'The total return on a portfolio of investments takes into account not only the capital appreciation on the portfolio, but also the income received on the portfolio. The income typically consists of interest, dividends, and securities lending fees. This contrasts with the price return, which takes into account only the capital gain on an investment.'

Using this definition on our asset we see for example:- Looking at the total return, or performance of 518.6% in the last 5 years of Atlassian, we see it is relatively greater, thus better in comparison to the benchmark SPY (60.7%)
- Looking at total return, or increase in value in of 59.4% in the period of the last 3 years, we see it is relatively larger, thus better in comparison to SPY (29.5%).

'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.'

Applying this definition to our asset in some examples:- Compared with the benchmark SPY (10%) in the period of the last 5 years, the annual performance (CAGR) of 44% of Atlassian is greater, thus better.
- Looking at annual return (CAGR) in of 16.8% in the period of the last 3 years, we see it is relatively higher, thus better in comparison to SPY (9%).

'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:- Compared with the benchmark SPY (20.8%) in the period of the last 5 years, the volatility of 50.5% of Atlassian is higher, thus worse.
- Looking at volatility in of 53.7% in the period of the last 3 years, we see it is relatively greater, thus worse in comparison to SPY (24%).

'The downside volatility is similar to the volatility, or standard deviation, but only takes losing/negative periods into account.'

Using this definition on our asset we see for example:- The downside risk over 5 years of Atlassian is 33.2%, which is higher, thus worse compared to the benchmark SPY (15.3%) in the same period.
- Compared with SPY (17.6%) in the period of the last 3 years, the downside deviation of 35.5% is greater, thus worse.

'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.'

Using this definition on our asset we see for example:- Looking at the risk / return profile (Sharpe) of 0.82 in the last 5 years of Atlassian, we see it is relatively greater, thus better in comparison to the benchmark SPY (0.36)
- Looking at ratio of return and volatility (Sharpe) in of 0.27 in the period of the last 3 years, we see it is relatively greater, thus better in comparison to SPY (0.27).

'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 1.25 in the last 5 years of Atlassian, we see it is relatively higher, thus better in comparison to the benchmark SPY (0.49)
- Compared with SPY (0.37) in the period of the last 3 years, the excess return divided by the downside deviation of 0.4 is greater, thus better.

'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 (7.52 ) in the period of the last 5 years, the Downside risk index of 20 of Atlassian is greater, thus worse.
- Compared with SPY (8.81 ) in the period of the last 3 years, the Ulcer Ratio of 24 is higher, thus worse.

'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.'

Which means for our asset as example:- Compared with the benchmark SPY (-33.7 days) in the period of the last 5 years, the maximum reduction from previous high of -64.5 days of Atlassian is lower, thus worse.
- Compared with SPY (-33.7 days) in the period of the last 3 years, the maximum drop from peak to valley of -64.5 days is lower, thus worse.

'The Maximum 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. It is the length of time the account was in the Max Drawdown. A Max Drawdown measures a retrenchment from when an equity curve reaches a new high. It’s the maximum an account lost during that retrenchment. This method is applied because a valley can’t be measured until a new high occurs. Once the new high is reached, the percentage change from the old high to the bottom of the largest trough is recorded.'

Which means for our asset as example:- Looking at the maximum days under water of 226 days in the last 5 years of Atlassian, we see it is relatively higher, thus worse in comparison to the benchmark SPY (182 days)
- During the last 3 years, the maximum days under water is 226 days, which is higher, thus worse than the value of 182 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 (45 days) in the period of the last 5 years, the average time in days below previous high water mark of 41 days of Atlassian is lower, thus better.
- During the last 3 years, the average time in days below previous high water mark is 53 days, which is greater, thus worse than the value of 43 days from the benchmark.

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.