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:
  • Looking at the total return, or performance of 91% in the last 5 years of Automatic Data Processing, we see it is relatively lower, thus worse in comparison to the benchmark SPY (98.1%)
  • Looking at total return, or performance in of 36.5% in the period of the last 3 years, we see it is relatively larger, thus better in comparison to SPY (35.3%).

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.'

Applying this definition to our asset in some examples:
  • Looking at the annual performance (CAGR) of 13.8% in the last 5 years of Automatic Data Processing, we see it is relatively lower, thus worse in comparison to the benchmark SPY (14.7%)
  • Compared with SPY (10.6%) in the period of the last 3 years, the compounded annual growth rate (CAGR) of 11% is greater, 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 27.6%, which is larger, thus worse compared to the benchmark SPY (21%) in the same period.
  • Compared with SPY (17.5%) in the period of the last 3 years, the historical 30 days volatility of 22.2% is larger, 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.'

Applying this definition to our asset in some examples:
  • The downside risk over 5 years of Automatic Data Processing is 19.7%, which is higher, thus worse compared to the benchmark SPY (15%) in the same period.
  • Looking at downside deviation in of 15.9% in the period of the last 3 years, we see it is relatively greater, thus worse in comparison to SPY (12.2%).

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.'

Which means for our asset as example:
  • Looking at the ratio of return and volatility (Sharpe) of 0.41 in the last 5 years of Automatic Data Processing, we see it is relatively lower, thus worse in comparison to the benchmark SPY (0.58)
  • Looking at Sharpe Ratio in of 0.38 in the period of the last 3 years, we see it is relatively lower, thus worse in comparison to SPY (0.46).

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:
  • The ratio of annual return and downside deviation over 5 years of Automatic Data Processing is 0.57, which is lower, thus worse compared to the benchmark SPY (0.81) in the same period.
  • Compared with SPY (0.66) in the period of the last 3 years, the ratio of annual return and downside deviation of 0.53 is lower, thus worse.

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:
  • Compared with the benchmark SPY (9.32 ) in the period of the last 5 years, the Ulcer Index of 12 of Automatic Data Processing is greater, thus worse.
  • Looking at Downside risk index in of 11 in the period of the last 3 years, we see it is relatively higher, 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:
  • Looking at the maximum DrawDown of -39.5 days in the last 5 years of Automatic Data Processing, we see it is relatively lower, thus worse in comparison to the benchmark SPY (-33.7 days)
  • Looking at maximum reduction from previous high in of -21.8 days in the period of the last 3 years, we see it is relatively higher, thus better in comparison to SPY (-24.5 days).

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.'

Which means for our asset as example:
  • 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 414 days of Automatic Data Processing is lower, thus better.
  • During the last 3 years, the maximum days below previous high is 414 days, which is lower, thus better than the value of 488 days from the benchmark.

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.'

Using this definition on our asset we see for example:
  • The average time in days below previous high water mark over 5 years of Automatic Data Processing is 109 days, which is lower, thus better compared to the benchmark SPY (122 days) in the same period.
  • Compared with SPY (178 days) in the period of the last 3 years, the average days under water of 141 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 and do not account for slippage, fees or taxes.