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**Compound annual growth rate** (**CAGR**) is a business and investing specific term for the geometric progression ratio that provides a constant rate of return over the time period.^{ [1] }^{ [2] } CAGR is not an accounting term, but it is often used to describe some element of the business, for example revenue, units delivered, registered users, etc. CAGR dampens the effect of volatility of periodic returns that can render arithmetic means irrelevant. It is particularly useful to compare growth rates from various data sets of common domain such as revenue growth of companies in the same industry or sector.^{ [3] }

In mathematics, a **geometric progression**, also known as a **geometric sequence**, is a sequence of numbers where each term after the first is found by multiplying the previous one by a fixed, non-zero number called the *common ratio*. For example, the sequence 2, 6, 18, 54, ... is a geometric progression with common ratio 3. Similarly 10, 5, 2.5, 1.25, ... is a geometric sequence with common ratio 1/2.

**CAGR** is equivalent to the more generic exponential growth rate when the exponential growth interval is one year.

**Exponential growth** is exhibited when the rate of change—the change per instant or unit of time—of the value of a mathematical function of time is proportional to the function's current value, resulting in its value at any time being an exponential function of time, i.e., a function in which the time value is the exponent. Exponential decay occurs in the same way when the growth rate is negative. In the case of a discrete domain of definition with equal intervals, it is also called **geometric growth** or **geometric decay**, the function values forming a geometric progression. In either exponential growth or exponential decay, the ratio of the rate of change of the quantity to its current size remains constant over time.

CAGR is defined as:

where is the initial value, is the end value, and is the number of years.

Actual or normalized values may be used for calculation as long as they retain the same mathematical proportion.

In this example, we will compute the CAGR over three periods. Assume that the year-end revenues of a business over a three-year period, , have been:

Year-End 12/31/2004 12/31/2007 Year-End Revenue 9,000 13,000

Therefore, to calculate the CAGR of the revenues over the three-year period spanning the "end" of 2004 to the "end" of 2007 is:

- –

Note that this is a smoothed growth rate per year. This rate of growth would take you to the ending value, from the starting value, in the number of years given, if growth had been at the same rate every year. (In reality, growth is seldom constant.)

**Verification**:

Multiply the initial value (2004 year-end revenue) by (1 + CAGR) three times (because we calculated for 3 years). The product will equal the year-end revenue for 2007. This shows the compound growth rate:

For *n* = 3:

**For comparison**:

- the Arithmetic Mean Return (AMR) would be the sum of annual revenue changes (compared with the previous year) divided by number of years, or:

In contrast to CAGR, you cannot obtain by multiplying the initial value, , three times by (1 + AMR) (unless all annual growth rates are the same).

- the arithmetic return (AR) or simple return would be the ending value minus beginning value divided by the beginning value:

These are some of the common CAGR applications:

- Calculating and communicating the average returns of investment funds
^{ [4] } - Demonstrating and comparing the performance of investment advisors
^{ [4] } - Comparing the historical returns of stocks with bonds or with a savings account
^{ [4] } - Forecasting future values based on the CAGR of a data series (you find future values by multiplying the last datum of the series by (1 + CAGR) as many times as years required). As every forecasting method, this method has a calculation error associated.
- Analyzing and communicating the behavior, over a series of years, of different business measures such as sales, market share, costs, customer satisfaction, and performance.

- Annual growth %
- Arithmetic mean
- Average annual return
- Continuous compounding
- Geometric mean
- Exponential growth
- Multiplicative calculus

In mathematics and statistics, the **arithmetic mean**, or simply the mean or **average** when the context is clear, is the sum of a collection of numbers divided by the count of numbers in the collection. The collection is often a set of results of an experiment or an observational study, or frequently a set of results from a survey. The term "arithmetic mean" is preferred in some contexts in mathematics and statistics because it helps distinguish it from other means, such as the geometric mean and the harmonic mean.

In mathematics, the **geometric mean** is a mean or average, which indicates the central tendency or typical value of a set of numbers by using the product of their values. The geometric mean is defined as the *n*th root of the product of n numbers, i.e., for a set of numbers *x*_{1}, *x*_{2}, ..., *x _{n}*, the geometric mean is defined as

In mathematics, a **multiplicative calculus** is a system with two multiplicative operators, called a "multiplicative derivative" and a "multiplicative integral", which are inversely related in a manner analogous to the inverse relationship between the derivative and integral in the classical calculus of Newton and Leibniz. The multiplicative calculi provide alternatives to the classical calculus, which has an additive derivative and an additive integral.

The number **e** is a mathematical constant that is the base of the natural logarithm: the unique number whose natural logarithm is equal to one. It is approximately equal to **2.71828**, and is the limit of (1 + 1/*n*)^{n} as n approaches infinity, an expression that arises in the study of compound interest. It can also be calculated as the sum of the infinite series

In mathematics, an **exponential function** is a function of the form

In probability theory and statistics, the **exponential distribution** is the probability distribution that describes the time between events in a Poisson point process, i.e., a process in which events occur continuously and independently at a constant average rate. It is a particular case of the gamma distribution. It is the continuous analogue of the geometric distribution, and it has the key property of being memoryless. In addition to being used for the analysis of Poisson point processes it is found in various other contexts.

