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.'

Which means for our asset as example:
  • The total return, or performance over 5 years of Verisk Analytics is -0.3%, which is smaller, thus worse compared to the benchmark SPY (88%) in the same period.
  • Looking at total return in of 5.8% in the period of the last 3 years, we see it is relatively smaller, thus worse in comparison to SPY (74.8%).

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 (13.5%) in the period of the last 5 years, the compounded annual growth rate (CAGR) of -0.1% of Verisk Analytics is lower, thus worse.
  • Compared with SPY (20.6%) in the period of the last 3 years, the annual return (CAGR) of 1.9% is smaller, thus worse.

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.'

Using this definition on our asset we see for example:
  • Looking at the volatility of 23.7% in the last 5 years of Verisk Analytics, we see it is relatively greater, thus worse in comparison to the benchmark SPY (17.1%)
  • Looking at historical 30 days volatility in of 22.4% in the period of the last 3 years, we see it is relatively higher, thus worse in comparison to SPY (15.2%).

DownVol:

'Risk measures typically quantify the downside risk, whereas the standard deviation (an example of a deviation risk measure) measures both the upside and downside risk. Specifically, downside risk in our definition is the semi-deviation, that is the standard deviation of all negative returns.'

Which means for our asset as example:
  • Looking at the downside deviation of 18% in the last 5 years of Verisk Analytics, we see it is relatively greater, thus worse in comparison to the benchmark SPY (11.8%)
  • Looking at downside deviation in of 17% in the period of the last 3 years, we see it is relatively greater, thus worse in comparison to SPY (10.2%).

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.'

Applying this definition to our asset in some examples:
  • Looking at the Sharpe Ratio of -0.11 in the last 5 years of Verisk Analytics, we see it is relatively lower, thus worse in comparison to the benchmark SPY (0.65)
  • Looking at Sharpe Ratio in of -0.03 in the period of the last 3 years, we see it is relatively lower, thus worse in comparison to SPY (1.19).

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.'

Which means for our asset as example:
  • Compared with the benchmark SPY (0.94) in the period of the last 5 years, the ratio of annual return and downside deviation of -0.14 of Verisk Analytics is smaller, thus worse.
  • During the last 3 years, the excess return divided by the downside deviation is -0.03, which is lower, thus worse than the value of 1.78 from the benchmark.

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:
  • Compared with the benchmark SPY (8.42 ) in the period of the last 5 years, the Downside risk index of 14 of Verisk Analytics is greater, thus worse.
  • Looking at Ulcer Ratio in of 13 in the period of the last 3 years, we see it is relatively greater, thus worse in comparison to SPY (3.42 ).

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 (-24.5 days) in the period of the last 5 years, the maximum reduction from previous high of -47 days of Verisk Analytics is smaller, thus worse.
  • Looking at maximum drop from peak to valley in of -47 days in the period of the last 3 years, we see it is relatively lower, thus worse in comparison to SPY (-18.8 days).

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:
  • Looking at the maximum days below previous high of 396 days in the last 5 years of Verisk Analytics, we see it is relatively lower, thus better in comparison to the benchmark SPY (488 days)
  • During the last 3 years, the maximum days below previous high is 178 days, which is higher, thus worse than the value of 87 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:
  • Compared with the benchmark SPY (119 days) in the period of the last 5 years, the average days below previous high of 97 days of Verisk Analytics is lower, thus better.
  • Looking at average days below previous high in of 42 days in the period of the last 3 years, we see it is relatively larger, thus worse in comparison to SPY (19 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.