'Total return, when measuring performance, is the actual rate of return of an investment or a pool of investments over a given evaluation period. Total return includes interest, capital gains, dividends and distributions realized over a given period of time. Total return accounts for two categories of return: income including interest paid by fixed-income investments, distributions or dividends and capital appreciation, representing the change in the market price of an asset.'

Using this definition on our asset we see for example:- The total return over 5 years of Automatic Data Processing is 97.3%, which is lower, thus worse compared to the benchmark SPY (111.3%) in the same period.
- During the last 3 years, the total return is 50.6%, which is larger, thus better than the value of 39.3% from the benchmark.

'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. 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.'

Using this definition on our asset we see for example:- The annual performance (CAGR) over 5 years of Automatic Data Processing is 14.6%, which is smaller, thus worse compared to the benchmark SPY (16.2%) in the same period.
- During the last 3 years, the annual return (CAGR) is 14.7%, which is larger, thus better than the value of 11.7% from the benchmark.

'Volatility is a statistical measure of the dispersion of returns for a given security or market index. Volatility can either be measured by using the standard deviation or variance between returns from that same security or market index. Commonly, the higher the volatility, the riskier the security. In the securities markets, volatility is often associated with big swings in either direction. For example, when the stock market rises and falls more than one percent over a sustained period of time, it is called a 'volatile' market.'

Using this definition on our asset we see for example:- Looking at the 30 days standard deviation of 27.6% in the last 5 years of Automatic Data Processing, we see it is relatively larger, thus worse in comparison to the benchmark SPY (20.9%)
- During the last 3 years, the 30 days standard deviation is 22.2%, which is larger, thus worse than the value of 17.5% from the benchmark.

'The downside volatility is similar to the volatility, or standard deviation, but only takes losing/negative periods into account.'

Applying this definition to our asset in some examples:- Compared with the benchmark SPY (14.9%) in the period of the last 5 years, the downside volatility of 19.7% of Automatic Data Processing is larger, thus worse.
- Looking at downside risk in of 15.9% in the period of the last 3 years, we see it is relatively larger, thus worse in comparison to SPY (12.2%).

'The Sharpe ratio (also known as the Sharpe index, the Sharpe measure, and the reward-to-variability ratio) is a way to examine the performance of an investment by adjusting for its risk. The ratio measures the excess return (or risk premium) per unit of deviation in an investment asset or a trading strategy, typically referred to as risk, named after William F. Sharpe.'

Which means for our asset as example:- Looking at the ratio of return and volatility (Sharpe) of 0.44 in the last 5 years of Automatic Data Processing, we see it is relatively lower, thus worse in comparison to the benchmark SPY (0.66)
- During the last 3 years, the ratio of return and volatility (Sharpe) is 0.55, which is greater, thus better than the value of 0.53 from the benchmark.

'The Sortino ratio, a variation of the Sharpe ratio only factors in the downside, or negative volatility, rather than the total volatility used in calculating the Sharpe ratio. The theory behind the Sortino variation is that upside volatility is a plus for the investment, and it, therefore, should not be included in the risk calculation. Therefore, the Sortino ratio takes upside volatility out of the equation and uses only the downside standard deviation in its calculation instead of the total standard deviation that is used in calculating the Sharpe ratio.'

Applying this definition to our asset in some examples:- Looking at the downside risk / excess return profile of 0.61 in the last 5 years of Automatic Data Processing, we see it is relatively lower, thus worse in comparison to the benchmark SPY (0.92)
- During the last 3 years, the ratio of annual return and downside deviation is 0.76, which is higher, thus better than the value of 0.75 from the benchmark.

'Ulcer Index is a method for measuring investment risk that addresses the real concerns of investors, unlike the widely used standard deviation of return. UI is a measure of the depth and duration of drawdowns in prices from earlier highs. Using Ulcer Index instead of standard deviation can lead to very different conclusions about investment risk and risk-adjusted return, especially when evaluating strategies that seek to avoid major declines in portfolio value (market timing, dynamic asset allocation, hedge funds, etc.). The Ulcer Index was originally developed in 1987. Since then, it has been widely recognized and adopted by the investment community. According to Nelson Freeburg, editor of Formula Research, Ulcer Index is “perhaps the most fully realized statistical portrait of risk there is.'

Using this definition on our asset we see for example:- The Ulcer Index over 5 years of Automatic Data Processing is 12 , which is greater, thus worse compared to the benchmark SPY (9.32 ) in the same period.
- Compared with SPY (10 ) in the period of the last 3 years, the Ulcer Ratio of 11 is greater, thus worse.

'A maximum drawdown is the maximum loss from a peak to a trough of a portfolio, before a new peak is attained. Maximum Drawdown is an indicator of downside risk over a specified time period. It can be used both as a stand-alone measure or as an input into other metrics such as 'Return over Maximum Drawdown' and the Calmar Ratio. Maximum Drawdown is expressed in percentage terms.'

Applying this definition to our asset in some examples:- Looking at the maximum DrawDown of -39.5 days in the last 5 years of Automatic Data Processing, we see it is relatively smaller, thus worse in comparison to the benchmark SPY (-33.7 days)
- During the last 3 years, the maximum reduction from previous high is -21.8 days, which is larger, thus better than the value of -24.5 days from the benchmark.

'The Drawdown Duration is the length of any peak to peak period, or the time between new equity highs. The Max Drawdown Duration is the worst (the maximum/longest) amount of time an investment has seen between peaks (equity highs). Many assume Max DD Duration is the length of time between new highs during which the Max DD (magnitude) occurred. But that isn’t always the case. The Max DD duration is the longest time between peaks, period. So it could be the time when the program also had its biggest peak to valley loss (and usually is, because the program needs a long time to recover from the largest loss), but it doesn’t have to be'

Applying this definition to our asset in some examples:- Looking at the maximum days below previous high of 414 days in the last 5 years of Automatic Data Processing, we see it is relatively lower, thus better in comparison to the benchmark SPY (488 days)
- Looking at maximum days under water in of 414 days in the period of the last 3 years, we see it is relatively lower, thus better in comparison to SPY (488 days).

'The Drawdown Duration is the length of any peak to peak period, or the time between new equity highs. The Avg Drawdown Duration is the average amount of time an investment has seen between peaks (equity highs), or in other terms the average of time under water of all drawdowns. So in contrast to the Maximum duration it does not measure only one drawdown event but calculates the average of all.'

Using this definition on our asset we see for example:- The average time in days below previous high water mark over 5 years of Automatic Data Processing is 109 days, which is smaller, thus better compared to the benchmark SPY (124 days) in the same period.
- During the last 3 years, the average time in days below previous high water mark is 144 days, which is lower, thus better than the value of 179 days from the benchmark.

Historical returns have been extended using synthetic data.
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- Note that yearly returns do not equal the sum of monthly returns due to compounding.
- Performance results of Automatic Data Processing are hypothetical and do not account for slippage, fees or taxes.