MongoDB (MDB)

TotalReturn:

'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.'

• The total return over 5 years of MongoDB is 12.7%, which is lower, thus worse compared to the benchmark SPY (91.7%) in the same period.
• Looking at total return, or increase in value in of 15.4% in the period of the last 3 years, we see it is relatively lower, thus worse in comparison to SPY (84.4%).

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 2.4% in the last 5 years of MongoDB, we see it is relatively lower, thus worse in comparison to the benchmark SPY (14%)
• During the last 3 years, the annual return (CAGR) is 4.9%, which is lower, thus worse than the value of 22.7% from the benchmark.

Volatility:

'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.'

• Looking at the volatility of 69.6% in the last 5 years of MongoDB, we see it is relatively greater, thus worse in comparison to the benchmark SPY (17%)
• During the last 3 years, the historical 30 days volatility is 62.9%, which is larger, thus worse than the value of 15.1% from the benchmark.

DownVol:

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

• Looking at the downside risk of 45.8% in the last 5 years of MongoDB, we see it is relatively larger, thus worse in comparison to the benchmark SPY (11.7%)
• Looking at downside deviation in of 41.2% in the period of the last 3 years, we see it is relatively greater, thus worse in comparison to SPY (10.1%).

Sharpe:

'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.'

• The risk / return profile (Sharpe) over 5 years of MongoDB is 0, which is lower, thus worse compared to the benchmark SPY (0.67) in the same period.
• During the last 3 years, the Sharpe Ratio is 0.04, which is lower, thus worse than the value of 1.34 from the benchmark.

Sortino:

'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.'

• Compared with the benchmark SPY (0.98) in the period of the last 5 years, the ratio of annual return and downside deviation of 0 of MongoDB is lower, thus worse.
• Compared with SPY (2) in the period of the last 3 years, the downside risk / excess return profile of 0.06 is smaller, thus worse.

Ulcer:

'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.'

• Compared with the benchmark SPY (8.45 ) in the period of the last 5 years, the Ulcer Index of 48 of MongoDB is larger, thus worse.
• Looking at Downside risk index in of 40 in the period of the last 3 years, we see it is relatively higher, thus worse in comparison to SPY (3.5 ).

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.'

• Looking at the maximum DrawDown of -76.5 days in the last 5 years of MongoDB, we see it is relatively smaller, thus worse in comparison to the benchmark SPY (-24.5 days)
• Compared with SPY (-18.8 days) in the period of the last 3 years, the maximum drop from peak to valley of -70.9 days is lower, thus worse.

MaxDuration:

'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.'

• Compared with the benchmark SPY (488 days) in the period of the last 5 years, the maximum time in days below previous high water mark of 1131 days of MongoDB is larger, thus worse.
• Compared with SPY (87 days) in the period of the last 3 years, the maximum days below previous high of 571 days is larger, thus worse.

AveDuration:

'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.'

• Compared with the benchmark SPY (120 days) in the period of the last 5 years, the average days under water of 523 days of MongoDB is higher, thus worse.
• During the last 3 years, the average time in days below previous high water mark is 231 days, which is larger, thus worse than the value of 20 days from the benchmark.