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, 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:
  • Looking at the total return, or increase in value of 105.5% in the last 5 years of Verisk Analytics, we see it is relatively lower, thus worse in comparison to the benchmark SPY (112.6%)
  • During the last 3 years, the total return is 88.5%, which is higher, thus better than the value of 56.3% from the benchmark.

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:
  • The annual return (CAGR) over 5 years of Verisk Analytics is 15.5%, which is lower, thus worse compared to the benchmark SPY (16.3%) in the same period.
  • During the last 3 years, the annual return (CAGR) is 23.7%, which is higher, thus better than the value of 16.1% 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.'

Which means for our asset as example:
  • Looking at the 30 days standard deviation of 22.8% in the last 5 years of Verisk Analytics, we see it is relatively greater, thus worse in comparison to the benchmark SPY (17.9%)
  • Compared with SPY (18.2%) in the period of the last 3 years, the 30 days standard deviation of 22.1% 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:
  • Looking at the downside volatility of 16.3% in the last 5 years of Verisk Analytics, we see it is relatively larger, thus worse in comparison to the benchmark SPY (12.4%)
  • Compared with SPY (12.2%) in the period of the last 3 years, the downside volatility of 15% is higher, 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:
  • The ratio of return and volatility (Sharpe) over 5 years of Verisk Analytics is 0.57, which is lower, thus worse compared to the benchmark SPY (0.77) in the same period.
  • Compared with SPY (0.75) in the period of the last 3 years, the ratio of return and volatility (Sharpe) of 0.96 is higher, thus better.

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.'

Applying this definition to our asset in some examples:
  • Looking at the ratio of annual return and downside deviation of 0.8 in the last 5 years of Verisk Analytics, we see it is relatively smaller, thus worse in comparison to the benchmark SPY (1.11)
  • Looking at ratio of annual return and downside deviation in of 1.41 in the period of the last 3 years, we see it is relatively greater, thus better in comparison to SPY (1.12).

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:
  • Looking at the Downside risk index of 12 in the last 5 years of Verisk Analytics, we see it is relatively higher, thus worse in comparison to the benchmark SPY (8.49 )
  • During the last 3 years, the Downside risk index is 7.06 , which is larger, thus worse than the value of 5.54 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.'

Which means for our asset as example:
  • Looking at the maximum reduction from previous high of -30.9 days in the last 5 years of Verisk Analytics, we see it is relatively lower, thus worse in comparison to the benchmark SPY (-24.5 days)
  • Looking at maximum drop from peak to valley in of -19.5 days in the period of the last 3 years, we see it is relatively smaller, thus worse in comparison to SPY (-18.8 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.'

Using this definition on our asset we see for example:
  • The maximum days below previous high over 5 years of Verisk Analytics is 396 days, which is smaller, thus better compared to the benchmark SPY (488 days) in the same period.
  • Looking at maximum days below previous high in of 180 days in the period of the last 3 years, we see it is relatively lower, thus better in comparison to SPY (199 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.'

Applying this definition to our asset in some examples:
  • Looking at the average time in days below previous high water mark of 94 days in the last 5 years of Verisk Analytics, we see it is relatively lower, thus better in comparison to the benchmark SPY (119 days)
  • Looking at average days under water in of 43 days in the period of the last 3 years, we see it is relatively smaller, 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 Verisk Analytics are hypothetical and do not account for slippage, fees or taxes.