etf Archives - Algorithmic and Mechanical Forex Strategies

Trading International ETFs Using Kaeppel’s Switch Strategy

November 4, 2013 by Andrew Selby Leave a Comment

The recent evolution of ETFs as trading vehicles has expanded the available opportunities for traders and trading systems. In a recent post on his blog, Jay Kaeppel took a creative look at the good and bad aspects of international ETFs. He also put together a simple system that traded either a collection of international ETFs or the S&P 500.

Jay built a simple index of international ETFs and is using a Switch Strategy to trade them.

He starts with some of the positive and negative aspects of international stock and ETF trading:

The bad news is that picking individual stocks is never an easy thing even if you focus only on domestic U.S. companies. For the average investor to successfully pick and choose among individual stocks around the globe is simply too much to expect.
The good news is that the proliferation of international ETFs – Single country funds, regional funds, global funds, etc. – has made it much easier for investors to diversify across the globe than it used to be.
The bad news is that the proliferation of ETFs has also reached a point where choosing an international ETF is getting to be almost as confusing as choosing a phone plan.
The good news is that there are ways to simplify and systematize things.

Jay goes on to describe building what he calls the BRIC index. This is a collection of four international ETFs that represent Brazil, Russia, India, and China. His BRIC index is comprised of an equal part of the single country ETF for each of those four countries.

He then puts together a strategy that will compare the relative strength of his BRIC index to that relative strength of the S&P 500. Here is how he sums up the relative strength strategy:

I will use a method I learned a long time ago from David Vomund, President of Vomund Investment Management, LLC and the author of “ETF Strategies Revealed.”
The measure calculates the relative strength between two assets on a weekly basis.
When the trend of relative strength reverses in a particular direction for two consecutive weeks it signals a switch into the stronger index.

Jay produces thorough backtesting results for this system from 2001 through 2013. Investing half of a portfolio in his BRIC index and the other half in the S&P 500 would have returned a total profit of 189.3%. Using his switching system on the same indexes would have returned a total profit of 490%.

One obvious hole in this strategy is that the trader is still 100% long equities at all times. This means that the system would be extremely exposed to a global black swan event.

Jay doesn’t dodge this flaw, though. He makes a point to close by saying that this is not a system you should run out and start trading.

It is just an idea that appears to have an edge. It also allows traders to gain exposure to international markets without becoming an expert in them. I suggested to Jay that it would be interesting to see what would happen if he tested the same strategy using commodity or bond ETFs as well.

SPY Crisis Strategy Questions

October 14, 2013 by Shaun Overton Leave a Comment

Ed wrote me an email asking how he can trade the SPY Crisis Strategy. He likes the idea, but the problem is that his account balance is too small. He was under the impression that he can only participate with a futures account.

That was true several years ago. Luckily, the brokers have wised up and offer traders many more options. SPY is the ETF based on the S&P 500. ETFs are technically “Exchange Traded Funds”, but you can think of the SPY as a stock. You would place SPY trades in the same way that you buy or sell any stock in your brokerage account. Wikipedia offers a great ETF explanation if you’re new to the concept.

The returns that I posted for the strategy assumed that you were trading SPY without leveraged. If you’re a forex or futures trader, there are a few options available:

Forex traders can inquire if their broker offers index CFDs, especially if you want to trade the idea from MetaTrader. A CFD stands for “Contract For Delivery”, but don’t worry. Your broker has no desire or interest to make deliveries on oil or the S&P 500 CFDs. CFD is a legalistic creation where the broker promises to deliver the object traded on a certain date. In reality, the contract is perpetually rolled 2 days into the future. The position allows you to hold the spot price of the S&P 500 without needing to purchasing any stocks or resorting to the futures market.

The best option for futures traders are the e-minis (Symbol: ES). You should trade the front month contract for all signals. This is certainly the most efficient way to trade the idea. The only reason I stuck with the ETF is that I don’t have to dive into messy backtesting assumptions with continuous contracts and rolling open positions.

