Description

MongoDB, Inc. - Class A Common Stock

Statistics (YTD)

What do these metrics mean? [Read More] [Hide]

TotalReturn:

'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.'

Which means for our asset as example:
  • The total return over 5 years of MongoDB is 60.3%, which is smaller, thus worse compared to the benchmark SPY (97.3%) in the same period.
  • During the last 3 years, the total return, or increase in value is -31.6%, which is lower, thus worse than the value of 40.1% from the benchmark.

CAGR:

'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.'

Which means for our asset as example:
  • The annual return (CAGR) over 5 years of MongoDB is 9.9%, which is lower, thus worse compared to the benchmark SPY (14.6%) in the same period.
  • During the last 3 years, the annual performance (CAGR) is -12%, which is lower, thus worse than the value of 12% 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.'

Using this definition on our asset we see for example:
  • Looking at the volatility of 67.5% in the last 5 years of MongoDB, we see it is relatively greater, thus worse in comparison to the benchmark SPY (21%)
  • Looking at historical 30 days volatility in of 70.1% in the period of the last 3 years, we see it is relatively larger, thus worse in comparison to SPY (17.3%).

DownVol:

'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 deviation over 5 years of MongoDB is 44.9%, which is larger, thus worse compared to the benchmark SPY (15%) in the same period.
  • Looking at downside deviation in of 47.6% in the period of the last 3 years, we see it is relatively higher, thus worse in comparison to SPY (12.1%).

Sharpe:

'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 ratio of return and volatility (Sharpe) over 5 years of MongoDB is 0.11, which is lower, thus worse compared to the benchmark SPY (0.58) in the same period.
  • Looking at ratio of return and volatility (Sharpe) in of -0.21 in the period of the last 3 years, we see it is relatively smaller, thus worse in comparison to SPY (0.55).

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.'

Using this definition on our asset we see for example:
  • The ratio of annual return and downside deviation over 5 years of MongoDB is 0.17, which is smaller, thus worse compared to the benchmark SPY (0.8) in the same period.
  • During the last 3 years, the ratio of annual return and downside deviation is -0.3, which is lower, thus worse than the value of 0.78 from the benchmark.

Ulcer:

'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.'

Applying this definition to our asset in some examples:
  • Compared with the benchmark SPY (9.33 ) in the period of the last 5 years, the Ulcer Index of 40 of MongoDB is greater, thus worse.
  • During the last 3 years, the Ulcer Index is 40 , which is greater, thus worse than the value of 8.64 from the benchmark.

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.'

Applying this definition to our asset in some examples:
  • Looking at the maximum drop from peak to valley 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 (-33.7 days)
  • Looking at maximum DrawDown in of -70.1 days in the period of the last 3 years, we see it is relatively smaller, thus worse in comparison to SPY (-22.1 days).

MaxDuration:

'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.'

Which means for our asset as example:
  • The maximum time in days below previous high water mark over 5 years of MongoDB is 806 days, which is higher, thus worse compared to the benchmark SPY (488 days) in the same period.
  • Looking at maximum days under water in of 463 days in the period of the last 3 years, we see it is relatively higher, thus worse in comparison to SPY (325 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.'

Which means for our asset as example:
  • Looking at the average time in days below previous high water mark of 281 days in the last 5 years of MongoDB, we see it is relatively higher, thus worse in comparison to the benchmark SPY (122 days)
  • Compared with SPY (89 days) in the period of the last 3 years, the average time in days below previous high water mark of 186 days is higher, thus worse.

Performance (YTD)

Historical returns have been extended using synthetic data.

Allocations ()

Allocations

Returns (%)

  • 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.