ll create a workspace with a chart of one of the ETFs used in the Perfect R Portfolio. I’ll select GLD. I will want to place trades on a daily chart so I set my GLD chart to daily price data. Next I want to generate buy/sell signals based upon a weekly chart. To do this I create a sub-chart of GLD to hold weekly price data within my chart. I can then access this data programmatically by referencing “data2” in my Easy Language code. I do the same thing for the monthly timeframe of GLD and can access that data by referencing “data3”.
Data1 = Daily chart
Data2 = Weekly chart
Data3 = Monthly chart
The TriFrame Portfolio will utilize these three timeframes to generate trading signals. Now I can test the system with the four ETFs over the life of each ETF. While TradeStation does have the ability to test a portfolio of ETFs given a single strategy, I have yet to explore this feature. So we’ll have to test each ETF individually. I created four different charts for each of the ETFs. I then added the strategy to each chart and dedicated $100,000 to each chart. The strategy would then trade 25% of the starting equity ($25,000) as indicated by the trading rules above. Profits and losses were accumulated and added to the starting equity after each trade. So how did the trading system do? The table below was created over the life of the ETFs through December 31, 2012. $30 in commissions were ducted per round trip.
Total Net Profit
Total No Of Trades
Avg.Trade Net Profit
Return on Capital
Annual Rate of Return
So, is this the “perfect portfolio?” While the returns are not spectacular, it’s probably better than the average person’s 401K over the past 6 years or so. The major benefit of the system is it will get you out of those large bear markets allowing you preserve your capital.
Using Ivy-10 Trading System Rules
What would happen if we took these four ETFs and traded them with the trading logic used with the Ivy-10 trading system? Using ETF Replay I generated the following results.
The ETF SPY was used as a benchmark. We can see this system generated a CAGR of 10.1% with a reasonable drawdown of 16.2%. Like the original trading rules, this system will keep you in cash during those bear markets. However, the total returns and CAGR look a lot better!