Description of Automatic Data Processing

Automatic Data Processing, Inc. - Common Stock

Statistics of Automatic Data Processing (YTD)

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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.'

Which means for our asset as example:
  • Looking at the total return, or performance of 156.3% in the last 5 years of Automatic Data Processing, we see it is relatively larger, thus better in comparison to the benchmark SPY (66.2%)
  • During the last 3 years, the total return is 85%, which is larger, thus better than the value of 45.7% 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.'

Which means for our asset as example:
  • Compared with the benchmark SPY (10.7%) in the period of the last 5 years, the compounded annual growth rate (CAGR) of 20.7% of Automatic Data Processing is greater, thus better.
  • Looking at compounded annual growth rate (CAGR) in of 22.8% in the period of the last 3 years, we see it is relatively greater, thus better in comparison to SPY (13.4%).

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.'

Applying this definition to our asset in some examples:
  • The volatility over 5 years of Automatic Data Processing is 18.8%, which is higher, thus worse compared to the benchmark SPY (13.3%) in the same period.
  • During the last 3 years, the historical 30 days volatility is 19.6%, which is larger, thus worse than the value of 12.5% 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.'

Which means for our asset as example:
  • Looking at the downside volatility of 20.4% in the last 5 years of Automatic Data Processing, we see it is relatively larger, thus worse in comparison to the benchmark SPY (14.6%)
  • Compared with SPY (14.1%) in the period of the last 3 years, the downside risk of 21.6% is larger, thus worse.

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.'

Which means for our asset as example:
  • Compared with the benchmark SPY (0.62) in the period of the last 5 years, the ratio of return and volatility (Sharpe) of 0.97 of Automatic Data Processing is higher, thus better.
  • During the last 3 years, the ratio of return and volatility (Sharpe) is 1.04, which is higher, thus better than the value of 0.87 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 excess return divided by the downside deviation over 5 years of Automatic Data Processing is 0.89, which is higher, thus better compared to the benchmark SPY (0.56) in the same period.
  • During the last 3 years, the excess return divided by the downside deviation is 0.94, which is larger, thus better than the value of 0.77 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.'

Which means for our asset as example:
  • Looking at the Ulcer Ratio of 5.34 in the last 5 years of Automatic Data Processing, we see it is relatively larger, thus better in comparison to the benchmark SPY (3.96 )
  • During the last 3 years, the Ulcer Index is 5.34 , which is greater, thus better than the value of 4.01 from the benchmark.

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.'

Applying this definition to our asset in some examples:
  • Looking at the maximum DrawDown of -19.2 days in the last 5 years of Automatic Data Processing, we see it is relatively higher, thus better in comparison to the benchmark SPY (-19.3 days)
  • Compared with SPY (-19.3 days) in the period of the last 3 years, the maximum DrawDown of -19.2 days is greater, 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) in days.'

Using this definition on our asset we see for example:
  • The maximum days below previous high over 5 years of Automatic Data Processing is 163 days, which is smaller, thus better compared to the benchmark SPY (187 days) in the same period.
  • Looking at maximum days below previous high in of 95 days in the period of the last 3 years, we see it is relatively lower, thus better in comparison to SPY (131 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.'

Which means for our asset as example:
  • Compared with the benchmark SPY (39 days) in the period of the last 5 years, the average time in days below previous high water mark of 36 days of Automatic Data Processing is lower, thus better.
  • Compared with SPY (34 days) in the period of the last 3 years, the average days below previous high of 30 days is smaller, thus better.

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 (%)

  • "Year" returns in the table above are not equal to 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.