Automatic Data Processing (ADP)

TotalReturn:

'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.'

• The total return, or increase in value over 5 years of Automatic Data Processing is 58.1%, which is lower, thus worse compared to the benchmark SPY (80.3%) in the same period.
• During the last 3 years, the total return is 36.9%, which is lower, thus worse than the value of 88.1% 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 (12.6%) in the period of the last 5 years, the annual performance (CAGR) of 9.6% of Automatic Data Processing is smaller, thus worse.
• Compared with SPY (23.5%) in the period of the last 3 years, the annual performance (CAGR) of 11.1% is smaller, thus worse.

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 30 days standard deviation over 5 years of Automatic Data Processing is 23%, which is higher, thus worse compared to the benchmark SPY (17.1%) in the same period.
• Compared with SPY (15.2%) in the period of the last 3 years, the historical 30 days volatility of 22.2% is larger, thus worse.

DownVol:

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

• The downside risk over 5 years of Automatic Data Processing is 16.2%, which is higher, thus worse compared to the benchmark SPY (11.8%) in the same period.
• During the last 3 years, the downside deviation is 15.6%, which is greater, 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.'

• Compared with the benchmark SPY (0.59) in the period of the last 5 years, the ratio of return and volatility (Sharpe) of 0.31 of Automatic Data Processing is lower, thus worse.
• During the last 3 years, the ratio of return and volatility (Sharpe) is 0.39, which is lower, thus worse than the value of 1.38 from the benchmark.

Sortino:

'The Sortino ratio measures the risk-adjusted return of an investment asset, portfolio, or strategy. It is a modification of the Sharpe ratio but penalizes only those returns falling below a user-specified target or required rate of return, while the Sharpe ratio penalizes both upside and downside volatility equally. Though both ratios measure an investment's risk-adjusted return, they do so in significantly different ways that will frequently lead to differing conclusions as to the true nature of the investment's return-generating efficiency. The Sortino ratio is used as a way to compare the risk-adjusted performance of programs with differing risk and return profiles. In general, risk-adjusted returns seek to normalize the risk across programs and then see which has the higher return unit per risk.'

• Compared with the benchmark SPY (0.85) in the period of the last 5 years, the excess return divided by the downside deviation of 0.44 of Automatic Data Processing is lower, thus worse.
• During the last 3 years, the excess return divided by the downside deviation is 0.55, which is lower, thus worse than the value of 2.08 from the benchmark.

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.'

• The Ulcer Ratio over 5 years of Automatic Data Processing is 14 , which is greater, thus worse compared to the benchmark SPY (8.45 ) in the same period.
• Compared with SPY (3.2 ) in the period of the last 3 years, the Ulcer Ratio of 15 is higher, thus worse.

MaxDD:

'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.'

• The maximum drop from peak to valley over 5 years of Automatic Data Processing is -40.8 days, which is smaller, thus worse compared to the benchmark SPY (-24.5 days) in the same period.
• During the last 3 years, the maximum drop from peak to valley is -40.8 days, which is lower, thus worse than the value of -18.8 days from the benchmark.

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 time in days below previous high water mark over 5 years of Automatic Data Processing is 414 days, which is lower, thus better compared to the benchmark SPY (488 days) in the same period.
• During the last 3 years, the maximum time in days below previous high water mark is 346 days, which is greater, thus worse than the value of 87 days from the benchmark.

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.'

• The average days below previous high over 5 years of Automatic Data Processing is 138 days, which is larger, thus worse compared to the benchmark SPY (118 days) in the same period.
• Looking at average time in days below previous high water mark in of 101 days in the period of the last 3 years, we see it is relatively higher, thus worse in comparison to SPY (17 days).