 # Glossary: 20 pair trading terms for beginners

4.3

Pair trading is a strategy that involves matching a long position with a short position in two highly correlated stocks. Here, a trade is initiated when the correlation between the two stocks weakens temporarily. At this point, the price of one stock may move up, while the price of the other may remain unchanged or may move downward. In such a scenario, the pair trader initiates the trade by taking a long position in (or buying) the cheaper stock, and taking a short position in (or selling) the more expensive stock.

2. Correlation

Correlation is a concept that tells you how closely two given variables are related, if at all they are. It is measured and expressed using the correlation coefficient. The correlation coefficient ranges from -1 to +1.

The symbol tells you the direction of movement. A positive symbol means that the two variables tend to move in the same direction, while a negative symbol means they typically move in opposite directions.

The number following the symbol tells you the strength of the correlation. A correlation coefficient of 0.90, for instance, is stronger than a correlation coefficient of 0.60.

3. Differential

Differential is the difference in the closing price of the stocks in consideration. Here’s the formula for the differential.

 Differential = Closing price of stock A - Closing price of stock B (or vice versa)

The spread is  the difference between the daily changes in closing prices of the two stocks.

The formula for the spread is:

 Spread = Daily change in closing price of stock A - Daily change in closing price of stock B (or vice versa)

5. Price ratio

This is the ratio of the closing price of stock A to the closing price of stock B (or vice versa).

Check out the formula below.

 Price ratio = Closing price of stock A ÷ Closing price of stock B (or vice versa)

6. Divergence

A divergence occurs when the correlative behavior between the two stocks is temporarily weakened because they’re moving apart. This leads to an increased spread between the two stocks, and thereby, an increased ratio. The graph typically moves upward during such points, giving traders an indication that a divergence is occurring.

7. Convergence

A convergence occurs when the correlative behavior between the two stocks is temporarily weakened because they’re moving closer. This leads to a decreased spread between the two stocks, and consequently, a decreased ratio. The graph typically moves downward during such points, giving traders an indication that a convergence is occurring.

8. Mean

The mean is also commonly known as the average. Simply put, it represents the average value in a group of data points. It is calculated as the sum of all the data points, divided by the total number of data points.

Here’s the formula.

 Arithmetic mean = (Sum of all observations) ÷ (Total number of observations)

9. Median

The median represents the middle value in a set of distributions. To figure out what the median is, the given data points first need to be arranged in ascending order. Then, here’s how you calculate the median.

• If there is an odd number of observations, the median is the observation that features in the middle of the arrangement.
• If there is an even number of observations, the median is the average of the two middle data points.

10. Mode

The mode is the observation in a data set that occurs the maximum number of times.

11. Standard deviation

The standard deviation is a statistical tool that measures how far a data set is dispersed from its mean.

12. Daily return

The daily return is a measure of the gain (or the loss) that the daily price movements of a stock bring in. It is expressed as a percentage, and it’s calculated using the formula given below.

 Daily return: (Today’s closing price - Previous day’s closing price) ÷ Previous day’s closing price

13. The empirical rule

The empirical rule shows how data is dispersed in a normal distribution. It states that:

• 68% of values are within one standard deviation (1 SD) away from the mean.
• 95% of values are within two standard deviations (2 SD) away from the mean.
• 99.7% of values are within three standard deviations (3 SD) away from the mean.

14. Density curve

The density curve is a theoretical curve that represents the probability of a variable reverting to the mean.

A long trade, in the context of pair trading, involves taking a long position on the numerator stock and a short position on the denominator stock (if you’re using the price ratio as a variable). If you’re using residuals, it involves taking a long position on the dependent stock and a short position on the independent stock.

A short trade, in the context of pair trading, involves taking a short position on the numerator stock and a long position on the denominator stock (if you’re using the price ratio as a variable). If you’re using residuals, it involves taking a short position on the dependent stock and a long position on the independent stock.

17. Straight line equation

The straight line equation shows the relationship between two variables. It is written as:

y = mx + c

Here, y is the dependent variable while x is the independent variable. The slope is denoted as m, and the intercept is c.

18. Linear regression

Linear regression is a technique that aims to establish the relationship between two variables by fitting a linear equation to observed data. One variable is considered to be an independent variable, and the other is considered to be a dependent variable. Since the data is discrete and unconnected, the linear regression technique tries to make sense of the data points you have and identify a possible relationship between them.

19. Residuals

Residuals represent the deviations of the observations from the linear regression line. It is represented as the vertical distance between the coordinates of a data set and the regression line.

20. Error ratio

This is the ratio of the standard error of intercept and the standard error. Here is the formula.

 Error ratio = Standard error of intercept ÷ Standard error

The standard error in the denominator is essentially the standard deviation of the residuals for each data pair.

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