'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.'

Using this definition on our asset we see for example:- The total return over 5 years of Atlassian is 839%, which is greater, thus better compared to the benchmark SPY (122.2%) in the same period.
- Looking at total return in of 337.9% in the period of the last 3 years, we see it is relatively larger, thus better in comparison to SPY (43.6%).

'The compound annual growth rate (CAGR) is a useful measure of growth over multiple time periods. It can be thought of as the growth rate that gets you from the initial investment value to the ending investment value if you assume that the investment has been compounding over the time period.'

Using this definition on our asset we see for example:- The annual performance (CAGR) over 5 years of Atlassian is 56.5%, which is greater, thus better compared to the benchmark SPY (17.3%) in the same period.
- During the last 3 years, the compounded annual growth rate (CAGR) is 63.7%, which is higher, thus better than the value of 12.8% from the benchmark.

'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.'

Which means for our asset as example:- Looking at the volatility of 42.2% in the last 5 years of Atlassian, we see it is relatively larger, thus worse in comparison to the benchmark SPY (18.7%)
- Compared with SPY (22.9%) in the period of the last 3 years, the historical 30 days volatility of 43% is greater, thus worse.

'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:- The downside deviation over 5 years of Atlassian is 28.3%, which is larger, thus worse compared to the benchmark SPY (13.6%) in the same period.
- During the last 3 years, the downside deviation is 29.4%, which is larger, thus worse than the value of 16.8% from the benchmark.

'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.'

Applying this definition to our asset in some examples:- Looking at the Sharpe Ratio of 1.28 in the last 5 years of Atlassian, we see it is relatively larger, thus better in comparison to the benchmark SPY (0.79)
- During the last 3 years, the risk / return profile (Sharpe) is 1.42, which is larger, thus better than the value of 0.45 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.'

Using this definition on our asset we see for example:- Looking at the ratio of annual return and downside deviation of 1.91 in the last 5 years of Atlassian, we see it is relatively larger, thus better in comparison to the benchmark SPY (1.09)
- Compared with SPY (0.62) in the period of the last 3 years, the excess return divided by the downside deviation of 2.08 is higher, thus better.

'Ulcer Index is a method for measuring investment risk that addresses the real concerns of investors, unlike the widely used standard deviation of return. UI is a measure of the depth and duration of drawdowns in prices from earlier highs. Using Ulcer Index instead of standard deviation can lead to very different conclusions about investment risk and risk-adjusted return, especially when evaluating strategies that seek to avoid major declines in portfolio value (market timing, dynamic asset allocation, hedge funds, etc.). The Ulcer Index was originally developed in 1987. Since then, it has been widely recognized and adopted by the investment community. According to Nelson Freeburg, editor of Formula Research, Ulcer Index is “perhaps the most fully realized statistical portrait of risk there is.'

Applying this definition to our asset in some examples:- Looking at the Ulcer Ratio of 9.63 in the last 5 years of Atlassian, we see it is relatively greater, thus worse in comparison to the benchmark SPY (5.59 )
- Compared with SPY (7.15 ) in the period of the last 3 years, the Ulcer Index of 9.62 is higher, thus worse.

'A maximum drawdown is the maximum loss from a peak to a trough of a portfolio, before a new peak is attained. Maximum Drawdown is an indicator of downside risk over a specified time period. It can be used both as a stand-alone measure or as an input into other metrics such as 'Return over Maximum Drawdown' and the Calmar Ratio. Maximum Drawdown is expressed in percentage terms.'

Applying this definition to our asset in some examples:- Compared with the benchmark SPY (-33.7 days) in the period of the last 5 years, the maximum reduction from previous high of -30.2 days of Atlassian is larger, thus better.
- Compared with SPY (-33.7 days) in the period of the last 3 years, the maximum reduction from previous high of -30.2 days is larger, thus better.

'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.'

Applying this definition to our asset in some examples:- The maximum days under water over 5 years of Atlassian is 178 days, which is greater, thus worse compared to the benchmark SPY (139 days) in the same period.
- Looking at maximum days under water in of 112 days in the period of the last 3 years, we see it is relatively lower, thus better in comparison to SPY (139 days).

'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:- The average days under water over 5 years of Atlassian is 33 days, which is higher, thus worse compared to the benchmark SPY (33 days) in the same period.
- Looking at average time in days below previous high water mark in of 23 days in the period of the last 3 years, we see it is relatively lower, thus better in comparison to SPY (45 days).

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 Atlassian 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.