Inverse Lognormal Distribution Excel
The LOGNORM.INV Function is categorized under Excel Statistical functions. It will calculate the inverse lognormal distribution in Excel at a given value of x. We can use the function to analyze data that’s been logarithmically transformed.
LOGNORMAL distribution is often used in financial analysis to help make investment decisions. It is often used in analyzing stock prices, as normal distribution cannot be used to model stock prices. This is because the normal distribution includes a negative side and stock prices cannot fall below zero.
The LOGNORM.INV function is useful in financial analysis when we are given the probability and we wish to find the value of x. For example, we can use the function to know the probability of a stock price rising and want to find the stock price that is x.
Also, the function is useful in pricing options. The Black-Scholes model uses the lognormal distribution as its basis to determine option prices.
The LOGNORM.INV function uses the following argument:
- Probability (required argument) – This is the probability associated with the lognormal distribution.
- Mean (required argument) – The mean of In(x).
- Standard_dev (required argument) – This is the standard deviation of In(x).
Remember, If p = LOGNORM.DIST(x,…), then LOGNORM.INV(p,…) = x.
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How to use Inverse Lognormal Distribution in Excel?
To understand the uses of the LOGNORM.INV function, let’s consider an example:
Suppose we are given the following data:
Using the probability, mean, and standard deviation given above, the formula for calculating the inverse of lognormal cumulative distribution is shown below:
We get the result below:
Notes about Inverse Lognormal Distribution Excel
- #NUM! error – Occurs when:
- The argument x given is less than or equal to zero; or
- The argument standard_dev is less than or equal to zero.
- #VALUE! error – Occurs when any of the given arguments is non-numeric.
- The LOGNORM.INV function was introduced in Excel 2010 and hence is unavailable in earlier versions. For older versions, we can use the LOGINV function.
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