'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.'

Which means for our asset as example:- The total return, or performance over 5 years of Datadog is %, which is lower, thus worse compared to the benchmark SPY (67.1%) in the same period.
- Looking at total return, or performance in of 95.4% in the period of the last 3 years, we see it is relatively higher, thus better in comparison to SPY (61.5%).

'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.'

Which means for our asset as example:- The annual performance (CAGR) over 5 years of Datadog is %, which is lower, thus worse compared to the benchmark SPY (10.8%) in the same period.
- Looking at compounded annual growth rate (CAGR) in of 25% in the period of the last 3 years, we see it is relatively higher, thus better in comparison to SPY (17.3%).

'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.'

Applying this definition to our asset in some examples:- Compared with the benchmark SPY (21.4%) in the period of the last 5 years, the volatility of % of Datadog is lower, thus better.
- Compared with SPY (20%) in the period of the last 3 years, the 30 days standard deviation of 63.6% is greater, thus worse.

'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.'

Which means for our asset as example:- Compared with the benchmark SPY (15.4%) in the period of the last 5 years, the downside deviation of % of Datadog is lower, thus better.
- Compared with SPY (13.9%) in the period of the last 3 years, the downside volatility of 42% is greater, thus worse.

'The Sharpe ratio (also known as the Sharpe index, the Sharpe measure, and the reward-to-variability ratio) is a way to examine the performance of an investment by adjusting for its risk. The ratio measures the excess return (or risk premium) per unit of deviation in an investment asset or a trading strategy, typically referred to as risk, named after William F. Sharpe.'

Using this definition on our asset we see for example:- Looking at the ratio of return and volatility (Sharpe) of in the last 5 years of Datadog, we see it is relatively lower, thus worse in comparison to the benchmark SPY (0.39)
- During the last 3 years, the risk / return profile (Sharpe) is 0.35, which is smaller, thus worse than the value of 0.74 from the benchmark.

'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:- Looking at the downside risk / excess return profile of in the last 5 years of Datadog, we see it is relatively lower, thus worse in comparison to the benchmark SPY (0.54)
- During the last 3 years, the downside risk / excess return profile is 0.54, which is smaller, thus worse than the value of 1.06 from the benchmark.

'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:- The Ulcer Ratio over 5 years of Datadog is , which is lower, thus better compared to the benchmark SPY (9.21 ) in the same period.
- Looking at Ulcer Index in of 34 in the period of the last 3 years, we see it is relatively larger, thus worse in comparison to SPY (9.87 ).

'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.'

Using this definition on our asset we see for example:- Compared with the benchmark SPY (-33.7 days) in the period of the last 5 years, the maximum DrawDown of days of Datadog is lower, thus worse.
- During the last 3 years, the maximum DrawDown is -67.7 days, which is smaller, thus worse than the value of -24.5 days from the benchmark.

'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.'

Which means for our asset as example:- The maximum time in days below previous high water mark over 5 years of Datadog is days, which is lower, thus better compared to the benchmark SPY (311 days) in the same period.
- During the last 3 years, the maximum days under water is 348 days, which is higher, thus worse than the value of 311 days from the benchmark.

'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 (66 days) in the period of the last 5 years, the average time in days below previous high water mark of days of Datadog is lower, thus better.
- Compared with SPY (82 days) in the period of the last 3 years, the average days below previous high of 106 days is larger, thus worse.

Historical returns have been extended using synthetic data.
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- Note that yearly returns do not equal the sum of monthly returns due to compounding.
- Performance results of Datadog 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.