Businesses often indulge in calculating the profit potential of a trend. It gives them the edge to make informed decisions and navigate their business processes accordingly. In business and marketing, often two things are connected. For instance, the impact of marketing on sales or the impact of stock price on investments. To understand how strongly two elements are connected, the Pearson coefficient can be used.
Pearson coefficient can be simply seen as a statistical measure of correlation. It lets you establish the relation between two variables. The purpose is to unfold how two variables can impact each other as well as the market trends and finances. There are different types of Pearson coefficients and they can be used in various contexts including marketing and investment. This comprehensive guide will help you understand the use and limitations of the Pearson coefficient in finance.
Understanding Pearson Coefficient in Detail
English mathematician and statistician Karl Pearson is the man behind the Pearson coefficient. It is also known as the Pearson correlation coefficient or the Pearson product-moment correlation coefficient. In this concept, two variables, say X and Y are placed on a scatter plot (a type of graph) to represent the relation between the two variables.
The Pearson coefficient is somewhat similar to the correlation coefficient when represented numerically. They use a linear regression that ranges from -1 to +1. Here, -1 shows a negative relation while +1 shows a positive relation. 0 means no relation. The closer variables get to the straight line, the deeper the relation between the two variables. The relations can be seen as:
Perfect positive relation (+1)
+1 indicates a perfect positive relation. This means both variables move in the same direction. If one increases, the other also increases.
Perfect negative relation (-1)
-1 is used to denote a perfect negative relation. In this relation, both variables move in opposite directions. This means if one variable increases, the other decreases, and vice-versa.
No relation (0)
A zero means the two variables have no relations at all.
The Pearson coefficient can be used to diversify an investment portfolio. Scatter plots can help understand the relation of pairs of assets.
Note: Pearson coefficient only depicts the correlation between two variables and not the causation. The factors affecting relations are not measured.
Advantages and Disadvantages of the Pearson Coefficient in Finance
Pearson coefficients can have various advantages and disadvantages in finance. It offers a deep understanding of the correlation between two variables and their extent. Along with this, it also has certain limitations. The table below will give you a detailed insight into the advantages and disadvantages of the Pearson coefficient:
Advantages of Pearson Coefficient
| Disadvantages of Pearson Coefficient
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The method indicates whether or not two variables have a correlation
| The method does not explain if exactly a variable is dependent on the other
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The Pearson coefficient represents the extent to which two variables are correlated
| The causation of the correlation is not explained
|
The correlation is explained as positive, negative, or no relation with +1, -1, and 0, respectively
| What proportion of variation in the dependent variable affects the independent variable is not explained
|
Comparability is possible on different scales
| There are lots of assumptions involved like linearity between two variables, independence of each case, etc. ⁴
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Understanding correlation can help make informed financial decisions. Businesses and investments can benefit from this method
| The calculation can be a time-consuming process. Also, there is a probability of possible errors.
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How to Use Pearson Coefficient in Finance?
Pearson correlation coefficient is one of the most common types of correlation coefficient. In finance, the Pearson coefficient can be used for the following purposes:
Investment portfolio diversification
By understanding the relation between two assets, say two different stocks, investors can diversify their portfolios. In order to mitigate the risk of losses, portfolio diversification is essential. Investors may study the relationship between purchasing new stocks or selling existing ones.
Risk management
In terms of risk management in investment, high positive correlations can be a negative sign. Since the movement of those two variables is in the same direction, it has a high probability of impacting both gains and losses. In case of stock A moves toward loss, stock B may also accompany it in the same direction if they have a perfect positive relation. Here, investors may opt for perfect negative variables to mitigate the risk generated from one investment.
Forecasting
Financial analysts may use the Pearson coefficient to predict future trends. It used historical data to understand the correlation between variables. They may also use other coefficient correlation methods to reach a conclusion regarding potential future trends.
Limitations of Pearson Coefficient
Pearson coefficient, although a helpful tool in finance, has certain limitations as well. This coefficient correlation does not represent causation but just the correlation. So, this means it cannot be possible to understand if one correlated variable is dependent on the other one. The slope of the line also cannot be determined through the Pearson coefficient. For this purpose, the least squares method is used.
Apart from these, it is also not possible for Pearson coefficients to understand nonlinear associations or data points not within scatter plots. Nonparametric methods are used to understand these relations. These are some of the common limitations of the Pearson coefficient.