Well its time to take a look at how this thing actually performs.

But if you are new to this series, you might want to take a look at Part 1.

To recap:

System Specifics

The system will calculate the momentum/strength of each ETF in the portfolio, and then based on that metric, rank the ETFs. Version V1.0 will use RSI as the proxy for momentum.

• The top 4 highest ranked ETFs will be bought on the next open after the signal to rotate.
• Each ETF will be held for a minimum number of trading days.
• At the end of the minimum hold time, the ETF portfolio will be ranked and re-balanced, with all sells taking place at the close.

Version 1.0 will be using only 2 factors, which are RSI(65) and the minimum number of trading days to hold the ETFs, which is also 65. Again, review Part 1 to see why those inputs were chosen.

The Results:

Summary

SPY has a compound annual rate of 5.34% over the same time period, so V1.0, once commission and slippage is accounted for, has probably not done any better than a buy-and-hold strategy.

Obviously, the system has a propensity for large drawdowns, and that issue must be addressed. That will be an easy fix/test, and not very much fun since it is so easy. Therefore, we’ll make improving V1.0 a little more challenging. What I will do for V1.1 is use two different RSI calculations, weighting both of them differently, and then summing them to get our ETF rank. Any of you who read the comments section here have probably seen Jeff Pietsch of Market Rewind fame mention this method a couple of times. Using two different period settings and weighting them should be more interesting than applying the old moving average filter to deal with the drawdowns, and will keep the system simple 2 factor model, for now.

One other thing to mention is that there were not but a few ETFs trading back in the middle 1990s. Because the system is requiring 4 ETFs, you’ll notice that some of the early trades are held for a few years, because there were simply no other ETFs to rotate in to. This issue disappears after a few years and other ETFs come on board. You can explore all this by viewing the trades, which I’ve linked to below.

View all the trades here: ETF Rotational System V1.0 All Trades

It might be hard for technicians not to be bullish after Friday’s (2/5/2010) close.

After a tiny gap-up on the opening, the SPY traded down ~-2% and then reversed to close just above the open and above yesterday’s close. This action creates an interesting candlestick which shows the battle between the bulls and bears. (See circled candlestick on chart).

Another interesting feature of Friday’s trading was the surge in volume. Volume on Friday surged to close more than 2x greater than the 50 day volume moving average. The chart shows the number of shares trading hands was reminiscent of the volume surges when the market was forming the March 2009 lows.

MACD looks as if it might have made a higher low, diverging from price, while VIX closed more than 5% above its 10 day moving average (this VIX setup is a high-probability buy signal if one closes the trade when the VIX closes back beneath its 10 day moving average).

All these appear to be bullish signals.

I have to admit, I was feeling pretty bullish after seeing the market reverse from its death spiral to close higher.

I decided to test a set of conditions similar to the characteristics of Friday’s trading to see what typically happens afterward.

The Setup

Using SPY…

1. One day ago, the market closes at a new 20 day low.

2. Today, the H-L range is greater than 1.5%

3. Today, volume is more than 2x greater than the 50 day moving average of volume.

4. The close is higher than the open.

Buy the SPY next open, and sell the close n bars later.

Results

About the axis of the graph.

• The horizontal axis shows how long the trade was held. Exiting on day zero means the trade was closed the same day it was opened.
• The left vertical axis shows the percentage of winners
• The right vertical axis shows the percentage gain of the average trade.

The setup appears to have a bullish edge.

Caveats

There were only 22 instances of this setup since 1995.

The same conditions as tested above also existed on Friday’s close for IWM, QQQQ, and DIA. The setup is decidedly bearish on the QQQQ and IWM over the full 30 days after buying and only marginally effective for the DIA.

Because the volume surge on Friday was surprisingly large, I increased the surge requirement to 2.5x the average. This adjustment halved the number of instances of this setup to 11, and made the setup only marginally effective up to 5 days after the buy day, and then bearish to neutral for the following 25 days.

Considering these caveats, you may decide, as I have, that the setup may not be as bullish as it first appeared to be.

By the way, if you enjoy reading this type of study, the undisputed master of the genre is Rob Hanna over at Quantifiable Edges.

Also, Michael Arold did some similar research over on his blog, and even posts a chart of each instance of the setup: The Friday Reversal Trade.

For history on how we got here…

Thinking About a 4 Factor ETF Rotational System

More Thinking About Factors

Proposed ETF Portfolio for Rotational System

The first runs will test a very basic system as I want to be able to see if adding any more complexity to the system improves it (and how it improves it) in any way over simpler versions.

System Specifics

The system will calculate the momentum/strength of each ETF in the portfolio, and then based on that metric, rank the ETFs. Version V1.0 will use RSI as the proxy for momentum.

• The top 4 highest ranked ETFs will be bought on the next open after the signal to rotate.
• Each ETF will be held for a minimum number of trading days.
• At the end of the minimum hold time, the ETF portfolio will be ranked and re-balanced.

Version 1.0 will be using only 2 factors, which are RSI(x) where x represents the periods, and the minimum number of trading days to hold the ETFs, represented by y.

Lets take a look at how these factors play together, using AmiBroker’s 3D Optimization graph.

