Description

Automatic Data Processing, Inc. provides cloud-based human capital management solutions worldwide. It operates through two segments, Employer Services and Professional Employer Organization (PEO). The Employer Services segment offers strategic, cloud-based platforms, and human resources (HR) outsourcing solutions. Its offerings include payroll, benefits administration, talent management, HR management, workforce management, insurance, retirement, and compliance services. The PEO Services segment provides HR outsourcing solutions to small and mid-sized businesses through a co-employment model. This segment offers benefits package, protection and compliance, talent engagement, comprehensive outsourcing, and recruitment process outsourcing services. The company was founded in 1949 and is headquartered in Roseland, New Jersey.

Statistics (YTD)

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TotalReturn:

'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.'

Which means for our asset as example:
  • Compared with the benchmark SPY (93.6%) in the period of the last 5 years, the total return, or performance of 86.5% of Automatic Data Processing is lower, thus worse.
  • Looking at total return, or increase in value in of 58.7% in the period of the last 3 years, we see it is relatively higher, thus better in comparison to SPY (33.2%).

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.'

Applying this definition to our asset in some examples:
  • Looking at the annual return (CAGR) of 13.3% in the last 5 years of Automatic Data Processing, we see it is relatively lower, thus worse in comparison to the benchmark SPY (14.2%)
  • During the last 3 years, the compounded annual growth rate (CAGR) is 16.7%, which is higher, thus better than the value of 10% from the benchmark.

Volatility:

'In finance, volatility (symbol σ) is the degree of variation of a trading price series over time as measured by the standard deviation of logarithmic returns. Historic volatility measures a time series of past market prices. Implied volatility looks forward in time, being derived from the market price of a market-traded derivative (in particular, an option). Commonly, the higher the volatility, the riskier the security.'

Which means for our asset as example:
  • Looking at the historical 30 days volatility of 27.8% in the last 5 years of Automatic Data Processing, we see it is relatively greater, thus worse in comparison to the benchmark SPY (20.9%)
  • Compared with SPY (17.5%) in the period of the last 3 years, the 30 days standard deviation of 22.8% is higher, thus worse.

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.'

Using this definition on our asset we see for example:
  • Looking at the downside volatility of 20% in the last 5 years of Automatic Data Processing, we see it is relatively greater, thus worse in comparison to the benchmark SPY (15%)
  • Compared with SPY (12.2%) in the period of the last 3 years, the downside risk of 16.2% is larger, thus worse.

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.'

Applying this definition to our asset in some examples:
  • The risk / return profile (Sharpe) over 5 years of Automatic Data Processing is 0.39, which is lower, thus worse compared to the benchmark SPY (0.56) in the same period.
  • During the last 3 years, the Sharpe Ratio is 0.62, which is greater, thus better than the value of 0.43 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.'

Applying this definition to our asset in some examples:
  • The downside risk / excess return profile over 5 years of Automatic Data Processing is 0.54, which is lower, thus worse compared to the benchmark SPY (0.78) in the same period.
  • During the last 3 years, the downside risk / excess return profile is 0.88, which is higher, thus better than the value of 0.62 from the benchmark.

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.'

Which means for our asset as example:
  • The Downside risk index over 5 years of Automatic Data Processing is 12 , which is larger, thus worse compared to the benchmark SPY (9.33 ) in the same period.
  • Looking at Ulcer Index in of 11 in the period of the last 3 years, we see it is relatively greater, thus worse in comparison to SPY (10 ).

MaxDD:

'A maximum drawdown is the maximum loss from a peak to a trough of a portfolio, before a new peak is attained. Maximum Drawdown is an indicator of downside risk over a specified time period. It can be used both as a stand-alone measure or as an input into other metrics such as 'Return over Maximum Drawdown' and the Calmar Ratio. Maximum Drawdown is expressed in percentage terms.'

Applying this definition to our asset in some examples:
  • The maximum drop from peak to valley over 5 years of Automatic Data Processing is -39.5 days, which is smaller, thus worse compared to the benchmark SPY (-33.7 days) in the same period.
  • During the last 3 years, the maximum reduction from previous high is -21.8 days, which is larger, thus better than the value of -24.5 days from the benchmark.

MaxDuration:

'The Maximum 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. It is the length of time the account was in the Max Drawdown. A Max Drawdown measures a retrenchment from when an equity curve reaches a new high. It’s the maximum an account lost during that retrenchment. This method is applied because a valley can’t be measured until a new high occurs. Once the new high is reached, the percentage change from the old high to the bottom of the largest trough is recorded.'

Applying this definition to our asset in some examples:
  • Compared with the benchmark SPY (488 days) in the period of the last 5 years, the maximum time in days below previous high water mark of 303 days of Automatic Data Processing is smaller, thus better.
  • Looking at maximum days under water in of 303 days in the period of the last 3 years, we see it is relatively lower, thus better in comparison to SPY (488 days).

AveDuration:

'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:
  • The average days below previous high over 5 years of Automatic Data Processing is 78 days, which is lower, thus better compared to the benchmark SPY (123 days) in the same period.
  • Compared with SPY (180 days) in the period of the last 3 years, the average time in days below previous high water mark of 90 days is smaller, thus better.

Performance (YTD)

Historical returns have been extended using synthetic data.

Allocations ()

Allocations

Returns (%)

  • 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.