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 increase in value over 5 years of Verisk Analytics is 169.1%, which is higher, thus better compared to the benchmark SPY (122.1%) in the same period.
  • Looking at total return, or increase in value in of 97.5% in the period of the last 3 years, we see it is relatively greater, thus better in comparison to SPY (43.5%).

CAGR:

'The compound annual growth rate (CAGR) is a useful measure of growth over multiple time periods. It can be thought of as the growth rate that gets you from the initial investment value to the ending investment value if you assume that the investment has been compounding over the time period.'

Which means for our asset as example:
  • Compared with the benchmark SPY (17.3%) in the period of the last 5 years, the annual performance (CAGR) of 21.9% of Verisk Analytics is larger, thus better.
  • During the last 3 years, the annual performance (CAGR) is 25.5%, which is greater, thus better than the value of 12.8% from the benchmark.

Volatility:

'Volatility is a rate at which the price of a security increases or decreases for a given set of returns. Volatility is measured by calculating the standard deviation of the annualized returns over a given period of time. It shows the range to which the price of a security may increase or decrease. Volatility measures the risk of a security. It is used in option pricing formula to gauge the fluctuations in the returns of the underlying assets. Volatility indicates the pricing behavior of the security and helps estimate the fluctuations that may happen in a short period of time.'

Using this definition on our asset we see for example:
  • Compared with the benchmark SPY (18.8%) in the period of the last 5 years, the 30 days standard deviation of 23% of Verisk Analytics is greater, thus worse.
  • Compared with SPY (22.9%) in the period of the last 3 years, the 30 days standard deviation of 26.7% is higher, thus worse.

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 16%, which is higher, thus worse compared to the benchmark SPY (13.6%) in the same period.
  • Looking at downside risk in of 18.6% in the period of the last 3 years, we see it is relatively larger, thus worse in comparison to SPY (16.8%).

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:
  • Compared with the benchmark SPY (0.79) in the period of the last 5 years, the risk / return profile (Sharpe) of 0.84 of Verisk Analytics is greater, thus better.
  • During the last 3 years, the risk / return profile (Sharpe) is 0.86, which is greater, thus better than the value of 0.45 from the benchmark.

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 excess return divided by the downside deviation of 1.21 in the last 5 years of Verisk Analytics, we see it is relatively greater, thus better in comparison to the benchmark SPY (1.09)
  • Looking at ratio of annual return and downside deviation in of 1.24 in the period of the last 3 years, we see it is relatively greater, thus better in comparison to SPY (0.61).

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:
  • Looking at the Ulcer Ratio of 5.39 in the last 5 years of Verisk Analytics, we see it is relatively lower, thus better in comparison to the benchmark SPY (5.59 )
  • During the last 3 years, the Ulcer Ratio is 6 , which is lower, thus better than the value of 7.15 from the benchmark.

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.'

Applying this definition to our asset in some examples:
  • The maximum DrawDown over 5 years of Verisk Analytics is -29.2 days, which is larger, thus better compared to the benchmark SPY (-33.7 days) in the same period.
  • During the last 3 years, the maximum reduction from previous high is -29.2 days, which is higher, thus better than the value of -33.7 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.'

Applying this definition to our asset in some examples:
  • The maximum days under water over 5 years of Verisk Analytics is 247 days, which is higher, thus worse compared to the benchmark SPY (139 days) in the same period.
  • Compared with SPY (139 days) in the period of the last 3 years, the maximum time in days below previous high water mark of 94 days is lower, thus better.

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.'

Which means for our asset as example:
  • Looking at the average days under water of 44 days in the last 5 years of Verisk Analytics, we see it is relatively higher, thus worse in comparison to the benchmark SPY (33 days)
  • Compared with SPY (45 days) in the period of the last 3 years, the average days below previous high of 19 days is smaller, thus better.

Performance (YTD)

Historical returns have been extended using synthetic data.

Allocations
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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.