Introduction
You must have heard the term “dispersion” in many contexts. The literal meaning of this term is the action or process of distributing things or people in a wide area. However, when used in different contexts like physics and statistics, the term has different meanings which are significant to the particular topic it has been used in regard to. For now, let’s just focus on the use of the term dispersion in statistics or statistical dispersion which has its applications in various fields including finance and economics. If you are at all interested in economics and finance, or read news related to these topics, you must have often read the term statistical dispersion. But what does this term imply? And what importance does it have in the economic and financial world? This is exactly what we are going to try to understand by going through the basics of this term and understanding its application.
What is Dispersion?
The term dispersion is a statistical term which represents the size of distribution of values that are expected for a specific variable. Dispersion can be calculated and measured using different statistics such as, range, variance and standard deviation. The term dispersion has found its application in various fields including finance, economic, business analysis and forecasting. The main use of this is to make predictions regarding the future purposes.
When it comes to finance and investing, the term dispersion usually refers to the range of possible returns on an investment. However, it can also be used to measure the inherent and default risk in a particular security and investment portfolio. Dispersion is often represented as a yardstick of uncertainty which represents the risk associated with a financial security or an investment portfolio. This helps the investors to understand and weigh out the potential risks before making the investment decisions.
In simple terms, you can also say that dispersion is the range of potential outcomes of investments based on the historical volatility of returns. For your better understanding you can say that the higher the dispersion, the more risk is associated with the said investment, whereas when the dispersion is lower, the risk associated with the investment is much less. Therefore, dispersion is usually represented as a measure of the degree of risk or uncertainty associated with the investment portfolio or a security.
When choosing which security to invest in, investors have thousands of potential securities to choose from and have to consider many factors before making the final decision. One of the most important factors that the investors have to consider is the profile of the investment that they are interested in. This factor tops the list of the investors when it comes to considering all the essential factors before investing. To get a clear perspective concerning the profile of investment, dispersion is the most reliable measure that is used. The dispersion of return on an asset is the measure that represents the volatility and risk associated with holding that asset. The more variable the return on an asset, the more risky or volatile it is to hold that asset.
Understanding the measures of dispersion
There are basically two types of measures of dispersion— absolute measure of dispersion and relative measure of dispersion. An absolute measure of dispersion contains the same value as a data set. The variations expressed in the absolute measure of dispersion are in the terms of average deviations of observations like standard or mean deviations. The absolute measure of dispersion includes range, variance, standard deviation, quartiles and quartile deviation, and mean and mean deviation.
The relative measures of dispersion are used to compare distribution of two or more data sets. This measure compares values without units. The relative measures of dispersion includes, coefficient of range, coefficient of variation, coefficient of standard deviation, coefficient of quartile deviation, and coefficient of mean deviation.
As we already discussed above, the measures of dispersion are useful in determining the risk and volatility associated with the investment portfolio or a particular security. These measures of dispersion are used for defining the data spread or its variation around a central value. When measuring dispersion, two different samples may have an equal mean or meridian but completely different variability levels, or they may have the same variability levels and completely different mean or meridian. When describing a data set both these characteristics should be included. Various methods can be used to measure the dispersion of a data set. All these methods have their own advantages as well as disadvantages.
What is the Application of Dispersion?
Although the term dispersion has many applications, it is more commonly seen in reference to finance and investments. As we already discussed above, one of the determining factors for investors to decide which policy to invest in is the profile of the investment. The risks and volatility associated with this profile can be better known by the use of dispersion. This dispersion can be calculated using alpha and beta which measure the risk adjusted returns and returns adjusted to the benchmark index respectively.
Given the above explanation, you can say that dispersion is a statistical tool which gives the investors the necessary outlook before deciding which security or policy to invest in. dispersion on return of an asset indicates the volatility and risk associated with holding that asset. This gives companies as well as investors an idea about which assets to hold on to.
Dispersion also has an application in economics. When talking about dispersion in reference to economics, the term that is commonly used is price dispersion. This price dispersion in economics is the variation in the prices across sellers of the item, that has the same characteristics of the items sold by a seller. Price dispersion is considered to be a measure of trading frictions or violation of the law of one price. The price dispersion is often associated with the unmeasured attributes of the retailing outlets involved and the consumer search costs. It has been observed by market researchers and experts that the Semantic Web has effects on price dispersion when it comes to e-commerce.
