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A financial term known as the compound annual growth rate (CAGR) calculates the average yearly rate of return on an investment over a certain time period longer than one year. The compound annual growth rate (CAGR), provided earnings were reinvested at the end of each year of the investment's life, is the rate of return necessary for an investment to increase in value from its starting balance to its final balance.
CAGR is calculated by using the following formula:
CAGR = (Ending Value / Beginning Value)^(1 / n) - 1
where n is the number of years in the period.
For example, if an investment of $10,000 grows to $15,000 in three years, the CAGR of the investment is:
CAGR = ($15,000 / $10,000)^(1 / 3) - 1
CAGR = 0.1467 - 1
CAGR = 0.1467 or 14.67%
CAGR is a valuable indicator of an investment's growth and performance over time since it eliminates the volatility and variations of periodic returns and offers a steady and comparable rate of return. The CAGR can be used to compare the returns of investments with various time horizons or to predict an investment's predicted future returns based on historical data.
CAGR has several restrictions and disadvantages, though. One of its disadvantages is that it expects the investment will increase at a steady and constant rate, which might not accurately reflect the state of the market or the performance of the investment. As it doesn't take into consideration the variance or standard deviation of the periodic returns, it also disregards the investment's risk and volatility. The time and frequency of cash flows, such as dividends, interest, or withdrawals, which may have an impact on the investment's real return, are also not taken into account.
According to the choice of the beginning and ending values or the period of time, some of the disadvantages include the possibility that it may be deceptive or inaccurate, as it may exaggerate or understate the genuine development and success of the investment. Additionally, because it can be influenced by outliers or extremely high or low values in the data set, it can be changed or distorted.
