'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.'

Using this definition on our asset we see for example:- Compared with the benchmark SPY (62.9%) in the period of the last 5 years, the total return, or increase in value of 109.4% of Automatic Data Processing is higher, thus better.
- Compared with SPY (39.8%) in the period of the last 3 years, the total return of 72.9% is higher, 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:- Looking at the compounded annual growth rate (CAGR) of 15.9% in the last 5 years of Automatic Data Processing, we see it is relatively higher, thus better in comparison to the benchmark SPY (10.3%)
- During the last 3 years, the annual return (CAGR) is 20.1%, which is greater, thus better than the value of 11.8% from the benchmark.

'Volatility is a rate at which the price of a security increases or decreases for a given set of returns. Volatility is measured by calculating the standard deviation of the annualized returns over a given period of time. It shows the range to which the price of a security may increase or decrease. Volatility measures the risk of a security. It is used in option pricing formula to gauge the fluctuations in the returns of the underlying assets. Volatility indicates the pricing behavior of the security and helps estimate the fluctuations that may happen in a short period of time.'

Using this definition on our asset we see for example:- Looking at the volatility of 19.6% in the last 5 years of Automatic Data Processing, we see it is relatively higher, thus worse in comparison to the benchmark SPY (13.5%)
- Looking at 30 days standard deviation in of 20.4% in the period of the last 3 years, we see it is relatively greater, thus worse in comparison to SPY (13.3%).

'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 13.9%, which is larger, thus worse compared to the benchmark SPY (9.8%) in the same period.
- Looking at downside deviation in of 14.4% in the period of the last 3 years, we see it is relatively larger, thus worse in comparison to SPY (9.8%).

'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 0.69 in the last 5 years of Automatic Data Processing, we see it is relatively larger, thus better in comparison to the benchmark SPY (0.58)
- Looking at Sharpe Ratio in of 0.86 in the period of the last 3 years, we see it is relatively higher, thus better in comparison to SPY (0.71).

'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.'

Which means for our asset as example:- Compared with the benchmark SPY (0.79) in the period of the last 5 years, the excess return divided by the downside deviation of 0.97 of Automatic Data Processing is greater, thus better.
- Compared with SPY (0.96) in the period of the last 3 years, the ratio of annual return and downside deviation of 1.22 is greater, thus better.

'The Ulcer Index is a technical indicator that measures downside risk, in terms of both the depth and duration of price declines. The index increases in value as the price moves farther away from a recent high and falls as the price rises to new highs. The indicator is usually calculated over a 14-day period, with the Ulcer Index showing the percentage drawdown a trader can expect from the high over that period. The greater the value of the Ulcer Index, the longer it takes for a stock to get back to the former high.'

Applying this definition to our asset in some examples:- The Downside risk index over 5 years of Automatic Data Processing is 5.51 , which is greater, thus worse compared to the benchmark SPY (3.98 ) in the same period.
- During the last 3 years, the Downside risk index is 5.06 , which is higher, thus worse than the value of 4.12 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.'

Applying this definition to our asset in some examples:- The maximum DrawDown over 5 years of Automatic Data Processing is -19.2 days, which is greater, thus better compared to the benchmark SPY (-19.3 days) in the same period.
- During the last 3 years, the maximum drop from peak to valley is -19.2 days, which is higher, thus better than the value of -19.3 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) in days.'

Using this definition on our asset we see for example:- Looking at the maximum days under water of 163 days in the last 5 years of Automatic Data Processing, we see it is relatively lower, thus better in comparison to the benchmark SPY (187 days)
- Compared with SPY (139 days) in the period of the last 3 years, the maximum time in days below previous high water mark of 95 days is lower, thus better.

'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:- Looking at the average days under water of 38 days in the last 5 years of Automatic Data Processing, we see it is relatively lower, thus better in comparison to the benchmark SPY (42 days)
- During the last 3 years, the average time in days below previous high water mark is 28 days, which is smaller, thus better than the value of 37 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.