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:

'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.'

Using this definition on our asset we see for example:
  • The total return over 5 years of Automatic Data Processing is 110.6%, which is greater, thus better compared to the benchmark SPY (63%) in the same period.
  • Looking at total return, or performance in of 37.8% in the period of the last 3 years, we see it is relatively larger, thus better in comparison to SPY (33.5%).

CAGR:

'Compound annual growth rate (CAGR) is a business and investing specific term for the geometric progression ratio that provides a constant rate of return over the time period. CAGR is not an accounting term, but it is often used to describe some element of the business, for example revenue, units delivered, registered users, etc. CAGR dampens the effect of volatility of periodic returns that can render arithmetic means irrelevant. It is particularly useful to compare growth rates from various data sets of common domain such as revenue growth of companies in the same industry.'

Which means for our asset as example:
  • Compared with the benchmark SPY (10.3%) in the period of the last 5 years, the annual performance (CAGR) of 16.1% of Automatic Data Processing is greater, thus better.
  • During the last 3 years, the annual performance (CAGR) is 11.3%, which is higher, thus better than the value of 10.1% from the benchmark.

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.'

Which means for our asset as example:
  • The 30 days standard deviation over 5 years of Automatic Data Processing is 28.4%, which is larger, thus worse compared to the benchmark SPY (21.6%) in the same period.
  • During the last 3 years, the volatility is 32.5%, which is larger, thus worse than the value of 25.1% 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.'

Using this definition on our asset we see for example:
  • Compared with the benchmark SPY (15.6%) in the period of the last 5 years, the downside risk of 20.2% of Automatic Data Processing is greater, thus worse.
  • Looking at downside risk in of 23.2% in the period of the last 3 years, we see it is relatively higher, thus worse in comparison to SPY (18.1%).

Sharpe:

'The Sharpe ratio is the measure of risk-adjusted return of a financial portfolio. Sharpe ratio is a measure of excess portfolio return over the risk-free rate relative to its standard deviation. Normally, the 90-day Treasury bill rate is taken as the proxy for risk-free rate. A portfolio with a higher Sharpe ratio is considered superior relative to its peers. The measure was named after William F Sharpe, a Nobel laureate and professor of finance, emeritus at Stanford University.'

Applying this definition to our asset in some examples:
  • Compared with the benchmark SPY (0.36) in the period of the last 5 years, the Sharpe Ratio of 0.48 of Automatic Data Processing is larger, thus better.
  • Looking at Sharpe Ratio in of 0.27 in the period of the last 3 years, we see it is relatively lower, thus worse in comparison to SPY (0.3).

Sortino:

'The Sortino ratio improves upon the Sharpe ratio by isolating downside volatility from total volatility by dividing excess return by the downside deviation. The Sortino ratio is a variation of the Sharpe ratio that differentiates harmful volatility from total overall volatility by using the asset's standard deviation of negative asset returns, called downside deviation. The Sortino ratio takes the asset's return and subtracts the risk-free rate, and then divides that amount by the asset's downside deviation. The ratio was named after Frank A. Sortino.'

Applying this definition to our asset in some examples:
  • Compared with the benchmark SPY (0.5) in the period of the last 5 years, the excess return divided by the downside deviation of 0.67 of Automatic Data Processing is greater, thus better.
  • Looking at ratio of annual return and downside deviation in of 0.38 in the period of the last 3 years, we see it is relatively smaller, thus worse in comparison to SPY (0.42).

Ulcer:

'Ulcer Index is a method for measuring investment risk that addresses the real concerns of investors, unlike the widely used standard deviation of return. UI is a measure of the depth and duration of drawdowns in prices from earlier highs. Using Ulcer Index instead of standard deviation can lead to very different conclusions about investment risk and risk-adjusted return, especially when evaluating strategies that seek to avoid major declines in portfolio value (market timing, dynamic asset allocation, hedge funds, etc.). The Ulcer Index was originally developed in 1987. Since then, it has been widely recognized and adopted by the investment community. According to Nelson Freeburg, editor of Formula Research, Ulcer Index is “perhaps the most fully realized statistical portrait of risk there is.'

Which means for our asset as example:
  • Looking at the Downside risk index of 10 in the last 5 years of Automatic Data Processing, we see it is relatively higher, thus worse in comparison to the benchmark SPY (8.88 )
  • During the last 3 years, the Ulcer Ratio is 12 , which is higher, thus worse than the value of 11 from the benchmark.

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.'

Which means for our asset as example:
  • The maximum reduction from previous high over 5 years of Automatic Data Processing is -39.5 days, which is lower, thus worse compared to the benchmark SPY (-33.7 days) in the same period.
  • Compared with SPY (-33.7 days) in the period of the last 3 years, the maximum DrawDown of -39.5 days is lower, thus worse.

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) in days.'

Applying this definition to our asset in some examples:
  • The maximum days below previous high over 5 years of Automatic Data Processing is 212 days, which is lower, thus better compared to the benchmark SPY (273 days) in the same period.
  • Looking at maximum days below previous high in of 212 days in the period of the last 3 years, we see it is relatively smaller, thus better in comparison to SPY (273 days).

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.'

Which means for our asset as example:
  • The average time in days below previous high water mark over 5 years of Automatic Data Processing is 46 days, which is lower, thus better compared to the benchmark SPY (57 days) in the same period.
  • Compared with SPY (73 days) in the period of the last 3 years, the average time in days below previous high water mark of 59 days is lower, 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.