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.'

Using this definition on our asset we see for example:
  • The total return over 5 years of Verisk Analytics is 79.4%, which is lower, thus worse compared to the benchmark SPY (111.6%) in the same period.
  • Looking at total return in of 73.3% in the period of the last 3 years, we see it is relatively higher, thus better in comparison to SPY (68%).

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.'

Using this definition on our asset we see for example:
  • Compared with the benchmark SPY (16.2%) in the period of the last 5 years, the annual performance (CAGR) of 12.5% of Verisk Analytics is lower, thus worse.
  • During the last 3 years, the annual performance (CAGR) is 20.2%, which is higher, thus better than the value of 19% 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:
  • The historical 30 days volatility over 5 years of Verisk Analytics is 22.5%, which is greater, thus worse compared to the benchmark SPY (17.5%) in the same period.
  • Compared with SPY (17.5%) in the period of the last 3 years, the historical 30 days volatility of 21.7% is greater, thus worse.

DownVol:

'The downside volatility is similar to the volatility, or standard deviation, but only takes losing/negative periods into account.'

Applying this definition to our asset in some examples:
  • The downside deviation over 5 years of Verisk Analytics is 16.2%, which is greater, thus worse compared to the benchmark SPY (12.1%) in the same period.
  • Looking at downside volatility in of 14.8% in the period of the last 3 years, we see it is relatively larger, thus worse in comparison to SPY (11.5%).

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 0.44 in the last 5 years of Verisk Analytics, we see it is relatively lower, thus worse in comparison to the benchmark SPY (0.78)
  • Compared with SPY (0.94) in the period of the last 3 years, the Sharpe Ratio of 0.82 is lower, thus worse.

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 ratio of annual return and downside deviation over 5 years of Verisk Analytics is 0.62, which is lower, thus worse compared to the benchmark SPY (1.14) in the same period.
  • During the last 3 years, the ratio of annual return and downside deviation is 1.2, which is lower, thus worse than the value of 1.43 from the benchmark.

Ulcer:

'The Ulcer Index is a technical indicator that measures downside risk, in terms of both the depth and duration of price declines. The index increases in value as the price moves farther away from a recent high and falls as the price rises to new highs. The indicator is usually calculated over a 14-day period, with the Ulcer Index showing the percentage drawdown a trader can expect from the high over that period. The greater the value of the Ulcer Index, the longer it takes for a stock to get back to the former high.'

Which means for our asset as example:
  • Compared with the benchmark SPY (8.48 ) in the period of the last 5 years, the Downside risk index of 12 of Verisk Analytics is greater, thus worse.
  • Looking at Downside risk index in of 7.01 in the period of the last 3 years, we see it is relatively higher, thus worse in comparison to SPY (5.31 ).

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.'

Which means for our asset as 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 lower, thus worse in comparison to the benchmark SPY (-24.5 days)
  • Compared with SPY (-18.8 days) in the period of the last 3 years, the maximum drop from peak to valley of -19.5 days is lower, thus worse.

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:
  • Compared with the benchmark SPY (488 days) in the period of the last 5 years, the maximum days below previous high of 396 days of Verisk Analytics is smaller, thus better.
  • During the last 3 years, the maximum days below previous high is 180 days, which is smaller, thus better than the value of 199 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.'

Using this definition on our asset we see for example:
  • Compared with the benchmark SPY (120 days) in the period of the last 5 years, the average days below previous high of 94 days of Verisk Analytics is lower, thus better.
  • Compared with SPY (47 days) in the period of the last 3 years, the average time in days below previous high water mark of 43 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 and do not account for slippage, fees or taxes.