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:

'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:
  • Compared with the benchmark SPY (85.8%) in the period of the last 5 years, the total return, or increase in value of % of CA Technologies is lower, thus worse.
  • Compared with SPY (85%) in the period of the last 3 years, the total return, or increase in value of % is smaller, thus worse.

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 (13.2%) in the period of the last 5 years, the compounded annual growth rate (CAGR) of % of CA Technologies is smaller, thus worse.
  • During the last 3 years, the compounded annual growth rate (CAGR) is %, which is lower, thus worse than the value of 22.9% 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 CA Technologies is %, which is lower, thus better compared to the benchmark SPY (17.2%) in the same period.
  • Looking at 30 days standard deviation in of % in the period of the last 3 years, we see it is relatively lower, thus better in comparison to SPY (15.3%).

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:
  • The downside deviation over 5 years of CA Technologies is %, which is lower, thus better compared to the benchmark SPY (11.8%) in the same period.
  • During the last 3 years, the downside deviation is %, which is smaller, thus better than the value of 10.2% from the benchmark.

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.'

Using this definition on our asset we see for example:
  • The Sharpe Ratio over 5 years of CA Technologies is , which is lower, thus worse compared to the benchmark SPY (0.63) in the same period.
  • During the last 3 years, the risk / return profile (Sharpe) is , which is lower, thus worse than the value of 1.33 from the benchmark.

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.'

Using this definition on our asset we see for example:
  • Compared with the benchmark SPY (0.91) in the period of the last 5 years, the excess return divided by the downside deviation of of CA Technologies is smaller, thus worse.
  • Compared with SPY (2) in the period of the last 3 years, the excess return divided by the downside deviation of is lower, thus worse.

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 Ulcer Index of of CA Technologies is lower, thus better.
  • During the last 3 years, the Downside risk index is , which is lower, thus better than the value of 3.23 from the benchmark.

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)
  • During the last 3 years, the maximum drop from peak to valley is days, which is smaller, thus worse than the value of -18.8 days from the benchmark.

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 time in days below previous high water mark over 5 years of CA Technologies is days, which is smaller, thus better compared to the benchmark SPY (488 days) in the same period.
  • Looking at maximum days under water in of days in the period of the last 3 years, we see it is relatively smaller, thus better in comparison to SPY (87 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:
  • Looking at the average days under water of days in the last 5 years of CA Technologies, we see it is relatively smaller, thus better in comparison to the benchmark SPY (118 days)
  • Looking at average days below previous high in of days in the period of the last 3 years, we see it is relatively lower, thus better in comparison to SPY (17 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.