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.'

Applying this definition to our asset in some examples:
  • Looking at the total return of 73.8% in the last 5 years of MongoDB, we see it is relatively lower, thus worse in comparison to the benchmark SPY (97.4%)
  • Looking at total return, or increase in value in of -30.6% in the period of the last 3 years, we see it is relatively lower, thus worse in comparison to SPY (44.7%).

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:
  • Looking at the annual performance (CAGR) of 11.7% in the last 5 years of MongoDB, we see it is relatively smaller, thus worse in comparison to the benchmark SPY (14.6%)
  • Looking at annual performance (CAGR) in of -11.5% in the period of the last 3 years, we see it is relatively lower, thus worse in comparison to SPY (13.2%).

Volatility:

'Volatility is a rate at which the price of a security increases or decreases for a given set of returns. Volatility is measured by calculating the standard deviation of the annualized returns over a given period of time. It shows the range to which the price of a security may increase or decrease. Volatility measures the risk of a security. It is used in option pricing formula to gauge the fluctuations in the returns of the underlying assets. Volatility indicates the pricing behavior of the security and helps estimate the fluctuations that may happen in a short period of time.'

Which means for our asset as example:
  • Looking at the historical 30 days volatility of 67.5% in the last 5 years of MongoDB, we see it is relatively larger, thus worse in comparison to the benchmark SPY (21%)
  • During the last 3 years, the 30 days standard deviation is 70.4%, which is higher, thus worse than the value of 17.4% from the benchmark.

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.'

Using this definition on our asset we see for example:
  • Looking at the downside volatility of 44.9% in the last 5 years of MongoDB, we see it is relatively greater, thus worse in comparison to the benchmark SPY (15%)
  • During the last 3 years, the downside volatility is 47.8%, which is greater, thus worse than the value of 12.1% from the benchmark.

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.'

Applying this definition to our asset in some examples:
  • Looking at the Sharpe Ratio of 0.14 in the last 5 years of MongoDB, we see it is relatively lower, thus worse in comparison to the benchmark SPY (0.58)
  • Looking at risk / return profile (Sharpe) in of -0.2 in the period of the last 3 years, we see it is relatively lower, thus worse in comparison to SPY (0.61).

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.'

Using this definition on our asset we see for example:
  • The excess return divided by the downside deviation over 5 years of MongoDB is 0.21, which is lower, 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 -0.29, which is lower, thus worse than the value of 0.88 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.'

Which means for our asset as example:
  • Compared with the benchmark SPY (9.33 ) in the period of the last 5 years, the Ulcer Ratio of 40 of MongoDB is higher, thus worse.
  • During the last 3 years, the Downside risk index is 39 , which is larger, thus worse than the value of 8.63 from the benchmark.

MaxDD:

'A maximum drawdown is the maximum loss from a peak to a trough of a portfolio, before a new peak is attained. Maximum Drawdown is an indicator of downside risk over a specified time period. It can be used both as a stand-alone measure or as an input into other metrics such as 'Return over Maximum Drawdown' and the Calmar Ratio. Maximum Drawdown is expressed in percentage terms.'

Applying this definition to our asset in some examples:
  • The maximum DrawDown over 5 years of MongoDB is -76.5 days, which is smaller, thus worse compared to the benchmark SPY (-33.7 days) in the same period.
  • During the last 3 years, the maximum drop from peak to valley is -70.1 days, which is lower, thus worse than the value of -22.1 days from the benchmark.

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:
  • 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 797 days of MongoDB is larger, thus worse.
  • Compared with SPY (325 days) in the period of the last 3 years, the maximum days below previous high of 463 days is larger, thus worse.

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.'

Applying this definition to our asset in some examples:
  • Looking at the average days below previous high of 276 days in the last 5 years of MongoDB, we see it is relatively larger, thus worse in comparison to the benchmark SPY (122 days)
  • Looking at average days under water in of 184 days in the period of the last 3 years, we see it is relatively greater, thus worse in comparison to SPY (89 days).

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.