'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.'

Which means for our asset as example:- Looking at the total return of 144.4% in the last 5 years of Automatic Data Processing, we see it is relatively greater, thus better in comparison to the benchmark SPY (115.8%)
- Compared with SPY (57%) in the period of the last 3 years, the total return of 58.8% is higher, thus better.

'The compound annual growth rate (CAGR) is a useful measure of growth over multiple time periods. It can be thought of as the growth rate that gets you from the initial investment value to the ending investment value if you assume that the investment has been compounding over the time period.'

Using this definition on our asset we see for example:- The annual return (CAGR) over 5 years of Automatic Data Processing is 19.6%, which is higher, thus better compared to the benchmark SPY (16.7%) in the same period.
- During the last 3 years, the annual return (CAGR) is 16.7%, which is higher, thus better than the value of 16.3% from the benchmark.

'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.'

Which means for our asset as example:- Looking at the volatility of 26.7% in the last 5 years of Automatic Data Processing, we see it is relatively larger, thus worse in comparison to the benchmark SPY (18.8%)
- During the last 3 years, the historical 30 days volatility is 30.6%, which is greater, thus worse than the value of 22.5% from the benchmark.

'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:- The downside risk over 5 years of Automatic Data Processing is 19%, which is larger, thus worse compared to the benchmark SPY (13.7%) in the same period.
- Looking at downside volatility in of 21.9% in the period of the last 3 years, we see it is relatively higher, thus worse in comparison to SPY (16.4%).

'The Sharpe ratio was developed by Nobel laureate William F. Sharpe, and is used to help investors understand the return of an investment compared to its risk. The ratio is the average return earned in excess of the risk-free rate per unit of volatility or total risk. Subtracting the risk-free rate from the mean return allows an investor to better isolate the profits associated with risk-taking activities. One intuition of this calculation is that a portfolio engaging in 'zero risk' investments, such as the purchase of U.S. Treasury bills (for which the expected return is the risk-free rate), has a Sharpe ratio of exactly zero. Generally, the greater the value of the Sharpe ratio, the more attractive the risk-adjusted return.'

Which means for our asset as example:- Compared with the benchmark SPY (0.75) in the period of the last 5 years, the ratio of return and volatility (Sharpe) of 0.64 of Automatic Data Processing is lower, thus worse.
- Compared with SPY (0.61) in the period of the last 3 years, the ratio of return and volatility (Sharpe) of 0.46 is lower, thus worse.

'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.'

Which means for our asset as example:- Compared with the benchmark SPY (1.04) in the period of the last 5 years, the excess return divided by the downside deviation of 0.9 of Automatic Data Processing is lower, thus worse.
- During the last 3 years, the downside risk / excess return profile is 0.65, which is lower, thus worse than the value of 0.84 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.'

Which means for our asset as example:- Looking at the Ulcer Ratio of 9.16 in the last 5 years of Automatic Data Processing, we see it is relatively greater, thus worse in comparison to the benchmark SPY (5.58 )
- Looking at Downside risk index in of 11 in the period of the last 3 years, we see it is relatively larger, thus worse in comparison to SPY (6.83 ).

'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.'

Which means for our asset as example:- Compared with the benchmark SPY (-33.7 days) in the period of the last 5 years, the maximum drop from peak to valley of -39.5 days of Automatic Data Processing is lower, thus worse.
- Compared with SPY (-33.7 days) in the period of the last 3 years, the maximum reduction from previous high of -39.5 days is lower, thus worse.

'The Maximum Drawdown Duration is an extension of the Maximum Drawdown. However, this metric does not explain the drawdown in dollars or percentages, rather in days, weeks, or months. It is the length of time the account was in the Max Drawdown. A Max Drawdown measures a retrenchment from when an equity curve reaches a new high. It’s the maximum an account lost during that retrenchment. This method is applied because a valley can’t be measured until a new high occurs. Once the new high is reached, the percentage change from the old high to the bottom of the largest trough is recorded.'

Using this definition on our asset we see for example:- Looking at the maximum days below previous high of 212 days in the last 5 years of Automatic Data Processing, we see it is relatively higher, thus worse in comparison to the benchmark SPY (139 days)
- During the last 3 years, the maximum time in days below previous high water mark is 212 days, which is higher, thus worse than the value of 139 days from the benchmark.

'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.'

Applying this definition to our asset in some examples:- The average days under water over 5 years of Automatic Data Processing is 42 days, which is higher, thus worse compared to the benchmark SPY (33 days) in the same period.
- Looking at average time in days below previous high water mark in of 51 days in the period of the last 3 years, we see it is relatively higher, thus worse in comparison to SPY (35 days).

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.