The Average Value Method for Economics

by Patrick Gleeson, Ph. D., Registered Investment Adv ; Updated July 27, 2017

The average value method, sometimes called the average cost method in accounting, provides an easy way to make a variety of determinations useful in finance and economics. One related calculation allows the analyst to reset marginal value on the basis of changing average value. More complex financial analyses incorporate the method as a simple, but essential building block that facilitates probabilistic analysis -- a range of far future values dependent upon uncertain intermediate future events.

Average Value Vs. Marginal Value

Relationships between average value and marginal value have three basic characteristics. When the average value curve rises, the marginal curve rises above it. When the average value curve falls, the marginal curve falls below it. When the average curve reaches its minimum, the average value equals the marginal value. To a set of prices, for example, if you add an additional price and thereafter the average price of the set rises, you can infer that the additional price, the marginal value, exceeds the previous average.

Average Cost Method

Average cost method accounting provides a quick and easy way of accurately determining the value of an asset group. Total cost for all units divided by the total number of units equals average cost. This formula applies to any group but has practical limits. For high-volume investors, for example, other accounting methods may produce outcomes faster.

Average Cost Method for Tax Purposes

Investors may use average cost method accounting to determine the cost basis for a group of equities purchased or sold in a given tax year. The average value, derived by dividing the total cost by the number of equities, equals the cost basis for all securities in the group. The investor can add or subtract this to any security purchased in the tax year to determine the taxable gain or loss.

Advanced Applications

The average value method underlies and facilitates more complex financial modeling, such as Monte Carlo simulation methods essential to risk analysis. Financial planners, for example, use this simulation method to build retirement models encompassing a range of outcomes -- essentially a probability distribution -- that depends upon such uncertainties as future interest rates. Even simulations that depend upon multiple variables -- future interest rates, stock market returns, life expectancy and any number of other variables -- have average value method computations at their core.


About the Author

Patrick Gleeson received a doctorate in 18th century English literature at the University of Washington. He served as a professor of English at the University of Victoria and was head of freshman English at San Francisco State University. Gleeson is the director of technical publications for McClarie Group and manages an investment fund. He is a Registered Investment Advisor.