Datadog (DDOG)

TotalReturn:

'Total return is the amount of value an investor earns from a security over a specific period, typically one year, when all distributions are reinvested. Total return is expressed as a percentage of the amount invested. For example, a total return of 20% means the security increased by 20% of its original value due to a price increase, distribution of dividends (if a stock), coupons (if a bond) or capital gains (if a fund). Total return is a strong measure of an investment’s overall performance.'

• Looking at the total return of % in the last 5 years of Datadog, we see it is relatively lower, thus worse in comparison to the benchmark SPY (81.5%)
• During the last 3 years, the total return, or performance is %, which is lower, thus worse than the value of 48.1% from the benchmark.

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.'

• Looking at the annual performance (CAGR) of % in the last 5 years of Datadog, we see it is relatively lower, thus worse in comparison to the benchmark SPY (12.7%)
• Looking at compounded annual growth rate (CAGR) in of % in the period of the last 3 years, we see it is relatively smaller, thus worse in comparison to SPY (14%).

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.'

• The historical 30 days volatility over 5 years of Datadog is %, which is lower, thus better compared to the benchmark SPY (20.5%) in the same period.
• Compared with SPY (23.8%) in the period of the last 3 years, the 30 days standard deviation of % is smaller, thus better.

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.'

• Looking at the downside deviation of % in the last 5 years of Datadog, we see it is relatively lower, thus better in comparison to the benchmark SPY (15%)
• Compared with SPY (17.3%) in the period of the last 3 years, the downside risk of % is lower, thus better.

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.'

• The ratio of return and volatility (Sharpe) over 5 years of Datadog is , which is lower, thus worse compared to the benchmark SPY (0.5) in the same period.
• During the last 3 years, the risk / return profile (Sharpe) is , which is lower, thus worse than the value of 0.48 from the benchmark.

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.'

• Compared with the benchmark SPY (0.68) in the period of the last 5 years, the downside risk / excess return profile of of Datadog is lower, thus worse.
• During the last 3 years, the downside risk / excess return profile is , which is lower, thus worse than the value of 0.66 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.'

• Looking at the Ulcer Index of in the last 5 years of Datadog, we see it is relatively lower, thus better in comparison to the benchmark SPY (7.13 )
• Looking at Downside risk index in of in the period of the last 3 years, we see it is relatively lower, thus better in comparison to SPY (8.25 ).

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.'

• The maximum DrawDown over 5 years of Datadog is days, which is greater, thus better compared to the benchmark SPY (-33.7 days) in the same period.
• During the last 3 years, the maximum DrawDown is days, which is larger, 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) in days.'

• The maximum days under water over 5 years of Datadog is days, which is lower, thus better compared to the benchmark SPY (150 days) in the same period.
• Looking at maximum days under water in of days in the period of the last 3 years, we see it is relatively lower, thus better in comparison to SPY (150 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.'

• Compared with the benchmark SPY (41 days) in the period of the last 5 years, the average days below previous high of days of Datadog is lower, thus better.
• During the last 3 years, the average days below previous high is days, which is lower, thus better than the value of 36 days from the benchmark.