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:
  • Compared with the benchmark SPY (60.6%) in the period of the last 5 years, the total return of 107.1% of Verisk Analytics is larger, thus better.
  • Compared with SPY (38%) in the period of the last 3 years, the total return of 37.5% is smaller, thus worse.

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.'

Which means for our asset as example:
  • The annual performance (CAGR) over 5 years of Verisk Analytics is 15.7%, which is higher, thus better compared to the benchmark SPY (10%) in the same period.
  • Looking at annual performance (CAGR) in of 11.2% in the period of the last 3 years, we see it is relatively lower, thus worse in comparison to SPY (11.3%).

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:
  • The historical 30 days volatility over 5 years of Verisk Analytics is 26.4%, which is larger, thus worse compared to the benchmark SPY (21.5%) in the same period.
  • During the last 3 years, the volatility is 24%, which is larger, thus worse than the value of 17.9% from the benchmark.

DownVol:

'Downside risk is the financial risk associated with losses. That is, it is the risk of the actual return being below the expected return, or the uncertainty about the magnitude of that difference. 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.'

Applying this definition to our asset in some examples:
  • Compared with the benchmark SPY (15.5%) in the period of the last 5 years, the downside risk of 18.7% of Verisk Analytics is greater, thus worse.
  • Looking at downside volatility in of 17.3% in the period of the last 3 years, we see it is relatively higher, thus worse in comparison to SPY (12.5%).

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.'

Which means for our asset as example:
  • Looking at the risk / return profile (Sharpe) of 0.5 in the last 5 years of Verisk Analytics, we see it is relatively greater, thus better in comparison to the benchmark SPY (0.35)
  • Looking at ratio of return and volatility (Sharpe) in of 0.36 in the period of the last 3 years, we see it is relatively smaller, thus worse in comparison to SPY (0.49).

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:
  • The excess return divided by the downside deviation over 5 years of Verisk Analytics is 0.71, which is larger, thus better compared to the benchmark SPY (0.48) in the same period.
  • During the last 3 years, the downside risk / excess return profile is 0.51, which is lower, thus worse than the value of 0.71 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:
  • Looking at the Downside risk index of 12 in the last 5 years of Verisk Analytics, we see it is relatively greater, thus worse in comparison to the benchmark SPY (9.55 )
  • Compared with SPY (10 ) in the period of the last 3 years, the Ulcer Ratio of 15 is larger, thus worse.

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.'

Using this definition on our asset we see for example:
  • The maximum drop from peak to valley over 5 years of Verisk Analytics is -30.9 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 drop from peak to valley is -30.9 days, which is lower, thus worse than the value of -24.5 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'

Using this definition on our asset we see for example:
  • The maximum days below previous high over 5 years of Verisk Analytics is 394 days, which is lower, thus better compared to the benchmark SPY (431 days) in the same period.
  • Compared with SPY (431 days) in the period of the last 3 years, the maximum time in days below previous high water mark of 394 days is lower, thus better.

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:
  • Compared with the benchmark SPY (105 days) in the period of the last 5 years, the average days under water of 94 days of Verisk Analytics is smaller, thus better.
  • Compared with SPY (144 days) in the period of the last 3 years, the average time in days below previous high water mark of 136 days is lower, thus better.

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.