The most obvious feature of these graphs is that they are peaky. This is not a good thing. You know you have a robust interplay of factors when rather than looking like some crags in Switzerland, the graph looks like a nice grassy knoll.

I’ve circled the area that looks the most promising. We’ll be optimistic and call it the grass knoll. You can see that on either side of this area, performance begins to roll off.

So how do we choose the figures for x and y to plug into our factor calculations? Initially, I tend to eyeball things. I look for the area that seems to fall in the middle of the grassy knoll. If we choose a number near the edge of the knoll, it means that any change in the market may serious affect the system.

To my eyes, this looks like a value of near 65 for x and 65 for y. Even as I’m writing this, I haven’t tested those values, but I like them because they correspond nicely to 3 calendar months (approximately 22 trading days in a month). Keep in mind that if we choose the highest peaks for our x and y value, we will likely have curve fit the system.

Come Back for Part 2

In Part 2, we’ll backtest our x and y values over our ETF portfolio, take a look at the statistics and equity curve, and decide what we might do to improve performance.

I have to say that I’m very thankful that I asked for the collective wisdom of the blogosphere. The comments were very helpful and have absolutely solidified my thinking in how to approach this next ETF rotational system.

Okay, so the final step before we jump into this system is to decide the portfolio of ETFs on which to test.

My thoughts about this portfolio are simple. The ETFs should be liquid, cover the S&P500 sectors, contain some country specific ETFs, some commodities, and some inverse ETFs. I do not want leveraged ETFs and ideally we are looking for more than 5 years of trading.

I believe the list meets my goals, except the inverse ETFs are not quite as liquid as I hoped for and some of the ETFs have only been trading for a few years.

If there are any ETFs that you believe should be added or subtracted, please let me know in the comments section.

I’m going to ask for some input from the blogosphere with this issue.

I am a firm believer that a simple system is more robust than a more complex system. This means that a simple system is less likely to be curve-fit and more likely to survive changing market regimes without a major breakdown.

What I’m am struggling with is touched on briefly in the previous post about a 4 Factor ETF System.

As I think more about factors, I think it may be important to make a distinction about the number of inputs required to derive the factor.

For example, if we use Rate of Change to rank ETFs, then we have one factor (Rank) with one input (n periods):

Rank=ROC(n periods).

What if we instead use two differing ROCs, and weight them? That would look like this:

Rank=ROC(n periods*weight)+ROC(n periods*weight)

While “Rank” is still the single factor, we now have multiple inputs required to make this factor.

What I’m pondering is this: Are inputs equal to factors?

Thinking about what kind of ETF rotational system I would like to trade prompted me to ruminate a while upon which factors ( constituent or element that brings about certain effects or results) should be included. I want to keep things simple, which for me means not using more than four factors.

For an ETF system, we need to be able to assign some measure to the ETF in order to compare its performance relative to all of the other ETFs in the universe. I will call this factor 1.

Factor 1: This particular factor is often a measure of strength or weakness, perhaps Rate-of-Change, as we explored in the Fidelity Select system. The factor could be a moving average, or combination of moving averages, or the slope of a linear regression line.

For this next system, we will use RSI for factor 1.

Factor 2: Our next factor concerns how long the ETF will be held before it is rotated. Perhaps not rotating until after a specific amount of trading days have passed is an unnecessary waste of a factor. In that case, we could scan the ETF universe nightly to update the ranks for factor 1, and then rotate the next day into the ETFs that have moved into the top ranking.

As I believe that time exits have the tendency to be curve-fit, I want to make sure that we have a factor 2 that is robust, or else we will discard it and simply update the ETF rankings once a day.

Factor 3: The more I learn about trading and the markets, the more I realize the important role of volatility in affecting returns. For this reason, factor 3 will incorporate some measure of volatility. Will we use volatility to penalize the ranking mechanism, as we did in the Fidelity Select System, or will we seek to trade higher volatility ETFs? This will remain to be seen.

Factor 4: When I think about building a system that I could trade confidently for years at a time, factor 4 necessarily becomes some sort of drawdown protection. Factor 4 might only need to be something as simple as a moving average filter. Perhaps the moving average filter is replaced with inverse ETFs, and we instead diversify among a number of ETFs.

Other considerations, which I classify as filters rather than factors, concern how we decide which of the ETFs to exclude from our universe. Perhaps we only want ETFs that are liquid or perhaps we just want to include the S&P500 sectors. I have often wondered if these things that I consider filters are actually factors. This issue would make for an interesting discussion. Anyway, for now, I will not consider how we filter the universe to be a factor.

Next we will look at the basic ETF rotational system. I will outline the initial factors to be tested and will likely discuss my rationale for using them.

Our focus for The Power Dip System has always been to provide actionable picks with an edge, wrapped in a site that is simple and easy to use.

To that end, we have added ATR(10) metrics for each stock picked.

A quick glance at these metrics will aid in accurate and efficient position-sizing and setting of stops. Of course I am biased, but I think it is a great addition as it eliminates a step between getting the signals and entering orders into the platform.

Of course, if you are not a subscriber and would like to take a quick peek at the site, the 1 day trial is free and requires no billing information.