Automatic Data Processing (ADP)

TotalReturn:

'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.'

• The total return, or performance over 5 years of Automatic Data Processing is 15.6%, which is lower, thus worse compared to the benchmark SPY (82.2%) in the same period.
• During the last 3 years, the total return, or increase in value is -1.6%, which is lower, thus worse than the value of 78.3% from the benchmark.

CAGR:

'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.'

• Compared with the benchmark SPY (12.8%) in the period of the last 5 years, the annual return (CAGR) of 3% of Automatic Data Processing is smaller, thus worse.
• Looking at annual return (CAGR) in of -0.5% in the period of the last 3 years, we see it is relatively smaller, thus worse in comparison to SPY (21.3%).

Volatility:

'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.'

• The historical 30 days volatility over 5 years of Automatic Data Processing is 21.5%, which is larger, thus worse compared to the benchmark SPY (17.1%) in the same period.
• Looking at 30 days standard deviation in of 19.7% in the period of the last 3 years, we see it is relatively larger, thus worse in comparison to SPY (15.2%).

DownVol:

'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.'

• The downside risk over 5 years of Automatic Data Processing is 15.8%, which is greater, thus worse compared to the benchmark SPY (11.8%) in the same period.
• During the last 3 years, the downside risk is 14.8%, which is larger, thus worse than the value of 10.1% from the benchmark.

Sharpe:

'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.'

• The Sharpe Ratio over 5 years of Automatic Data Processing is 0.02, which is lower, thus worse compared to the benchmark SPY (0.6) in the same period.
• Compared with SPY (1.24) in the period of the last 3 years, the ratio of return and volatility (Sharpe) of -0.15 is lower, thus worse.

Sortino:

'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.'

• Compared with the benchmark SPY (0.87) in the period of the last 5 years, the downside risk / excess return profile of 0.03 of Automatic Data Processing is smaller, thus worse.
• Looking at ratio of annual return and downside deviation in of -0.2 in the period of the last 3 years, we see it is relatively lower, thus worse in comparison to SPY (1.86).

Ulcer:

'The ulcer index is a stock market risk measure or technical analysis indicator devised by Peter Martin in 1987, and published by him and Byron McCann in their 1989 book The Investors Guide to Fidelity Funds. It's designed as a measure of volatility, but only volatility in the downward direction, i.e. the amount of drawdown or retracement occurring over a period. Other volatility measures like standard deviation treat up and down movement equally, but a trader doesn't mind upward movement, it's the downside that causes stress and stomach ulcers that the index's name suggests.'

• Looking at the Ulcer Ratio of 12 in the last 5 years of Automatic Data Processing, we see it is relatively larger, thus worse in comparison to the benchmark SPY (8.45 )
• Looking at Ulcer Ratio in of 12 in the period of the last 3 years, we see it is relatively larger, thus worse in comparison to SPY (3.5 ).

MaxDD:

'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.'

• Looking at the maximum reduction from previous high of -40.8 days in the last 5 years of Automatic Data Processing, we see it is relatively smaller, thus worse in comparison to the benchmark SPY (-24.5 days)
• Looking at maximum drop from peak to valley in of -40.8 days in the period of the last 3 years, we see it is relatively lower, thus worse in comparison to SPY (-18.8 days).

MaxDuration:

'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'

• The maximum days below previous high over 5 years of Automatic Data Processing is 414 days, which is smaller, thus better compared to the benchmark SPY (488 days) in the same period.
• Compared with SPY (87 days) in the period of the last 3 years, the maximum days below previous high of 216 days is larger, thus worse.

AveDuration:

'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.'

• Looking at the average days under water of 110 days in the last 5 years of Automatic Data Processing, we see it is relatively smaller, thus better in comparison to the benchmark SPY (119 days)
• Compared with SPY (20 days) in the period of the last 3 years, the average time in days below previous high water mark of 57 days is higher, thus worse.