To those of you unfamiliar with spread trading, this article will provide you with an overview of what is meant by the term along with an example of how to analyze and produce these types of trades.
So first, one purpose of a spread trade is that it shouldn't be highly correlated with a long position in the market. Usually, spread trades are either market neutral or they err on being negatively correlated with the market since that is a way to increase portfolio efficiency (having alpha generating positions that have a zero or a negative correlation with your long-only trades significantly increases the overall performance of your portfolio).
Second, a spread trade is usually formed by examining mean-reverting spreads and implementing the trade when the spread is at one extreme or the other. Let's take the example that we'll examine here, Consumer Discretionary Select Sector SPDR ETF (NYSEARCA:XLY) and Consumer Staples Select Sector SPDR ETF (NYSEARCA:XLP). These are two ETFs that provide exposure to consumer luxury (or discretionary) goods (XLY) and consumer staples (XLP). The majority holdings of XLY are:
Source: Yahoo Finance
And the majority holdings of XLP are:
Source: Yahoo Finance
As you can see, most of the holdings in XLY (except arguably McDonald's (NYSE:MCD) and some proportion of Home Depot (NYSE:HD)) are stocks that consumers utilize more often when they have more discretionary income. On the other hand, the stocks held in XLP are much more geared towards purchases that consumers have to make regardless of how much discretionary income they have (or are goods that are more in demand when discretionary income is below average).
Without looking at the data, we'd expect to see some relationship between these two ETFs that tends to widen and narrow based on how well the economy and market are doing and thus, how much discretionary income people have to spend (when they have a lot of discretionary income, or they expect to have a lot of future discretionary income, they buy more goods represented in XLY and vice versa holds for XLP).
Now, with that hypothesis, we can look at the data of the spread trade (calculated simply as the price of XLP minus the price of XLY):
Source: Yahoo Finance
During the two previous recessionary periods (the dotcom bust and the subprime mortgage crisis), we can see that there were increases in the price of XLP compared to XLY. Since the latter crisis, it appears that, based on how we'd interpret this relationship, that consumers have had an ever-increasing amount of discretionary income to spend since the 2008 crisis.
Fortunately, we have a convenient way to test this hypothesis, which is by looking at actual discretionary income growth over the same period (1998-2017):
Source: Author Calculation from FRED Real Disposable Income Series (DSPIC96)
Based on this chart, we can see some kind of relationship between discretionary income growth over the previous 12 months and the spread between XLY and XLP. Interestingly, there was recently a significant slowdown in the growth of discretionary income (from over 0.40% to just over 0%); however, the spread between XLY and XLP has continued to widen (except for a brief period in 2015). Indeed, the spread between XLY and XLP is at an all-time low.
The spread is also at its widest gap with respect to the S&P 500 (with which it has an approximately -55% correlation over the past 19 years EDIT: As pointed out in the comment below, it's better to look at monthly and daily data. The stats for the monthly data are that XLY's volatility was 1.47x XLP's in the monthly data and 1.50x XLP's in the daily data. Similarly there was a -65% correlation with the S&P using monthly data):
Source: Yahoo Finance & Author Calculation
So, assuming that we are convinced that the spread will narrow in the short to medium term, what can we do about it? In other words, how would we put on this trade?
The steps are relatively simple and they involve:
1. Determining the trade ratio, and
2. calculating the expected exit point based on a risk/reward analysis.
I'll provide the first and leave the second to the individual reader. For the trade ratio, what we want to do is create a position that allows for equal overall market exposure to each ETF. Since one ETF (XLY) is more volatile than the other (XLP), we need to take both their volatility and their correlation into account. As a result, to determine the amount to go long/short each ETF, we would utilize the following formula:
Trade Ratio = Vol(XLY)/Vol(XLP)*Corr(XLP, XLY)
where Vol() is the volatility of each ETF (daily volatility from 1998-2017) and Corr() is the correlation between their daily price movements over the same period. In this case, the calculation is 1.41%/0.95%*61.3% = 0.90 Trade Ratio.
This means that for every share of XLY bought, 0.90 shares of XLP should be bought as well. The cumulative return for holding this position is represented by the XLP/XLY (right axis) line in the above graph.
EDIT: Again as pointed out in the comments, it's better to use monthly and daily data to generate this ratio and the ratio should be applied to the dollar amount invested rather than the shares themselves. This means using the 0.83 trade ratio I calculated below in the comments and going short 109 shares of XLY and going long 156 shares of XLP for each $10,000 of XLY shorted.
Another way to examine how strong we'd believe this trading signal is would be to examine the Zscore of the spread itself (the first graph of the prices of XLP-XLY). Looking at the Zscore (which is the observation-average/(standard deviation) compared with the cumulative return of holding $0.83HeldinXLP*-$1HeldinXLY, we see the following:
Source: Yahoo Finance & Author Calculation
Based on this graph, we can see that the spread is at the largest number of standard deviations away from its average level than it's ever been. So the signal generated here would indicate a strong buy of this spread (buying $0.83ofXLP for every $1ofXLY that is shorted).
The exact sizing of the trade and exit strategy has been ignored in this article and is left to the reader.
Disclosure: I am/we are long THE XLP/XLY SPREAD. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it. I have no business relationship with any company whose stock is mentioned in this article.
