'Total return is the amount of value an investor earns from a security over a specific period, typically one year, when all distributions are reinvested. Total return is expressed as a percentage of the amount invested. For example, a total return of 20% means the security increased by 20% of its original value due to a price increase, distribution of dividends (if a stock), coupons (if a bond) or capital gains (if a fund). Total return is a strong measure of an investment’s overall performance.'

Applying this definition to our asset in some examples:- Compared with the benchmark SPY (78.4%) in the period of the last 5 years, the total return, or performance of 135.1% of Automatic Data Processing is higher, thus better.
- Looking at total return in of 37.7% in the period of the last 3 years, we see it is relatively smaller, thus worse in comparison to SPY (44.1%).

'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:- Looking at the annual performance (CAGR) of 18.6% in the last 5 years of Automatic Data Processing, we see it is relatively greater, thus better in comparison to the benchmark SPY (12.3%)
- Looking at compounded annual growth rate (CAGR) in of 11.2% in the period of the last 3 years, we see it is relatively lower, thus worse in comparison to SPY (12.9%).

'In finance, volatility (symbol σ) is the degree of variation of a trading price series over time as measured by the standard deviation of logarithmic returns. Historic volatility measures a time series of past market prices. Implied volatility looks forward in time, being derived from the market price of a market-traded derivative (in particular, an option). Commonly, the higher the volatility, the riskier the security.'

Applying this definition to our asset in some examples:- The 30 days standard deviation over 5 years of Automatic Data Processing is 27.5%, which is higher, thus worse compared to the benchmark SPY (19.9%) in the same period.
- Compared with SPY (23.1%) in the period of the last 3 years, the historical 30 days volatility of 31% is greater, thus worse.

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

Using this definition on our asset we see for example:- Compared with the benchmark SPY (14.6%) in the period of the last 5 years, the downside deviation of 19.6% of Automatic Data Processing is higher, thus worse.
- During the last 3 years, the downside risk is 22.5%, which is higher, thus worse than the value of 16.9% from the benchmark.

'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.'

Applying this definition to our asset in some examples:- The ratio of return and volatility (Sharpe) over 5 years of Automatic Data Processing is 0.59, which is larger, thus better compared to the benchmark SPY (0.49) in the same period.
- During the last 3 years, the risk / return profile (Sharpe) is 0.28, which is lower, thus worse than the value of 0.45 from the benchmark.

'The Sortino ratio improves upon the Sharpe ratio by isolating downside volatility from total volatility by dividing excess return by the downside deviation. The Sortino ratio is a variation of the Sharpe ratio that differentiates harmful volatility from total overall volatility by using the asset's standard deviation of negative asset returns, called downside deviation. The Sortino ratio takes the asset's return and subtracts the risk-free rate, and then divides that amount by the asset's downside deviation. The ratio was named after Frank A. Sortino.'

Using this definition on our asset we see for example:- Looking at the ratio of annual return and downside deviation of 0.82 in the last 5 years of Automatic Data Processing, we see it is relatively greater, thus better in comparison to the benchmark SPY (0.67)
- Looking at downside risk / excess return profile in of 0.39 in the period of the last 3 years, we see it is relatively smaller, thus worse in comparison to SPY (0.62).

'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.'

Applying this definition to our asset in some examples:- Looking at the Ulcer Index of 9.69 in the last 5 years of Automatic Data Processing, we see it is relatively higher, thus worse in comparison to the benchmark SPY (6.16 )
- Compared with SPY (6.87 ) in the period of the last 3 years, the Ulcer Ratio of 12 is greater, thus worse.

'Maximum drawdown is defined as the peak-to-trough decline of an investment during a specific period. It is usually quoted as a percentage of the peak value. The maximum drawdown can be calculated based on absolute returns, in order to identify strategies that suffer less during market downturns, such as low-volatility strategies. However, the maximum drawdown can also be calculated based on returns relative to a benchmark index, for identifying strategies that show steady outperformance over time.'

Applying this definition to our asset in some examples:- Looking at the maximum drop from peak to valley 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)
- Looking at maximum drop from peak to valley in of -39.5 days in the period of the last 3 years, we see it is relatively lower, thus worse in comparison to SPY (-33.7 days).

'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) in days.'

Applying this definition to our asset in some examples:- Compared with the benchmark SPY (139 days) in the period of the last 5 years, the maximum days below previous high of 210 days of Automatic Data Processing is larger, thus worse.
- Compared with SPY (119 days) in the period of the last 3 years, the maximum time in days below previous high water mark of 210 days is higher, thus worse.

'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.'

Which means for our asset as example:- The average days under water over 5 years of Automatic Data Processing is 43 days, which is higher, thus worse compared to the benchmark SPY (35 days) in the same period.
- During the last 3 years, the average days under water is 51 days, which is greater, thus worse than the value of 27 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, do not account for slippage, fees or taxes, and are based on backtesting, which has many inherent limitations, some of which are described in our Terms of Use.