'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.'

Applying this definition to our asset in some examples:- Looking at the total return, or increase in value of 130% in the last 5 years of MongoDB, we see it is relatively higher, thus better in comparison to the benchmark SPY (109.2%)
- During the last 3 years, the total return, or increase in value is -49.2%, which is lower, thus worse than the value of 33.3% from the benchmark.

'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:- The annual return (CAGR) over 5 years of MongoDB is 18.2%, which is larger, thus better compared to the benchmark SPY (15.9%) in the same period.
- Looking at compounded annual growth rate (CAGR) in of -20.2% in the period of the last 3 years, we see it is relatively smaller, thus worse in comparison to SPY (10.1%).

'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:- The volatility over 5 years of MongoDB is 66.8%, which is greater, thus worse compared to the benchmark SPY (20.9%) in the same period.
- Looking at 30 days standard deviation in of 71.2% in the period of the last 3 years, we see it is relatively greater, thus worse in comparison to SPY (17.6%).

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

Which means for our asset as example:- Looking at the downside risk of 44.1% in the last 5 years of MongoDB, we see it is relatively higher, thus worse in comparison to the benchmark SPY (14.9%)
- Looking at downside risk in of 48.2% in the period of the last 3 years, we see it is relatively larger, thus worse in comparison to SPY (12.3%).

'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.'

Which means for our asset as example:- The risk / return profile (Sharpe) over 5 years of MongoDB is 0.23, which is lower, thus worse compared to the benchmark SPY (0.64) in the same period.
- During the last 3 years, the risk / return profile (Sharpe) is -0.32, which is lower, thus worse than the value of 0.43 from the benchmark.

'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:- The downside risk / excess return profile over 5 years of MongoDB is 0.35, which is lower, thus worse compared to the benchmark SPY (0.9) in the same period.
- Compared with SPY (0.62) in the period of the last 3 years, the downside risk / excess return profile of -0.47 is smaller, thus worse.

'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.'

Using this definition on our asset we see for example:- The Downside risk index over 5 years of MongoDB is 39 , which is larger, thus worse compared to the benchmark SPY (9.32 ) in the same period.
- Looking at Ulcer Ratio in of 48 in the period of the last 3 years, we see it is relatively greater, thus worse in comparison to SPY (10 ).

'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:- Looking at the maximum reduction from previous high of -76.5 days in the last 5 years of MongoDB, we see it is relatively lower, thus worse in comparison to the benchmark SPY (-33.7 days)
- During the last 3 years, the maximum reduction from previous high is -76.5 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). 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'

Using this definition on our asset we see for example:- Compared with the benchmark SPY (488 days) in the period of the last 5 years, the maximum days below previous high of 749 days of MongoDB is higher, thus worse.
- Compared with SPY (488 days) in the period of the last 3 years, the maximum days below previous high of 749 days is greater, thus worse.

'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:- Compared with the benchmark SPY (123 days) in the period of the last 5 years, the average days below previous high of 247 days of MongoDB is greater, thus worse.
- Looking at average time in days below previous high water mark in of 373 days in the period of the last 3 years, we see it is relatively higher, thus worse in comparison to SPY (176 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 MongoDB are hypothetical and do not account for slippage, fees or taxes.