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)

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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.'

Applying this definition to our asset in some examples:
  • Looking at the total return, or increase in value of 122.8% in the last 5 years of Verisk Analytics, we see it is relatively higher, thus better in comparison to the benchmark SPY (81.9%)
  • Looking at total return, or performance in of 23.3% in the period of the last 3 years, we see it is relatively smaller, thus worse in comparison to SPY (46.1%).

CAGR:

'The compound annual growth rate isn't a true return rate, but rather a representational figure. It is essentially a number that describes the rate at which an investment would have grown if it had grown the same rate every year and the profits were reinvested at the end of each year. In reality, this sort of performance is unlikely. However, CAGR can be used to smooth returns so that they may be more easily understood when compared to alternative investments.'

Applying this definition to our asset in some examples:
  • Compared with the benchmark SPY (12.7%) in the period of the last 5 years, the annual return (CAGR) of 17.4% of Verisk Analytics is larger, thus better.
  • Compared with SPY (13.5%) in the period of the last 3 years, the annual return (CAGR) of 7.2% is lower, thus worse.

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.'

Using this definition on our asset we see for example:
  • Compared with the benchmark SPY (19.8%) in the period of the last 5 years, the 30 days standard deviation of 24.6% of Verisk Analytics is larger, thus worse.
  • Looking at historical 30 days volatility in of 28.4% in the period of the last 3 years, we see it is relatively larger, thus worse in comparison to SPY (23%).

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 Verisk Analytics is 17.7%, which is larger, thus worse compared to the benchmark SPY (14.5%) in the same period.
  • During the last 3 years, the downside risk is 20.6%, which is greater, thus worse than the value of 16.8% from the benchmark.

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.'

Using this definition on our asset we see for example:
  • The ratio of return and volatility (Sharpe) over 5 years of Verisk Analytics is 0.61, which is higher, thus better compared to the benchmark SPY (0.52) in the same period.
  • Compared with SPY (0.48) in the period of the last 3 years, the risk / return profile (Sharpe) of 0.17 is lower, thus worse.

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.'

Which means for our asset as example:
  • The ratio of annual return and downside deviation over 5 years of Verisk Analytics is 0.84, which is higher, thus better compared to the benchmark SPY (0.7) in the same period.
  • Looking at excess return divided by the downside deviation in of 0.23 in the period of the last 3 years, we see it is relatively smaller, thus worse in comparison to SPY (0.65).

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.'

Applying this definition to our asset in some examples:
  • Looking at the Ulcer Index of 7.82 in the last 5 years of Verisk Analytics, we see it is relatively larger, thus worse in comparison to the benchmark SPY (6.08 )
  • Looking at Downside risk index in of 9.55 in the period of the last 3 years, we see it is relatively greater, thus worse in comparison to SPY (6.77 ).

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.'

Which means for our asset as example:
  • Compared with the benchmark SPY (-33.7 days) in the period of the last 5 years, the maximum reduction from previous high of -29.2 days of Verisk Analytics is larger, thus better.
  • During the last 3 years, the maximum drop from peak to valley is -29.2 days, which is greater, thus better than the value of -33.7 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'

Which means for our asset as example:
  • Compared with the benchmark SPY (139 days) in the period of the last 5 years, the maximum days under water of 185 days of Verisk Analytics is greater, thus worse.
  • During the last 3 years, the maximum days under water is 185 days, which is greater, thus worse than the value of 119 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.'

Using this definition on our asset we see for example:
  • The average days under water over 5 years of Verisk Analytics is 36 days, which is higher, thus worse compared to the benchmark SPY (35 days) in the same period.
  • Compared with SPY (27 days) in the period of the last 3 years, the average time in days below previous high water mark of 49 days is larger, thus worse.

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, do not account for slippage, fees or taxes, and are based on backtesting, which has many inherent limitations, some of which are described in our Terms of Use.