Strategy Basics
While it is commonly agreed that individual stock prices are difficult to forecast, there is evidence suggesting that it is possible to forecast the price ratio of the stock pair. A common way to attempt this is by constructing the portfolio such that the spread series is a stationary process. If we find a stock pair with long-term stable price ration, we can speculate with the high success rate on short-term ratio fluctuation will return to the mean value and we collect a profit. To achieve spread stationarity in the context of pairs trading, one can attempt to find a cointegration between the two stock price series. The stationary process can be than successfully modeled, and subsequently forecasted, using techniques of time series analysis.
Overall statistics
The following graphs summarizes an extensive study of the profitability of stock pairs. 324,125 stock pairs of 132 sectors of the US economy was tested using
Stock Pair Builder . Pairs were tested on the model Ratio with default settings (15 to 15 - 2.0 to 0.0) for a period of 1, 2, 3 and 4 years.
The trading strategy is based on the fact that the ratio is stable and oscillates around the average value. If (for whatever reason) ratio comes outside the normal area, you can speculate with high success rate that ratio will return to the mean value. This short-time divergence between pairs may be caused by temporary supply / demand changes when single large investor changes position in a single security, fundamental news, dividend payment etc. Deflection of the market is defined as the difference between current and long-term ratio of stock prices in the pair. If the difference exceeds a predefined threshold (usually the second standard deviation), strategy generate signal to enter the position. The output signal is defined as the ratio of prices return to long-term average or by achieving a time stop-loss.
Fig. 1: Chart of stock pair price ratio with entry levels and trades
Legend:
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Price ratio,
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price ratio moving average
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Entry levels = 2.standard deviation,
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trades
Correlation
Selection of suitable pairs is based on mutual correlation (dependency) of shares in the pair. The greater the correlation of stock prices,the more stable is the ratio of prices. Perfectly correlated stocks can usually be found within one sector (or subsector) economy (eg. mining and processing of gold, Life Insurance, Telecommunications, etc.). Selection of stocks in one sector also eliminates the risks associated with different economic development of various sectors.
Correlation of the shares in a pair is examined at different periods, most commonly 30 to 400. Correlation of prices fluctuate over time (the more, the shorter the period of calculation of correlation). Therefore average correlation is used for quantification. Stable stock pairs perform an average correlation of 70% to 80%.
Market Neutrality
The pairs trade helps to hedge sector- and market-risk. For example, if the whole market crashes, and the two stocks plummet along with it, the trade should result in a gain on the short position and a negating loss on the long position, leaving the profit close to zero in spite of the large move.
Drift and Risk Management
Trading pairs is not a risk-free strategy. The difficulty comes when prices of the two securities begin to drift apart, i.e. the spread begins to trend instead of reverting to the original mean. Dealing with such adverse situations requires strict risk management rules, which have the trader exit an unprofitable trade as soon as possible. One of the simplest and most effective way to achieve this is time stop-loss, which terminates the trade at the end of predefined period (typically 15 days).
Important part of risk management is also money management, ie. capital allocation to individual positions. Trading many (tens or hundreds) stock pairs helps to eliminate the risk since the funds allocated to a single (pair) position are only a small part of the trading account.