Description of Automatic Data Processing

Automatic Data Processing, Inc. - Common Stock

Statistics of Automatic Data Processing (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.'

Using this definition on our asset we see for example:
  • The total return, or increase in value over 5 years of Automatic Data Processing is 126.4%, which is larger, thus better compared to the benchmark SPY (67.2%) in the same period.
  • Compared with SPY (50.7%) in the period of the last 3 years, the total return of 92.6% is greater, thus better.

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.'

Using this definition on our asset we see for example:
  • The compounded annual growth rate (CAGR) over 5 years of Automatic Data Processing is 17.8%, which is larger, thus better compared to the benchmark SPY (10.8%) in the same period.
  • Compared with SPY (14.7%) in the period of the last 3 years, the compounded annual growth rate (CAGR) of 24.5% is larger, thus better.

Volatility:

'Volatility is a rate at which the price of a security increases or decreases for a given set of returns. Volatility is measured by calculating the standard deviation of the annualized returns over a given period of time. It shows the range to which the price of a security may increase or decrease. Volatility measures the risk of a security. It is used in option pricing formula to gauge the fluctuations in the returns of the underlying assets. Volatility indicates the pricing behavior of the security and helps estimate the fluctuations that may happen in a short period of time.'

Applying this definition to our asset in some examples:
  • The historical 30 days volatility over 5 years of Automatic Data Processing is 19.4%, which is greater, thus worse compared to the benchmark SPY (13.5%) in the same period.
  • During the last 3 years, the volatility is 20.2%, which is larger, thus worse than the value of 12.8% from the benchmark.

DownVol:

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

Applying this definition to our asset in some examples:
  • Compared with the benchmark SPY (14.8%) in the period of the last 5 years, the downside volatility of 21.4% of Automatic Data Processing is larger, thus worse.
  • Compared with SPY (14.7%) in the period of the last 3 years, the downside volatility of 22.7% 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.'

Using this definition on our asset we see for example:
  • Compared with the benchmark SPY (0.62) in the period of the last 5 years, the risk / return profile (Sharpe) of 0.79 of Automatic Data Processing is higher, thus better.
  • During the last 3 years, the Sharpe Ratio is 1.09, which is greater, thus better than the value of 0.95 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.'

Using this definition on our asset we see for example:
  • Compared with the benchmark SPY (0.56) in the period of the last 5 years, the ratio of annual return and downside deviation of 0.71 of Automatic Data Processing is greater, thus better.
  • During the last 3 years, the excess return divided by the downside deviation is 0.97, which is larger, thus better than the value of 0.83 from the benchmark.

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.'

Using this definition on our asset we see for example:
  • Compared with the benchmark SPY (3.99 ) in the period of the last 5 years, the Ulcer Index of 5.51 of Automatic Data Processing is higher, thus worse.
  • Compared with SPY (4.09 ) in the period of the last 3 years, the Downside risk index of 5.1 is higher, thus worse.

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.'

Using this definition on our asset we see for example:
  • The maximum DrawDown over 5 years of Automatic Data Processing is -19.2 days, which is higher, thus better compared to the benchmark SPY (-19.3 days) in the same period.
  • Looking at maximum drop from peak to valley in of -19.2 days in the period of the last 3 years, we see it is relatively larger, thus better in comparison to SPY (-19.3 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) in days.'

Which means for our asset as example:
  • 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 smaller, 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 smaller, thus better.

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.'

Using this definition on our asset we see for example:
  • Compared with the benchmark SPY (42 days) in the period of the last 5 years, the average days under water of 37 days of Automatic Data Processing is smaller, thus better.
  • During the last 3 years, the average time in days below previous high water mark is 26 days, which is lower, thus better than the value of 36 days from the benchmark.

Performance of Automatic Data Processing (YTD)

Historical returns have been extended using synthetic data.

Allocations of Automatic Data Processing
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Allocations

Returns of Automatic Data Processing (%)

  • 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.