In physical chemistry, the **Arrhenius equation** is a formula for the temperature dependence of reaction rates. The equation was proposed by Svante Arrhenius in 1889, based on the work of Dutch chemist Jacobus Henricus van 't Hoff who had noted in 1884 that van 't Hoff equation for the temperature dependence of equilibrium constants suggests such a formula for the rates of both forward and reverse reactions. This equation has a vast and important application in determining rate of chemical reactions and for calculation of energy of activation. Arrhenius provided a physical justification and interpretation for the formula. Currently, it is best seen as an empirical relationship. It can be used to model the temperature variation of diffusion coefficients, population of crystal vacancies, creep rates, and many other thermally-induced processes/reactions. The Eyring equation, developed in 1935, also expresses the relationship between rate and energy.

In colloquial language, an **average** is a single number taken as representative of a list of numbers. Different concepts of average are used in different contexts. Often "average" refers to the arithmetic mean, the sum of the numbers divided by how many numbers are being averaged. In statistics, mean, median, and mode are all known as measures of central tendency, and in colloquial usage any of these might be called an **average value**.

In economics and finance, **present value** (**PV**), also known as **present discounted value**, is the value of an expected income stream determined as of the date of valuation. The present value is always less than or equal to the future value because money has interest-earning potential, a characteristic referred to as the time value of money, except during times of negative interest rates, when the present value will be more than the future value. Time value can be described with the simplified phrase, "A dollar today is worth more than a dollar tomorrow". Here, 'worth more' means that its value is greater. A dollar today is worth more than a dollar tomorrow because the dollar can be invested and earn a day's worth of interest, making the total accumulate to a value more than a dollar by tomorrow. Interest can be compared to rent. Just as rent is paid to a landlord by a tenant without the ownership of the asset being transferred, interest is paid to a lender by a borrower who gains access to the money for a time before paying it back. By letting the borrower have access to the money, the lender has sacrificed the exchange value of this money, and is compensated for it in the form of interest. The initial amount of the borrowed funds is less than the total amount of money paid to the lender.

A **logistic function** or **logistic curve** is a common "S" shape, with equation:

In probability theory, a **log-normal distribution** is a continuous probability distribution of a random variable whose logarithm is normally distributed. Thus, if the random variable X is log-normally distributed, then *Y* = ln(*X*) has a normal distribution. Likewise, if Y has a normal distribution, then the exponential function of Y, *X* = exp(*Y*), has a log-normal distribution. A random variable which is log-normally distributed takes only positive real values. The distribution is occasionally referred to as the **Galton distribution** or **Galton's distribution**, after Francis Galton. The log-normal distribution also has been associated with other names, such as McAlister, Gibrat and Cobb–Douglas.

The **time value of money** is the greater benefit of receiving money now rather than an identical sum later. It is founded on time preference.

In finance, the **rule of 72**, the **rule of 70** and the **rule of 69.3** are methods for estimating an investment's doubling time. The rule number is divided by the interest percentage per period to obtain the approximate number of periods required for doubling. Although scientific calculators and spreadsheet programs have functions to find the accurate doubling time, the rules are useful for mental calculations and when only a basic calculator is available.

In probability and statistics, an **exponential family** is a parametric set of probability distributions of a certain form, specified below. This special form is chosen for mathematical convenience, based on some useful algebraic properties, as well as for generality, as exponential families are in a sense very natural sets of distributions to consider. The term **exponential class** is sometimes used in place of "exponential family", or the older term **Koopman-Darmois family**. The terms "distribution" and "family" are often used loosely: properly, *an* exponential family is a *set* of distributions, where the specific distribution varies with the parameter; however, a parametric *family* of distributions is often referred to as "*a* distribution", and the set of all exponential families is sometimes loosely referred to as "the" exponential family.

**Compound interest** is the addition of interest to the principal sum of a loan or deposit, or in other words, interest on interest. It is the result of reinvesting interest, rather than paying it out, so that interest in the next period is then earned on the principal sum plus previously accumulated interest. Compound interest is standard in finance and economics.

**Future value** is the value of an asset at a specific date. It measures the nominal future sum of money that a given sum of money is "worth" at a specified time in the future assuming a certain interest rate, or more generally, rate of return; it is the present value multiplied by the accumulation function. The value does not include corrections for inflation or other factors that affect the true value of money in the future. This is used in time value of money calculations.

In science, ** e-folding** is the time interval in which an exponentially growing quantity increases by a factor of

In finance, **return** is a profit on an investment. It comprises any change in value of the investment, and/or cash flows which the investor receives from the investment, such as interest payments or dividends. It may be measured either in absolute terms or as a percentage of the amount invested. The latter is also called the holding period return.

The **doubling time** is the period of time required for a quantity to double in size or value. It is applied to population growth, inflation, resource extraction, consumption of goods, compound interest, the volume of malignant tumours, and many other things that tend to grow over time. When the relative growth rate is constant, the quantity undergoes exponential growth and has a constant doubling time or period, which can be calculated directly from the growth rate.

The **volatility tax** is a mathematical finance term, formalized by hedge fund manager Mark Spitznagel, describing the effect of large investment losses on compound returns. It has also been called “volatility drag”.

- ↑ Mark J. P. Anson; Frank J. Fabozzi; Frank J. Jones (3 December 2010).
*The Handbook of Traditional and Alternative Investment Vehicles: Investment Characteristics and Strategies*. John Wiley & Sons. pp. 489–. ISBN 978-1-118-00869-0. - ↑ root. "Compound Annual Growth Rate (CAGR) Definition | Investopedia".
*Investopedia*. Retrieved 2016-03-04. - ↑ Emily Chan (27 November 2012).
*Harvard Business School Confidential: Secrets of Success*. John Wiley & Sons. pp. 185–. ISBN 978-1-118-58344-9. - 1 2 3 "Compound Annual Growth Rate CAGR: Summary and Forum".
*www.12manage.com*. Retrieved 2019-05-02.

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