NinjaTrader is a great option regardless of the instrument that you trade. It’ll handle any market that you select: CFD, futures or the ETF.

SPY Crisis Strategy

October 11, 2013 by Shaun Overton 3 Comments

Yesterday’s musings on an S&P 500 doji strategy led to a general discussion of stocks and market crises. I promised to analyze a price-moving average cross strategy and to analyze the performance in times of exceptional volatility.

The results are in and they’re exactly what I predicted. I’m shamelessly tooting my own horn on this one – it’s so rare where strategies do exactly what I predicts.

The direction of the returns matches any traders definition of crisis and regular trading periods over the past decade

SPY Crisis Strategy Rules

The trading rules only initiate short trades. No long positions are allowed.

Enter short next bar at market when:
The price crossed and closed below the 20 day SMA on the last closed bar
The trader believes that a crisis environment either currently exists or is about to exist

Exit an open short trade when:
The price crosses and closes above the 20 day SMA on the last closed bar

The position size is equal to a fixed dollar value divided by the current share price. As an example, SPY currently trades at $169.24. If you wanted to control a position size worth $1,000, then the number of shares is the floor of $1,000/$169.24 = 5 shares.

This strategy is intended to be timely for the current trading environment. Based on all of my proposed definitions below, most of the crisis alarm bells are ringing at the moment.

Defining a crisis

The most difficult part of this type of strategy comes from defining a “crisis environment” quantitatively. Crises don’t happen very often by definition, so I don’t think it’s a worthwhile endeavor to try to quantity the crisis bit. That said, a few obvious crisis indicators come to mind based on basic market mechanics.

PE Ratio

The morons on Tout TV (CNBC and company) keep on screaming how cheap stocks are. I’m not a fundamental trader, but the PE ratio contains useful information. Even the most hard core technical analysis buff would agree that companies generating huge positive cash flow and earning growth have to appreciate at some point. The argument isn’t about if that type of stock will rise; it’s just a question of when.

I don’t see how anyone could possibly look at the current PE ratio of 19.3 and argue that stocks are cheap. They aren’t. Stocks are currently very expensive based on a historical comparison.

VIX

VIX is a CBOE benchmark index that allows traders to compare the price of front month options traded on the S&P 500. A more detailed explanation of the VIX is available on Wikipedia if the concept is new. There’s nothing magical about the 20 level. It’s my general experience that most traders consider that number the one to watch. They think of VIX < 20 as "normal" and VIX > 20 as a severe market move.

Most traders regard a VIX above 20 as a dangerous level.

Put-Call Ratio

Options are effectively leveraged bets on market movements with fixed downside risk. When traders load up on puts, they’re expecting the market to fall. When traders buy more calls, they’re expecting the market to rise.

The put call ratio is simply the number of put contracts traded / the number of call contracts traded. A number > 1 means that more puts were purchased that day than calls, indicating an expectation of a market drop.

Theory has it that short term traders are wrong, making the put call ratio a contrarian indicator. I see the put call ratio as more of a lagging indicator.

When a move is real and already happened, traders react too late and buy protection that they no longer need. The 2008 financial crisis a great example when the ratio spiked to 1.5, a wild number. Just in the past week the ratio went as high as 1.3 before settling back down. The volatility in the number indicates a panicky crowd in my opinion.

Margin debt

Leverage is a two way sword. The theory is that it’s a way to multiply returns by risking debt in the market.

Most traders, and especially retail traders, wind up using leverage as the rope to hang themselves with. Stocks are most commonly purchased with cash among investors. Unlike forex and futures where almost every trader enters a position with leverage, the average retail stock trader enters a position using only the cash present in his account.

An increased willingness among traders to move from cash to margin debt is typically a sign of froth, bubble fever or whatever you want to call it. The chart of margin debt from Business Insider and Zero Hedge show that stocks are currently trading near historical highs.

