Description

CA, Inc., doing business as CA technologies, develops, markets, delivers, and licenses software products and services in the United States and internationally. It operates through three segments: Mainframe Solutions, Enterprise Solutions, and Services. The Mainframe Solutions segment offers solutions for the IBM z Systems platform, which runs various mission critical business applications. Its mainframe solutions enable customers enhance economics by increasing throughput and lowering cost per transaction; increasing business agility through DevOps tooling and processes; increasing reliability and availability of operations through machine intelligence and automation solutions; and protecting enterprise data with security and compliance. The Enterprise Solutions segment provides a range of software planning, development, and management tools for mobile, cloud, and distributed computing environments. It primarily provides customers secure application development, infrastructure management, automation, and identity-centric security solutions. The Services segment offers various services, such as consulting, implementation, application management, education, and support services to commercial and government customers for implementation and adoption of its software solutions. The company serves banks, insurance companies, other financial services providers, government agencies, information technology service providers, telecommunication providers, transportation companies, manufacturers, technology companies, retailers, educational organizations, and health care institutions. It sells its products through direct sales force, as well as through various partner channels comprising resellers, service providers, system integrators, managed service providers, and technology partners. The company was formerly known as Computer Associates International, Inc. and changed its name to CA, Inc. in 2006. CA, Inc. was founded in 1974 and is headquartered in New York, New York.

Statistics (YTD)

What do these metrics mean? [Read More] [Hide]

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.'

Applying this definition to our asset in some examples:
  • The total return, or performance over 5 years of CA Technologies is %, which is lower, thus worse compared to the benchmark SPY (109.3%) in the same period.
  • Looking at total return in of % in the period of the last 3 years, we see it is relatively smaller, thus worse in comparison to SPY (34.3%).

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.'

Using this definition on our asset we see for example:
  • Looking at the annual performance (CAGR) of % in the last 5 years of CA Technologies, we see it is relatively lower, thus worse in comparison to the benchmark SPY (16%)
  • During the last 3 years, the compounded annual growth rate (CAGR) is %, which is lower, thus worse than the value of 10.4% 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.'

Applying this definition to our asset in some examples:
  • Compared with the benchmark SPY (18%) in the period of the last 5 years, the 30 days standard deviation of % of CA Technologies is smaller, thus better.
  • During the last 3 years, the 30 days standard deviation is %, which is smaller, thus better than the value of 18.8% from the benchmark.

DownVol:

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

Using this definition on our asset we see for example:
  • The downside risk over 5 years of CA Technologies is %, which is smaller, thus better compared to the benchmark SPY (12.5%) in the same period.
  • Looking at downside volatility in of % in the period of the last 3 years, we see it is relatively smaller, thus better in comparison to SPY (13%).

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:
  • Compared with the benchmark SPY (0.75) in the period of the last 5 years, the ratio of return and volatility (Sharpe) of of CA Technologies is lower, thus worse.
  • Looking at risk / return profile (Sharpe) in of in the period of the last 3 years, we see it is relatively lower, thus worse in comparison to SPY (0.42).

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:
  • Compared with the benchmark SPY (1.07) in the period of the last 5 years, the excess return divided by the downside deviation of of CA Technologies is lower, thus worse.
  • During the last 3 years, the ratio of annual return and downside deviation is , which is smaller, thus worse than the value of 0.6 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.'

Using this definition on our asset we see for example:
  • Compared with the benchmark SPY (8.45 ) in the period of the last 5 years, the Downside risk index of of CA Technologies is lower, thus better.
  • Compared with SPY (5.75 ) in the period of the last 3 years, the Ulcer Ratio of is lower, thus better.

MaxDD:

'Maximum drawdown is defined as the peak-to-trough decline of an investment during a specific period. It is usually quoted as a percentage of the peak value. The maximum drawdown can be calculated based on absolute returns, in order to identify strategies that suffer less during market downturns, such as low-volatility strategies. However, the maximum drawdown can also be calculated based on returns relative to a benchmark index, for identifying strategies that show steady outperformance over time.'

Using this definition on our asset we see for example:
  • Looking at the maximum DrawDown of days in the last 5 years of CA Technologies, we see it is relatively lower, thus worse in comparison to the benchmark SPY (-24.5 days)
  • Compared with SPY (-18.8 days) in the period of the last 3 years, the maximum drop from peak to valley of 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). Many assume Max DD Duration is the length of time between new highs during which the Max DD (magnitude) occurred. But that isn’t always the case. The Max DD duration is the longest time between peaks, period. So it could be the time when the program also had its biggest peak to valley loss (and usually is, because the program needs a long time to recover from the largest loss), but it doesn’t have to be'

Using this definition on our asset we see for example:
  • The maximum days under water over 5 years of CA Technologies is days, which is smaller, thus better compared to the benchmark SPY (488 days) in the same period.
  • During the last 3 years, the maximum time in days below previous high water mark is days, which is lower, thus better than the value of 199 days from the benchmark.

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:
  • Compared with the benchmark SPY (118 days) in the period of the last 5 years, the average days below previous high of days of CA Technologies is smaller, thus better.
  • Looking at average days under water in of days in the period of the last 3 years, we see it is relatively lower, thus better in comparison to SPY (45 days).

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 CA Technologies are hypothetical and do not account for slippage, fees or taxes.