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:

'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:
  • The total return, or increase in value over 5 years of Verisk Analytics is 87.1%, which is greater, thus better compared to the benchmark SPY (63%) in the same period.
  • During the last 3 years, the total return is 11.1%, which is smaller, thus worse than the value of 33.5% from the benchmark.

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:
  • Compared with the benchmark SPY (10.3%) in the period of the last 5 years, the compounded annual growth rate (CAGR) of 13.4% of Verisk Analytics is larger, thus better.
  • During the last 3 years, the annual performance (CAGR) is 3.6%, which is smaller, thus worse than the value of 10.1% from the benchmark.

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 historical 30 days volatility of 26.3% in the last 5 years of Verisk Analytics, we see it is relatively higher, thus worse in comparison to the benchmark SPY (21.6%)
  • During the last 3 years, the 30 days standard deviation is 30.5%, which is greater, thus worse than the value of 25.1% from the benchmark.

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:
  • Compared with the benchmark SPY (15.6%) in the period of the last 5 years, the downside risk of 18.9% of Verisk Analytics is higher, thus worse.
  • Compared with SPY (18.1%) in the period of the last 3 years, the downside volatility of 22% is larger, thus worse.

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:
  • Compared with the benchmark SPY (0.36) in the period of the last 5 years, the Sharpe Ratio of 0.41 of Verisk Analytics is higher, thus better.
  • Compared with SPY (0.3) in the period of the last 3 years, the risk / return profile (Sharpe) of 0.04 is smaller, thus worse.

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.'

Applying this definition to our asset in some examples:
  • Compared with the benchmark SPY (0.5) in the period of the last 5 years, the ratio of annual return and downside deviation of 0.57 of Verisk Analytics is higher, thus better.
  • During the last 3 years, the excess return divided by the downside deviation is 0.05, which is lower, thus worse than the value of 0.42 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 11 in the last 5 years of Verisk Analytics, we see it is relatively higher, thus worse in comparison to the benchmark SPY (8.88 )
  • Compared with SPY (11 ) in the period of the last 3 years, the Downside risk index of 14 is larger, thus worse.

MaxDD:

'Maximum drawdown measures the loss in any losing period during a fund’s investment record. It is defined as the percent retrenchment from a fund’s peak value to the fund’s valley value. The drawdown is in effect from the time the fund’s retrenchment begins until a new fund high is reached. The maximum drawdown encompasses both the period from the fund’s peak to the fund’s valley (length), and the time from the fund’s valley to a new fund high (recovery). It measures the largest percentage drawdown that has occurred in any fund’s data record.'

Using this definition on our asset we see for example:
  • Looking at the maximum drop from peak to valley of -30.9 days in the last 5 years of Verisk Analytics, we see it is relatively greater, thus better in comparison to the benchmark SPY (-33.7 days)
  • During the last 3 years, the maximum reduction from previous high is -30.9 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 (273 days) in the period of the last 5 years, the maximum days under water of 302 days of Verisk Analytics is higher, thus worse.
  • During the last 3 years, the maximum time in days below previous high water mark is 302 days, which is larger, thus worse than the value of 273 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:
  • Looking at the average days under water of 67 days in the last 5 years of Verisk Analytics, we see it is relatively larger, thus worse in comparison to the benchmark SPY (57 days)
  • Compared with SPY (73 days) in the period of the last 3 years, the average days under water of 94 days is higher, 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.