What is Log-Normal Distribution

The log-normal distribution is a term associated with statistics and probability theory. Similarly, another name for the log-normal distribution is Galton distribution. The log-normal distribution represents a continuous distribution of random variables with normally distributed logarithms. It follows the concept that instead of having normally distributed original data, the logarithms of the data also show normal distribution.

A log-normal distribution is similar to normal distribution. In fact, the data in both of them can be used interchangeably by calculating the logarithms of the data points. However, the log-normal distribution is different from the normal distribution in many ways.

Add your business to our business directory https://harbourfronts.com/directory/ Add your business. Also check out other businesses in the directory

The biggest differentiating factor between the two is their shapes. While normal distribution represents a symmetrical shape, a log-normal distribution does not. The difference in their shapes comes due to their skewness. As log-normal distribution uses logarithmic values, the values are positive, thus, creating a right-skewed curve. Another difference between the two is the values used on deriving both.

What are the parameters of Log-normal Distribution?

The log-normal distribution has three parameters. These are the median, the location, and the standard deviation. Firstly, the median, also known as the scale, parameter, shrinks, or stretches the graph, represented by ‘m’. Secondly, the location, represented by ‘Θ’ or ‘μ’ represents the x-axis location of the graph.

Lastly, the shape parameter or standard deviation, represented by ‘σ’, affects the overall shape of the log-normal distribution. It does not impact the location or height of the graph. The parameters are available in historical data. However, it is also possible to estimate using current data.

What are the characteristics of Log-normal distribution?

Log-normal distribution has several characteristics or features. First of all, it shows a positive skew towards the right due to its lower mean values and higher variances in the random variables in consideration. Secondly, for log-normal distribution, the mean is usually higher than its mode because of its skew with a large number of small values and few major values.

Lastly, log-normal distribution does not include negative values. It is a feature that differentiates it from a normal distribution and, therefore, a defining characteristic.

What are the uses of Log-normal distribution?

Log-normal has several use cases in the world of finance. Most importantly, it fixes some problems with normal distribution, which helps increase its usage. For example, a normal distribution may include negative variables, while log-normal distribution consists of positive variables only. Apart from that, log-normal distribution is also commonly used in stock prices analysis.

Log-normal distribution can help investors identify the compound return that they can expect from a stock over a period of time. Usually, they use the normal distribution to analyze the potential returns they get from it. However, for analyzing the prices of stocks, log-normal is a better choice.

In finance, log-normal distribution common for calculating asset price over a period of time. It is because normal distribution may provide inconsistent prices, while log-normal does not have the same problem. It solves the problem with normal distribution taking asset prices below zero or negative. Therefore, the log-normal produces better results.

Conclusion

The log-normal distribution shows the continuous distribution of random variables with normally distributed logarithmic values. It is different from the normal distribution in several ways. There are three parameters in log-normal distribution, the median, the location, and the standard deviation.

Further questions

What's your question? Ask it in the discussion forum

Have an answer to the questions below? Post it here or in the forum

LATEST NEWSChild social media stars have few protections. Illinois aims to fix that
Child social media stars have few protections. Illinois aims to fix that

CHICAGO (AP) — Holed up at home during the pandemic lockdown three years ago, 13-year-old Shreya Nallamothu was scrolling through social media when she noticed a pattern: Children even younger than her were the stars — dancing, cracking one-liners and being generally adorable. “It seemed…

Stay up-to-date with the latest news - click here
LATEST NEWSWall St Week Ahead-Amid banking woes, faltering US small-caps offer ominous economic sign
Wall St Week Ahead-Amid banking woes, faltering US small-caps offer ominous economic sign

NEW YORK — A U.S. stocks rally is leaving behind smaller companies, a sign that investors may be bracing for economic turmoil ahead. The small-cap Russell 2000 is down about 1% this year, compared to a rally that has boosted the S&P 500, an index…

Stay up-to-date with the latest news - click here
LATEST NEWSCanada housing market upturn could delay shift to BoC rate cuts
Canada housing market upturn could delay shift to BoC rate cuts

TORONTO — Signs of recovery in Canada’s housing market after a year-long slump, just as higher borrowing costs are expected to slow much of the rest of the economy, could raise inflation and delay a shift by the central bank to interest rate cuts, analysts…

Stay up-to-date with the latest news - click here
LATEST NEWSFOMO is returning to Canada’s housing market
FOMO is returning to Canada’s housing market

Watch: John Pasalis of Realosophy Realty says low supply is sparking bidding wars and rising prices

Stay up-to-date with the latest news - click here
LATEST NEWSA.I. might finally kill off the cover letter
A.I. might finally kill off the cover letter

ChatGPT could render writing the cover letter as we know it dead—with a few human adjustments.

Stay up-to-date with the latest news - click here

Leave a Reply