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 performance over 5 years of Verisk Analytics is 17.1%, which is smaller, thus worse compared to the benchmark SPY (102.5%) in the same period.
  • During the last 3 years, the total return, or performance is 24.8%, which is smaller, thus worse than the value of 74.7% 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.'

Using this definition on our asset we see for example:
  • Compared with the benchmark SPY (15.2%) in the period of the last 5 years, the annual return (CAGR) of 3.2% of Verisk Analytics is smaller, thus worse.
  • Looking at compounded annual growth rate (CAGR) in of 7.7% in the period of the last 3 years, we see it is relatively smaller, thus worse in comparison to SPY (20.6%).

Volatility:

'Volatility is a statistical measure of the dispersion of returns for a given security or market index. Volatility can either be measured by using the standard deviation or variance between returns from that same security or market index. Commonly, the higher the volatility, the riskier the security. In the securities markets, volatility is often associated with big swings in either direction. For example, when the stock market rises and falls more than one percent over a sustained period of time, it is called a 'volatile' market.'

Applying this definition to our asset in some examples:
  • Looking at the volatility of 23.1% in the last 5 years of Verisk Analytics, we see it is relatively larger, thus worse in comparison to the benchmark SPY (17.1%)
  • During the last 3 years, the volatility is 21.6%, which is greater, thus worse than the value of 15.6% 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 (11.8%) in the period of the last 5 years, the downside risk of 17.3% of Verisk Analytics is higher, thus worse.
  • Compared with SPY (10.4%) in the period of the last 3 years, the downside risk of 15.9% is higher, 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 (0.74) in the period of the last 5 years, the Sharpe Ratio of 0.03 of Verisk Analytics is smaller, thus worse.
  • Looking at ratio of return and volatility (Sharpe) in of 0.24 in the period of the last 3 years, we see it is relatively lower, thus worse in comparison to SPY (1.16).

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:
  • Looking at the downside risk / excess return profile of 0.04 in the last 5 years of Verisk Analytics, we see it is relatively smaller, thus worse in comparison to the benchmark SPY (1.08)
  • Compared with SPY (1.73) in the period of the last 3 years, the downside risk / excess return profile of 0.33 is smaller, thus worse.

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 (8.42 ) in the period of the last 5 years, the Ulcer Ratio of 13 of Verisk Analytics is larger, thus worse.
  • Looking at Ulcer Ratio in of 9.14 in the period of the last 3 years, we see it is relatively larger, thus worse in comparison to SPY (3.63 ).

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:
  • Compared with the benchmark SPY (-24.5 days) in the period of the last 5 years, the maximum reduction from previous high of -35.1 days of Verisk Analytics is lower, thus worse.
  • Compared with SPY (-18.8 days) in the period of the last 3 years, the maximum drop from peak to valley of -35.1 days is smaller, 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'

Which means for our asset as example:
  • Compared with the benchmark SPY (488 days) in the period of the last 5 years, the maximum days under water of 396 days of Verisk Analytics is smaller, thus better.
  • During the last 3 years, the maximum days below previous high is 123 days, which is greater, thus worse than the value of 87 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.'

Applying this definition to our asset in some examples:
  • Looking at the average days under water of 98 days in the last 5 years of Verisk Analytics, we see it is relatively lower, thus better in comparison to the benchmark SPY (120 days)
  • Looking at average days under water in of 31 days in the period of the last 3 years, we see it is relatively greater, thus worse in comparison to SPY (21 days).

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.