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:
  • Compared with the benchmark SPY (72.2%) in the period of the last 5 years, the total return, or increase in value of -3.9% of Verisk Analytics is lower, thus worse.
  • Compared with SPY (79.9%) in the period of the last 3 years, the total return, or performance of -12.9% is lower, thus worse.

CAGR:

'Compound annual growth rate (CAGR) is a business and investing specific term for the geometric progression ratio that provides a constant rate of return over the time period. CAGR is not an accounting term, but it is often used to describe some element of the business, for example revenue, units delivered, registered users, etc. CAGR dampens the effect of volatility of periodic returns that can render arithmetic means irrelevant. It is particularly useful to compare growth rates from various data sets of common domain such as revenue growth of companies in the same industry.'

Applying this definition to our asset in some examples:
  • Looking at the annual performance (CAGR) of -0.8% in the last 5 years of Verisk Analytics, we see it is relatively lower, thus worse in comparison to the benchmark SPY (11.5%)
  • During the last 3 years, the annual performance (CAGR) is -4.5%, which is lower, thus worse than the value of 21.8% 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 30 days standard deviation over 5 years of Verisk Analytics is 26.4%, which is higher, thus worse compared to the benchmark SPY (17.3%) in the same period.
  • Compared with SPY (15.5%) in the period of the last 3 years, the 30 days standard deviation of 27.6% is higher, thus worse.

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.'

Using this definition on our asset we see for example:
  • Looking at the downside deviation of 19.2% in the last 5 years of Verisk Analytics, we see it is relatively greater, thus worse in comparison to the benchmark SPY (12%)
  • Compared with SPY (10.4%) in the period of the last 3 years, the downside deviation of 20.4% 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 (0.52) in the period of the last 5 years, the Sharpe Ratio of -0.13 of Verisk Analytics is lower, thus worse.
  • Compared with SPY (1.25) in the period of the last 3 years, the risk / return profile (Sharpe) of -0.25 is lower, thus worse.

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.'

Using this definition on our asset we see for example:
  • Looking at the downside risk / excess return profile of -0.17 in the last 5 years of Verisk Analytics, we see it is relatively lower, thus worse in comparison to the benchmark SPY (0.75)
  • Looking at downside risk / excess return profile in of -0.34 in the period of the last 3 years, we see it is relatively lower, thus worse in comparison to SPY (1.85).

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:
  • The Ulcer Index over 5 years of Verisk Analytics is 21 , which is greater, thus worse compared to the benchmark SPY (8.46 ) in the same period.
  • During the last 3 years, the Ulcer Index is 24 , which is larger, thus worse than the value of 3.22 from the benchmark.

MaxDD:

'Maximum drawdown is defined as the peak-to-trough decline of an investment during a specific period. It is usually quoted as a percentage of the peak value. The maximum drawdown can be calculated based on absolute returns, in order to identify strategies that suffer less during market downturns, such as low-volatility strategies. However, the maximum drawdown can also be calculated based on returns relative to a benchmark index, for identifying strategies that show steady outperformance over time.'

Applying this definition to our asset in some examples:
  • Looking at the maximum drop from peak to valley of -50.8 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)
  • Looking at maximum reduction from previous high in of -50.8 days in the period of the last 3 years, we see it is relatively lower, thus worse in comparison to SPY (-18.8 days).

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 time in days below previous high water mark over 5 years of Verisk Analytics is 396 days, which is smaller, thus better compared to the benchmark SPY (488 days) in the same period.
  • Looking at maximum days below previous high in of 360 days in the period of the last 3 years, we see it is relatively greater, thus worse in comparison to SPY (87 days).

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:
  • The average time in days below previous high water mark over 5 years of Verisk Analytics is 131 days, which is larger, thus worse compared to the benchmark SPY (117 days) in the same period.
  • Compared with SPY (17 days) in the period of the last 3 years, the average days below previous high of 104 days is greater, 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 and do not account for slippage, fees or taxes.