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 of 140.9% in the last 5 years of Verisk Analytics, we see it is relatively larger, thus better in comparison to the benchmark SPY (120.8%)
  • Compared with SPY (66.3%) in the period of the last 3 years, the total return of 78.6% is larger, thus better.

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:
  • Looking at the annual performance (CAGR) of 19.2% in the last 5 years of Verisk Analytics, we see it is relatively higher, thus better in comparison to the benchmark SPY (17.2%)
  • Looking at annual performance (CAGR) in of 21.3% in the period of the last 3 years, we see it is relatively greater, thus better in comparison to SPY (18.5%).

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.'

Applying this definition to our asset in some examples:
  • Looking at the historical 30 days volatility of 23.3% in the last 5 years of Verisk Analytics, we see it is relatively greater, thus worse in comparison to the benchmark SPY (18.7%)
  • Compared with SPY (22.4%) in the period of the last 3 years, the historical 30 days volatility of 27.3% is larger, thus worse.

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.'

Applying this definition to our asset in some examples:
  • Looking at the downside volatility of 16.5% in the last 5 years of Verisk Analytics, we see it is relatively greater, thus worse in comparison to the benchmark SPY (13.6%)
  • Compared with SPY (16.3%) in the period of the last 3 years, the downside risk of 19.3% is larger, thus worse.

Sharpe:

'The Sharpe ratio was developed by Nobel laureate William F. Sharpe, and is used to help investors understand the return of an investment compared to its risk. The ratio is the average return earned in excess of the risk-free rate per unit of volatility or total risk. Subtracting the risk-free rate from the mean return allows an investor to better isolate the profits associated with risk-taking activities. One intuition of this calculation is that a portfolio engaging in 'zero risk' investments, such as the purchase of U.S. Treasury bills (for which the expected return is the risk-free rate), has a Sharpe ratio of exactly zero. Generally, the greater the value of the Sharpe ratio, the more attractive the risk-adjusted return.'

Applying this definition to our asset in some examples:
  • Compared with the benchmark SPY (0.78) in the period of the last 5 years, the risk / return profile (Sharpe) of 0.72 of Verisk Analytics is smaller, thus worse.
  • During the last 3 years, the risk / return profile (Sharpe) is 0.69, which is smaller, thus worse than the value of 0.71 from the benchmark.

Sortino:

'The Sortino ratio, a variation of the Sharpe ratio only factors in the downside, or negative volatility, rather than the total volatility used in calculating the Sharpe ratio. The theory behind the Sortino variation is that upside volatility is a plus for the investment, and it, therefore, should not be included in the risk calculation. Therefore, the Sortino ratio takes upside volatility out of the equation and uses only the downside standard deviation in its calculation instead of the total standard deviation that is used in calculating the Sharpe ratio.'

Using this definition on our asset we see for example:
  • The downside risk / excess return profile over 5 years of Verisk Analytics is 1.01, which is lower, thus worse compared to the benchmark SPY (1.08) in the same period.
  • Looking at excess return divided by the downside deviation in of 0.97 in the period of the last 3 years, we see it is relatively lower, thus worse in comparison to SPY (0.98).

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.'

Which means for our asset as example:
  • The Downside risk index over 5 years of Verisk Analytics is 6.12 , which is larger, thus worse compared to the benchmark SPY (5.59 ) in the same period.
  • During the last 3 years, the Downside risk index is 7.13 , which is higher, thus worse than the value of 6.83 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.'

Using this definition on our asset we see for example:
  • Looking at the maximum DrawDown of -29.2 days in the last 5 years of Verisk Analytics, we see it is relatively larger, thus better in comparison to the benchmark SPY (-33.7 days)
  • Compared with SPY (-33.7 days) in the period of the last 3 years, the maximum DrawDown of -29.2 days is larger, thus better.

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'

Applying this definition to our asset in some examples:
  • Looking at the maximum days under water of 247 days in the last 5 years of Verisk Analytics, we see it is relatively larger, thus worse in comparison to the benchmark SPY (139 days)
  • During the last 3 years, the maximum days below previous high is 94 days, which is smaller, thus better than the value of 139 days from the benchmark.

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:
  • The average days under water over 5 years of Verisk Analytics is 44 days, which is larger, thus worse compared to the benchmark SPY (33 days) in the same period.
  • Compared with SPY (35 days) in the period of the last 3 years, the average days below previous high of 22 days is lower, 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.