Guide to Pairs Trading - Part 2
Fundamental and Technical Analysis
Pairs traders employ either fundamental or technical analysis, or a combination of the two, to make decisions regarding which instruments to pair, and when to get in and out of trades. Many pairs traders apply technical analysis techniques and then confirm the findings using fundamentals. This extra “layer” of analysis can be used simply to ensure that the trade “makes sense”. For instance, if all technical analysis points to taking a long position in stock ABC and a short in XYZ, but the fundamentals show that stock ABC will have a weak earnings report, the position may need to be reconsidered.
Fundamental analysis examines related economic, financial and other qualitative and quantitative factors to evaluate a security’s value, and to determine which security will perform better in the short-term. Fundamental analysts may consider a number of growth and value factors when identifying opportunities for pairs trading. These include (but are not limited to):
Changes in operating margins
Discounted cash flow
Dividend discount model
Excess cash flow
Price/earnings to growth (PEG ratio)
Price-earnings ratio (P/E ratio)
Price-to-book ratio (P/B ratio)
Price-to-cash-flow ratio (price/cash)
Price-to-sales ratio (price/sales)
Return on equity
Total assets over sales.
Technical analysis, on the other hand, is a method of evaluating securities by analyzing statistics generated by market activity; in particular, historical price and volume. Rather than attempting to measure a security’s intrinsic value, technical analysis seeks to identify patterns to predict future price movements.
Pairs traders call on a variety of tools and technical indicators to identify trading opportunities. The technical analyst may use, for example:
Chart patterns (i.e., candlestick charting)
On-balance volume (OBV)
Relative strength index (RSI)
Support and resistance
Other metrics may be useful to pairs traders as well. Consider beta, for example. Market risk can be measured by beta: a measure of a stock’s volatility relative to the market. The market has a beta of 1.0, and each individual stock is ranked based on how much it deviates from the market. If a stock swings more than the market over time, it will have a beta above 1.0; conversely, if a stock moves less than the market, its beta will be less than 1.0. High-beta stocks are considered riskier but tend to provide the potential for higher returns. Low-beta stocks have less risk, accompanied by lower potential returns. Ideally, the securities in a pairs trade have betas that are stable over time.
Deciding to implement a fundamental or technical approach is a matter of personal preference. Many pairs traders, and in particular short-term traders, prefer a technical approach. Some conduct technical analysis and look for confirmation using certain fundamentals, while others may use fundamental analysis exclusively. As with any investment strategy, finding the right combination of analysis tools and methodology takes research, historical modeling and testing.
As with nearly any investment, taking a pairs trade involves more than just hitting the buy and sell button. Here we examine, in very broad terms, the steps required to enter and exit a pairs trade.
Assemble a list of potentially related pairs
Just as long-only stock traders scan the markets for suitable securities, a pairs trader must start with a list of potentially related pairs. This entails conducting research to find securities that have something in common – whether the relationship is due to sector (such as the auto sector) or to asset (for example, bonds). While any random pair could theoretically be correlated, it is more likely that we will find correlation in securities that have something in common to begin with.
Determining the correlation level
The next step acts as a filter, or a means by which we can reduce the number of potential pairs in our quiver. One way is to use a correlation coefficient to determine how closely two instruments are related. Figure 4 shows a daily chart of the e-mini S&P 500 contract (in red) and the e-mini Dow contract (in green). Below the price chart is an indicator that shows the correlation coefficient (in yellow). We can see from the chart that during the time period evaluated, the ES and YM are highly correlated, with values hovering around 0.9. We will keep the ES/YM pair on our list of potential pairs candidates.
Figure 4 The e-mini S&P 500 contract (in red) and the e-mini Dow (in green) show potential as a pairs trade. Visual confirmation of price, backed by quantitative results from the correlation coefficient (in yellow), show that the two instruments are highly correlated. Image created with TradeStation.
Another chart, shown in Figure 5, illustrates a pair that is not correlated. In this example, a daily chart of Wal-mart (in red) and Target (in green) shows little correlation between the two instruments, despite the fact that they “have something in common”. Here, the correlation coefficient (in yellow) demonstrates that the relationship is scattered, ranging from high values of about 0.7 to values below zero, indicating a lack of correlation. In this case, we can remove the WMT/TGT pair from our list of potential pairs candidates.
Figure 5 This daily chart of WMT (in red) and TGT (in green) shows that this is not an ideal pair (at least not during the time period tested). A visual review of prices, confirmed by results from the correlation coefficient (in yellow) indicate a lack of correlation between the two stocks. Image created with TradeStation.
Use modeling to determine specific rules
An ongoing component of the process is to research and test trading ideas and determine absolute methods of evaluating pairs and defining divergence. Traders will have to answer questions like What constitutes “enough” divergence from the trend to initiate a trade? and How will this be evaluated (for example, using data from a price ratio indicator with standard deviation overlays). In general, traders should focus on quantifiable data: i.e., “I will enter a pairs trade when price ratio exceeds two standard deviations.” Figure 6 shows two ETFs – SPY (in red) and DIA (in green) – on a daily chart. Below the price chart is a spread ratio indicator (in blue), with a +/- one and two standard deviation overlay (dotted lines). The mean appears in pink.
Figure 6 A daily chart of the ETFs SPY (in red) and DIA (in green). A spread ratio indicator appears below the price chart, along with a standard deviation overlay. Image created with TradeStation.
Determining position sizing
Many traders use a dollar-neutral approach to position sizing when trading pairs. Using this method, the long and short sides of the trade are entered with equal dollar amounts. For example, a trader wants to enter a pairs trade with stock A, trading at $100 per share, and stock B, trading at $50 per share. To achieve a dollar-neutral position, the trader will have to purchase two shares of stock B for every one share of stock A. For example:
Long 100 shares of stock A = $10,000; and
Short 200 shares of stock B = $10,000.
Buy the underperformer and sell the overperformer
Once the trading rules are met, the trader will buy the underperforming security and simultaneously sell the overperforming security. In Figure 7, the spread ratio has exceeded two standard deviations, and a trading setup has occurred in our ES/YM pair. Here, a long position is entered with two ES contracts, and a simultaneous short position of two contracts is taken in the YM.
Figure 7 A trade is opened in the ES/YM pair. The order entry interface appears on the left side of the screen (one order entry box for the ES; one for the YM). The horizontal red and green lines at the top show the real-time P/L for each position. Image created with TradeStation.