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.'

• Looking at the total return, or increase in value of 161.5% in the last 5 years of Automatic Data Processing, we see it is relatively larger, thus better in comparison to the benchmark SPY (66.1%)
• During the last 3 years, the total return, or performance is 85.5%, which is greater, thus better than the value of 46.2% from the benchmark.

CAGR:

'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.'

• Compared with the benchmark SPY (10.7%) in the period of the last 5 years, the annual return (CAGR) of 21.2% of Automatic Data Processing is higher, thus better.
• Looking at compounded annual growth rate (CAGR) in of 22.9% in the period of the last 3 years, we see it is relatively larger, thus better in comparison to SPY (13.5%).

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.'

• Looking at the historical 30 days volatility of 19.1% in the last 5 years of Automatic Data Processing, we see it is relatively higher, thus worse in comparison to the benchmark SPY (13.4%)
• During the last 3 years, the volatility is 19.7%, which is higher, thus worse than the value of 12.3% from the benchmark.

DownVol:

'Downside risk is the financial risk associated with losses. That is, it is the risk of the actual return being below the expected return, or the uncertainty about the magnitude of that difference. 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.'

• Compared with the benchmark SPY (14.6%) in the period of the last 5 years, the downside volatility of 20.8% of Automatic Data Processing is larger, thus worse.
• Looking at downside deviation in of 22% in the period of the last 3 years, we see it is relatively greater, thus worse in comparison to SPY (13.9%).

Sharpe:

'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.'

• Compared with the benchmark SPY (0.61) in the period of the last 5 years, the ratio of return and volatility (Sharpe) of 0.98 of Automatic Data Processing is higher, thus better.
• During the last 3 years, the risk / return profile (Sharpe) is 1.04, which is greater, thus better than the value of 0.9 from the benchmark.

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 (0.56) in the period of the last 5 years, the excess return divided by the downside deviation of 0.9 of Automatic Data Processing is greater, thus better.
• Looking at ratio of annual return and downside deviation in of 0.93 in the period of the last 3 years, we see it is relatively greater, thus better in comparison to SPY (0.8).

Ulcer:

'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.'

• Compared with the benchmark SPY (3.99 ) in the period of the last 5 years, the Ulcer Index of 5.36 of Automatic Data Processing is greater, thus worse.
• Looking at Downside risk index in of 5.31 in the period of the last 3 years, we see it is relatively greater, thus worse in comparison to SPY (4.04 ).

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.'

• Compared with the benchmark SPY (-19.3 days) in the period of the last 5 years, the maximum reduction from previous high of -19.2 days of Automatic Data Processing is larger, thus better.
• Compared with SPY (-19.3 days) in the period of the last 3 years, the maximum reduction from previous high of -19.2 days is higher, thus better.

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'

• Looking at the maximum time in days below previous high water mark 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 days below previous high of 95 days is lower, thus better.

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 time in days below previous high water mark of 36 days in the last 5 years of Automatic Data Processing, we see it is relatively smaller, thus better in comparison to the benchmark SPY (41 days)
• During the last 3 years, the average days below previous high is 28 days, which is smaller, thus better than the value of 36 days from the benchmark.