Description

Verisk Analytics, Inc. provides data analytics solutions in the United States and internationally. It provides predictive analytics and decision support solutions to customers in rating, underwriting, claims, catastrophe and weather risk, natural resources intelligence, economic forecasting, commercial banking and finance, and various other fields. The company operates through three segments: Insurance, Energy and Specialized Markets, and Financial Services. The Insurance segment focuses on the prediction of loss, selection and pricing of risk, and compliance with their reporting requirements for property and casualty customers. It also develops predictive models to forecast scenarios and produce standard and customized analytics that help its customers to manage their businesses, including detecting fraud before and after a loss event, and quantifying losses. The Energy and Specialized Markets segment provides data analytics for the natural resources value chain, including energy, chemicals, metals, mining, power, and renewables sectors; research and consulting services focusing on exploration strategies and screening, asset development and acquisition, commodity markets, and corporate analysis; and consultancy services in the areas of business environment, business improvement, business strategies, commercial advisory, and transaction support, as well as analysis and advice on assets, companies, governments, and markets. The Financial Services segment offers benchmarking, decisioning algorithms, business intelligence, and customized analytic services to financial institutions, payment networks and processors, alternative lenders, regulators, and merchants. The company was founded in 1971 and is headquartered in Jersey City, New Jersey.

Statistics (YTD)

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

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.'

Applying this definition to our asset in some examples:
  • Looking at the total return, or performance of 6.4% in the last 5 years of Verisk Analytics, we see it is relatively lower, thus worse in comparison to the benchmark SPY (75.3%)
  • Looking at total return, or performance in of -1.6% in the period of the last 3 years, we see it is relatively smaller, thus worse in comparison to SPY (66.5%).

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.'

Using this definition on our asset we see for example:
  • The compounded annual growth rate (CAGR) over 5 years of Verisk Analytics is 1.2%, which is lower, thus worse compared to the benchmark SPY (11.9%) in the same period.
  • Looking at annual performance (CAGR) in of -0.5% in the period of the last 3 years, we see it is relatively lower, thus worse in comparison to SPY (18.6%).

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:
  • Looking at the volatility of 23.7% in the last 5 years of Verisk Analytics, we see it is relatively larger, thus worse in comparison to the benchmark SPY (17%)
  • Compared with SPY (15.1%) in the period of the last 3 years, the historical 30 days volatility of 23.1% is higher, thus worse.

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 (11.8%) in the period of the last 5 years, the downside risk of 17.7% of Verisk Analytics is higher, thus worse.
  • During the last 3 years, the downside risk is 17.6%, which is higher, thus worse than the value of 10.1% from the benchmark.

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:
  • Looking at the ratio of return and volatility (Sharpe) of -0.05 in the last 5 years of Verisk Analytics, we see it is relatively smaller, thus worse in comparison to the benchmark SPY (0.55)
  • During the last 3 years, the Sharpe Ratio is -0.13, which is lower, thus worse than the value of 1.06 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.'

Which means for our asset as example:
  • The ratio of annual return and downside deviation over 5 years of Verisk Analytics is -0.07, which is smaller, thus worse compared to the benchmark SPY (0.8) in the same period.
  • During the last 3 years, the excess return divided by the downside deviation is -0.17, which is lower, thus worse than the value of 1.59 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 (8.44 ) in the period of the last 5 years, the Ulcer Ratio of 16 of Verisk Analytics is higher, thus worse.
  • Compared with SPY (3.49 ) in the period of the last 3 years, the Ulcer Ratio of 15 is larger, thus worse.

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.'

Applying this definition to our asset in some examples:
  • Compared with the benchmark SPY (-24.5 days) in the period of the last 5 years, the maximum drop from peak to valley of -47 days of Verisk Analytics is lower, thus worse.
  • During the last 3 years, the maximum drop from peak to valley is -47 days, which is lower, thus worse than the value of -18.8 days from the benchmark.

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.'

Using this definition on our asset we see for example:
  • The maximum time in days below previous high water mark over 5 years of Verisk Analytics is 396 days, which is lower, thus better compared to the benchmark SPY (488 days) in the same period.
  • Compared with SPY (87 days) in the period of the last 3 years, the maximum days under water of 208 days is higher, thus worse.

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 days below previous high over 5 years of Verisk Analytics is 99 days, which is lower, thus better compared to the benchmark SPY (119 days) in the same period.
  • Looking at average days under water in of 50 days in the period of the last 3 years, we see it is relatively higher, thus worse in comparison to SPY (20 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 Verisk Analytics are hypothetical and do not account for slippage, fees or taxes.