'The total return on a portfolio of investments takes into account not only the capital appreciation on the portfolio, but also the income received on the portfolio. The income typically consists of interest, dividends, and securities lending fees. This contrasts with the price return, which takes into account only the capital gain on an investment.'

Applying this definition to our asset in some examples:- Compared with the benchmark SPY (67.8%) in the period of the last 5 years, the total return, or performance of 78.3% of Automatic Data Processing is higher, thus better.
- Compared with SPY (44.5%) in the period of the last 3 years, the total return, or performance of 52.5% is greater, thus better.

'The compound annual growth rate isn't a true return rate, but rather a representational figure. It is essentially a number that describes the rate at which an investment would have grown if it had grown the same rate every year and the profits were reinvested at the end of each year. In reality, this sort of performance is unlikely. However, CAGR can be used to smooth returns so that they may be more easily understood when compared to alternative investments.'

Using this definition on our asset we see for example:- The annual return (CAGR) over 5 years of Automatic Data Processing is 12.3%, which is larger, thus better compared to the benchmark SPY (10.9%) in the same period.
- During the last 3 years, the compounded annual growth rate (CAGR) is 15.1%, which is larger, thus better than the value of 13.1% 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.'

Applying this definition to our asset in some examples:- The historical 30 days volatility over 5 years of Automatic Data Processing is 28.1%, which is higher, thus worse compared to the benchmark SPY (21.4%) in the same period.
- Looking at 30 days standard deviation in of 24.6% in the period of the last 3 years, we see it is relatively higher, thus worse in comparison to SPY (18.8%).

'Risk measures typically quantify the downside risk, whereas the standard deviation (an example of a deviation risk measure) measures both the upside and downside risk. Specifically, downside risk in our definition is the semi-deviation, that is the standard deviation of all negative returns.'

Which means for our asset as example:- Compared with the benchmark SPY (15.4%) in the period of the last 5 years, the downside deviation of 20.1% of Automatic Data Processing is larger, thus worse.
- Looking at downside risk in of 17.5% in the period of the last 3 years, we see it is relatively larger, thus worse in comparison to SPY (13.3%).

'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.'

Using this definition on our asset we see for example:- Looking at the ratio of return and volatility (Sharpe) of 0.35 in the last 5 years of Automatic Data Processing, we see it is relatively lower, thus worse in comparison to the benchmark SPY (0.39)
- During the last 3 years, the ratio of return and volatility (Sharpe) is 0.51, which is lower, thus worse than the value of 0.56 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.'

Using this definition on our asset we see for example:- Compared with the benchmark SPY (0.55) in the period of the last 5 years, the ratio of annual return and downside deviation of 0.49 of Automatic Data Processing is lower, thus worse.
- Looking at downside risk / excess return profile in of 0.72 in the period of the last 3 years, we see it is relatively lower, thus worse in comparison to SPY (0.79).

'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:- Compared with the benchmark SPY (9.46 ) in the period of the last 5 years, the Ulcer Index of 11 of Automatic Data Processing is greater, thus worse.
- During the last 3 years, the Downside risk index is 10 , which is larger, thus worse than the value of 10 from the benchmark.

'Maximum drawdown measures the loss in any losing period during a fund’s investment record. It is defined as the percent retrenchment from a fund’s peak value to the fund’s valley value. The drawdown is in effect from the time the fund’s retrenchment begins until a new fund high is reached. The maximum drawdown encompasses both the period from the fund’s peak to the fund’s valley (length), and the time from the fund’s valley to a new fund high (recovery). It measures the largest percentage drawdown that has occurred in any fund’s data record.'

Using this definition on our asset we see for example:- The maximum drop from peak to valley over 5 years of Automatic Data Processing is -39.5 days, which is lower, thus worse compared to the benchmark SPY (-33.7 days) in the same period.
- Compared with SPY (-24.5 days) in the period of the last 3 years, the maximum DrawDown of -21.4 days is greater, thus better.

'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:- The maximum days under water over 5 years of Automatic Data Processing is 210 days, which is lower, thus better compared to the benchmark SPY (352 days) in the same period.
- During the last 3 years, the maximum days below previous high is 150 days, which is smaller, thus better than the value of 352 days from the benchmark.

'The Average 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. 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 time in days below previous high water mark over 5 years of Automatic Data Processing is 50 days, which is smaller, thus better compared to the benchmark SPY (78 days) in the same period.
- Looking at average time in days below previous high water mark in of 44 days in the period of the last 3 years, we see it is relatively lower, thus better in comparison to SPY (102 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.