Conclusion

The 20 day SMA price cross strategy is a great way to run account protection whenever market warning signs are going off. The warning signs may not predict the precise market turning point, but the strategy can function as an effective form of insurance.

The strategy would roughly break even over time if someone were foolish enough to run it that way. Say that you mistime the crisis. Big deal. This type of strategy can run for months without causing irreparable harm to the account.

The signals can run in the background. If you’re only a little bit right with your crisis predictions, the risk reward ratio is massively in your favor. If you’re wrong, the consequences appear to be slow losses that lose a couple of percentage points per quarter. If you’re feeling edgy, I think it’s a great strategy to run in the background to calm your mind.

Backtesting Biases and Variations

October 3, 2013 by Andrew Selby 4 Comments

Last week, I wrote a post discussing how altering the timeframe of a system can change its results. That got me thinking about other ways that backtesting results could be skewed in one way or another based on user defined data such as the date range and market used. These simple differences can have a tremendous influence on the overall returns of any system, so it is important to pay them their proper respect.

When running backtests, it can be very easy to gloss over the down periods and cherry-pick the big return years. The problem is that you won’t have that opportunity when actually trading a system live. You will need to prepare yourself for the possibility that you select the wrong time or the wrong market to trade a given system. Otherwise, you run the risk of letting these backtesting biases adjust your expected return to values the system cannot possibly deliver.

Adjusting the Date Range

Let’s use our 10/100 Moving Average Crossover System from last week as a base. We tested it from January 1, 2001 through December 31, 2010 on the Vanguard Total Stock Market ETF (VTI). All of our tests last week used a starting portfolio value of $10,000, a 10% trailing stop, and a $7 commission.

MA crosses on VTI returned almost 90% over the last decade.

Based on those settings, our 10/100 MA Crossover System returned 89.8% over ten years. This works out to be an annualized return of 12% with a maximum drawdown of 16.2%.

If we would have started trading this system on January 1, 2003, we would have registered a total return of 39% in the three years of trading until the end of 2005. This would have been good for a 16.4% annualized return with a maximum drawdown of only 6%. As you can see, if we based our strategy on these results, we would be expecting the system to continue to produce these extremely high returns.

On the other hand, if we would have started trading this system on January 1, 2006, we would have seen a total return of only 2.5% in the first three years. We also would have had to sit through a 14.2% drawdown.

It is also worth noting that while the ten year track record of this system from 2001 through 2010 is very respectable, we wouldn’t have known that when we started in 2001. If we actually started trading this system in 2001, we would show a total return of -6.2% at the end of 2002. After two full years trading this system, we would not have had a single thing to show for it. The system didn’t find its first big winner until April 15, 2003.

As you can see, the time you chose to begin trading the 10/100 Moving Average Crossover System could have made all the difference over the course of what was a net-profitable decade. It is very important to keep this in mind when you are struggling through drawdowns.

Adjusting the Markets Traded

The market you choose to trade can have the same affect on your trading as the date you start trading. Let’s look at how the exact same system would have performed over the exact same decade if we chose to trade it on different ETFs.

Trading the 10/100 Moving Average Crossover System on the XLF, which represents financials, would have provided a total return of -9.4% for the decade with a maximum drawdown of 30%. It is obvious to us at this point that financials had a rough time during this period, but we would have had no clue about that when we started in 2001.

The XLY, which represents consumer discretionary stocks, also would have underperformed the VTI. Trading the system on the XLY would have returned a total of 39.4, or 6.4% annually, with a maximum drawdown of 21.3%.

XLY shows a 39.4% return over the same decade

If we would have been fortunate enough to trade the XLK, which represents the technology sector, we would have seen a tremendous total return of 95.7%. This works out to be an annual return of 14.2% with a maximum drawdown of 22.3%.

Once again, we see that decisions like what markets to trade and when to start can have a tremendous influence on our results. This is why it is so important to thoroughly backtest any strategy across many different combinations of date ranges and markets.