Correlation

Correlation is the simple understanding that refers to two items, or things that share a mutual relationship or similarity. Correlation can be used in a wide variety of fields and industries but can be prominent in the financial and banking industry.

Highly Correlated Versus Uncorrelated Investments

  • High Correlated Investments: These investments respond to the same forces driven by the market.
  • Uncorrelated Investments: These investments do not respond to changes or fluctuations of the market and have no direct similarity to other parts of the market.

Fund managers will usually use a correlation coefficient as a way to measure and calculate the value of investment portfolios and are used to help manage these portfolios. Using economic and financial correlation, fund managers can also help investors diversify their portfolios.

What is an example of correlation in investment?

One of the easiest examples to understand the correlation between stocks or assets is to look at that provided by Getbaraka.com:

In 2020, Uber Technologies and Lyft Inc shared the same type of positive correlation between 1 January 2020 and September 2020. What’s significant about this correlation is that both these companies had similar stock performance throughout 2020.

Even more, these companies share the same type of industry and offer the same type of products and services and one another.

Types of correlation

Positive Correlation

In terms of economics, a positive correlation is recognized when an investment relates and responds to the market forces. Simply put, when the market goes up, investments go up, and when the market decreases, so do the corresponding investments. This occurs as these two forces are correlated to one another.

Negative Correlation

A negative correlation is the opposite of what a positive correlation is. If the market performs poorly, then certain investments will decrease compared to market profitability.

Zero Correlation

The correlation coefficient is zero, meaning there is no real relationship between the two sets.

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