MongoDB Correlations

MDB Stock

USD 384.82 14.94 3.74%

The current 90-days correlation between MongoDB and CyberArk Software is 0.42 (i.e., Very weak diversification). The correlation of MongoDB is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.

MongoDB Correlation With Market

Modest diversification

The correlation between MongoDB and DJI is 0.25 (i.e., Modest diversification) for selected investment horizon. Overlapping area represents the amount of risk that can be diversified away by holding MongoDB and DJI in the same portfolio, assuming nothing else is changed.

Build AI portfolio with MongoDB Stock

Check out Correlation Analysis to better understand how to build diversified portfolios, which includes a position in MongoDB. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as signals in american community survey.

For information on how to trade MongoDB Stock refer to our How to Trade MongoDB Stock guide.

Moving together with MongoDB Stock

0.7	DOCN	DigitalOcean Holdings Downward Rally	Pair Corr
0.64	TCX	Tucows Inc	Pair Corr
0.87	GDYN	Grid Dynamics Holdings Downward Rally	Pair Corr
0.81	TWLO	Twilio Inc	Pair Corr

Moving against MongoDB Stock

0.78	FCT	Firstwave Cloud Tech	Pair Corr
0.72	NXT	NEXTDC	Pair Corr
0.63	MP1	Megaport	Pair Corr
0.62	SYS	SysGroup PLC	Pair Corr
0.59	MAPSW	WM Technology	Pair Corr
0.58	900901	Inesa Intelligent Tech	Pair Corr
0.53	WIX	WixCom	Pair Corr
0.46	VRRM	Verra Mobility Corp	Pair Corr
0.44	PSFE	Paysafe	Pair Corr
0.41	VRSN	VeriSign	Pair Corr
0.41	300017	Wangsu Science Tech	Pair Corr
0.39	GDDY	Godaddy	Pair Corr
0.78	AMOD	Alpha Modus Holdings	Pair Corr
0.73	DXN	DXN	Pair Corr
0.64	SNOW	Snowflake	Pair Corr
0.56	CSAI	Cloudastructure Class	Pair Corr
0.55	300541	Beijing Advanced Digital	Pair Corr
0.52	CRWV	CoreWeave Class A Aggressive Push	Pair Corr
0.5	FSTF	First State Financial	Pair Corr
0.38	CORZ	Core Scientific Common Aggressive Push	Pair Corr
0.38	000034	Digital China Group	Pair Corr
0.35	BBAI	BigBearai Holdings	Pair Corr

Related Correlations Analysis

	CYBR	SMCI	IOT	SNDK	VRSN	TER	AFRM	ZM	CRDO	CHKP
CYBR		0.84	0.41	-0.4	-0.02	-0.55	0.02	-0.2	0.35	0.77	CYBR
SMCI	0.84		0.31	-0.61	0.22	-0.74	-0.09	-0.33	0.17	0.5	SMCI
IOT	0.41	0.31		-0.54	-0.14	-0.24	-0.29	0.44	0.45	0.59	IOT
SNDK	-0.4	-0.61	-0.54		-0.17	0.81	0.41	0.02	-0.08	-0.27	SNDK
VRSN	-0.02	0.22	-0.14	-0.17		-0.41	-0.14	-0.39	-0.18	-0.13	VRSN
TER	-0.55	-0.74	-0.24	0.81	-0.41		0.35	0.43	0.12	-0.29	TER
AFRM	0.02	-0.09	-0.29	0.41	-0.14	0.35		0.34	-0.19	0.1	AFRM
ZM	-0.2	-0.33	0.44	0.02	-0.39	0.43	0.34		0.2	0.12	ZM
CRDO	0.35	0.17	0.45	-0.08	-0.18	0.12	-0.19	0.2		0.33	CRDO
CHKP	0.77	0.5	0.59	-0.27	-0.13	-0.29	0.1	0.12	0.33		CHKP
	CYBR	SMCI	IOT	SNDK	VRSN	TER	AFRM	ZM	CRDO	CHKP

Please upgrade your account to get full access to Macroaxis premium features

Correlation Matchups

Over a given time period, the two securities move together when the Correlation Coefficient is positive. Conversely, the two assets move in opposite directions when the Correlation Coefficient is negative. Determining your positions' relationship to each other is valuable for analyzing and projecting your portfolio's future expected return and risk.

High positive correlations

SMCI	+ 0.84	CYBR
TER	+ 0.81	SNDK
CHKP	+ 0.77	CYBR
CHKP	+ 0.59	IOT
CHKP	+ 0.5	SMCI
CRDO	+ 0.45	IOT

High negative correlations

TER	- 0.74	SMCI
SNDK	- 0.61	SMCI
TER	- 0.55	CYBR
SNDK	- 0.54	IOT
TER	- 0.41	VRSN
SNDK	- 0.4	CYBR

Risk-Adjusted Indicators

There is a big difference between MongoDB Stock performing well and MongoDB Company doing well as a business compared to the competition. There are so many exceptions to the norm that investors cannot definitively determine what's good or bad unless they analyze MongoDB's multiple risk-adjusted performance indicators across the competitive landscape. These indicators are quantitative in nature and help investors forecast volatility and risk-adjusted expected returns across various positions.

	Mean Deviation	Jensen Alpha	Sortino Ratio	Treynor Ratio	Semi Deviation	Expected Shortfall	Potential Upside	Value @Risk	Maximum Drawdown
CYBR	1.23	(0.18)	0.00	(0.19)	0.00	0.00	1.92	(2.43)	8.38
SMCI	2.88	(0.86)	0.00	(0.45)	0.00	0.00	5.77	(6.60)	18.12
IOT	2.23	(0.33)	0.00	(0.12)	0.00	0.00	4.36	(4.37)	17.99
SNDK	5.65	1.78	0.30	0.53	5.36	(6.85)	15.31	(7.88)	36.75
VRSN	1.04	(0.14)	0.00	(0.16)	0.00	0.00	1.99	(2.77)	7.38
TER	2.52	0.64	0.24	0.39	2.26	(2.82)	6.80	(4.05)	27.80
AFRM	2.99	(0.14)	(0.01)	0.01	3.34	(3.56)	6.16	(5.46)	18.92
ZM	1.41	(0.03)	(0.01)	0.04	1.79	(1.47)	2.49	(3.14)	13.95
CRDO	4.00	0.24	0.06	0.21	4.38	(4.35)	10.04	(6.85)	23.45
CHKP	1.33	(0.16)	0.00	(0.09)	0.00	0.00	2.06	(2.74)	9.38

MongoDB Corporate Management

Andrew Stephens	General Secretary	Profile
Paul Capombassis	Chief Officer	Profile
May Petry	Chief Officer	Profile
Michael Berry	Chief Officer	Profile
Jess Lubert	Vice Relations	Profile

Macroaxis helps investors of all levels and skills to maximize the upside of all their holdings and minimize the risk associated with market volatility, economic swings, and company-specific events. View terms and conditions

Feedback Blog

Made with optimal in San Francisco

2026 Macroaxis LLC