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.'

• Looking at the total return, or performance of 11.6% in the last 5 years of MongoDB, we see it is relatively lower, thus worse in comparison to the benchmark SPY (92.4%)
• During the last 3 years, the total return, or performance is 14.9%, which is lower, thus worse than the value of 86.7% from the benchmark.

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.'

• The annual return (CAGR) over 5 years of MongoDB is 2.2%, which is lower, thus worse compared to the benchmark SPY (14%) in the same period.
• Compared with SPY (23.3%) in the period of the last 3 years, the compounded annual growth rate (CAGR) of 4.8% is lower, thus worse.

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.'

• The 30 days standard deviation over 5 years of MongoDB is 69.9%, which is greater, thus worse compared to the benchmark SPY (17.1%) in the same period.
• Looking at 30 days standard deviation in of 63.3% in the period of the last 3 years, we see it is relatively higher, thus worse in comparison to SPY (15.1%).

DownVol:

'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.'

• Compared with the benchmark SPY (11.7%) in the period of the last 5 years, the downside volatility of 45.9% of MongoDB is higher, thus worse.
• Looking at downside deviation in of 41.4% 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 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.'

• Compared with the benchmark SPY (0.68) in the period of the last 5 years, the risk / return profile (Sharpe) of 0 of MongoDB is lower, thus worse.
• During the last 3 years, the risk / return profile (Sharpe) is 0.04, which is lower, thus worse than the value of 1.37 from the benchmark.

Sortino:

'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.'

• Compared with the benchmark SPY (0.98) in the period of the last 5 years, the ratio of annual return and downside deviation of -0.01 of MongoDB is lower, thus worse.
• During the last 3 years, the ratio of annual return and downside deviation is 0.05, which is lower, thus worse than the value of 2.06 from the benchmark.

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.'

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

MaxDD:

'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.'

• The maximum drop from peak to valley over 5 years of MongoDB is -76.5 days, which is smaller, thus worse compared to the benchmark SPY (-24.5 days) in the same period.
• During the last 3 years, the maximum drop from peak to valley is -70.9 days, which is lower, thus worse than the value of -18.8 days from the benchmark.

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.'

• The maximum days under water over 5 years of MongoDB is 1135 days, which is larger, thus worse compared to the benchmark SPY (488 days) in the same period.
• Looking at maximum days under water in of 575 days in the period of the last 3 years, we see it is relatively larger, thus worse in comparison to SPY (87 days).

AveDuration:

'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.'

• Compared with the benchmark SPY (120 days) in the period of the last 5 years, the average days below previous high of 525 days of MongoDB is larger, thus worse.
• During the last 3 years, the average days under water is 233 days, which is greater, thus worse than the value of 20 days from the benchmark.