FT Cboe Correlations

XAUG Etf

34.15 0.06 0.18%

The current 90-days correlation between FT Cboe Vest and FT Cboe Vest is 0.89 (i.e., Very poor diversification). The correlation of FT Cboe 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.

FT Cboe Correlation With Market

Poor diversification

The correlation between FT Cboe Vest and DJI is 0.78 (i.e., Poor diversification) for selected investment horizon. Overlapping area represents the amount of risk that can be diversified away by holding FT Cboe Vest and DJI in the same portfolio, assuming nothing else is changed.

Check out Your Current Watchlist to better understand how to build diversified portfolios, which includes a position in FT Cboe Vest. Also, note that the market value of any etf could be closely tied with the direction of predictive economic indicators such as signals in employment.

Moving together with XAUG Etf

0.99	BUFR	First Trust Cboe	Pair Corr
0.99	BUFD	FT Cboe Vest	Pair Corr
0.99	PSEP	Innovator SP 500	Pair Corr
0.98	PJAN	Innovator SP 500	Pair Corr
0.99	PJUL	Innovator SP 500	Pair Corr
1.0	PAUG	Innovator Equity Power	Pair Corr
0.95	DNOV	FT Cboe Vest	Pair Corr
0.99	PMAY	Innovator SP 500	Pair Corr
1.0	PJUN	Innovator SP 500	Pair Corr
0.96	FNGU	MicroSectors FANG Index	Pair Corr
0.84	USD	ProShares Ultra Semi	Pair Corr
0.96	FNGO	MicroSectors FANG Index	Pair Corr
0.8	GBTC	Grayscale Bitcoin Trust	Pair Corr
0.89	TECL	Direxion Daily Technology	Pair Corr
0.97	FNGS	MicroSectors FANG ETN	Pair Corr
0.91	ROM	ProShares Ultra Tech	Pair Corr
0.96	QLD	ProShares Ultra QQQ	Pair Corr
0.75	SMH	VanEck Semiconductor ETF	Pair Corr
0.78	DIS	Walt Disney	Pair Corr
0.87	CAT	Caterpillar Fiscal Year End 3rd of February 2025	Pair Corr
0.66	XOM	Exxon Mobil Corp Sell-off Trend	Pair Corr
0.92	INTC	Intel Fiscal Year End 23rd of January 2025	Pair Corr
0.79	TRV	The Travelers Companies Fiscal Year End 17th of January 2025	Pair Corr
0.94	CSCO	Cisco Systems Aggressive Push	Pair Corr
0.7	JPM	JPMorgan Chase Fiscal Year End 10th of January 2025	Pair Corr
0.84	HPQ	HP Inc	Pair Corr
0.94	AXP	American Express Fiscal Year End 24th of January 2025	Pair Corr
0.82	HD	Home Depot	Pair Corr
0.93	AA	Alcoa Corp Fiscal Year End 15th of January 2025	Pair Corr

Moving against XAUG Etf

0.81	MRK	Merck Company Fiscal Year End 6th of February 2025	Pair Corr
0.57	PFE	Pfizer Inc Aggressive Push	Pair Corr
0.45	PG	Procter Gamble	Pair Corr

Related Correlations Analysis

	META	MSFT	UBER	F	T	A	CRM	JPM	MRK	XOM
META		0.29	0.57	-0.02	0.6	0.02	0.68	0.28	-0.56	0.72	META
MSFT	0.29		0.24	0.12	0.2	-0.02	0.02	-0.17	0.11	-0.18	MSFT
UBER	0.57	0.24		-0.02	0.02	0.26	0.05	-0.1	0.04	0.36	UBER
F	-0.02	0.12	-0.02		0.0	-0.37	0.36	0.62	-0.24	0.29	F
T	0.6	0.2	0.02	0.0		-0.48	0.73	0.49	-0.76	0.39	T
A	0.02	-0.02	0.26	-0.37	-0.48		-0.48	-0.65	0.64	-0.01	A
CRM	0.68	0.02	0.05	0.36	0.73	-0.48		0.83	-0.92	0.68	CRM
JPM	0.28	-0.17	-0.1	0.62	0.49	-0.65	0.83		-0.83	0.51	JPM
MRK	-0.56	0.11	0.04	-0.24	-0.76	0.64	-0.92	-0.83		-0.57	MRK
XOM	0.72	-0.18	0.36	0.29	0.39	-0.01	0.68	0.51	-0.57		XOM
	META	MSFT	UBER	F	T	A	CRM	JPM	MRK	XOM

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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

JPM	+ 0.83	CRM
CRM	+ 0.73	T
XOM	+ 0.72	META
CRM	+ 0.68	META
XOM	+ 0.68	CRM
MRK	+ 0.64	A

High negative correlations

MRK	- 0.92	CRM
MRK	- 0.83	JPM
MRK	- 0.76	T
JPM	- 0.65	A
XOM	- 0.57	MRK
MRK	- 0.56	META

FT Cboe Competition Risk-Adjusted Indicators

There is a big difference between XAUG Etf performing well and FT Cboe ETF 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 FT Cboe'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
META	1.05	0.00	(0.03)	0.12	1.40	(1.14)	2.62	(3.15)	8.02
MSFT	0.88	(0.08)	(0.07)	0.01	1.51	(0.82)	2.09	(1.85)	8.19
UBER	1.60	(0.14)	0.00	(0.02)	0.00	0.00	2.69	(2.44)	20.10
F	1.43	(0.12)	(0.02)	0.04	2.19	(1.43)	2.75	(2.90)	11.72
T	0.92	0.28	0.14	24.43	0.85	(1.04)	2.56	(1.72)	6.47
A	1.14	(0.13)	0.00	(0.12)	0.00	0.00	2.29	(2.42)	9.02
CRM	1.28	0.29	0.25	0.37	0.90	(1.52)	3.18	(1.91)	9.09
JPM	1.12	0.00	0.06	0.12	1.44	(1.17)	2.05	(2.00)	15.87
MRK	0.85	(0.26)	0.00	(1.12)	0.00	0.00	1.73	(2.13)	4.89
XOM	1.03	0.03	(0.01)	0.18	1.21	(1.11)	2.14	(2.09)	5.78

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