Cambria Fixed Correlations

CFIT Etf

25.24 0.04 0.16%

The current 90-days correlation between Cambria Fixed Income and MFS Active Core is 0.54 (i.e., Very weak diversification). The correlation of Cambria Fixed 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. If the correlation is 0, the equities are not correlated; they are entirely random.

Cambria Fixed Correlation With Market

Poor diversification

The correlation between Cambria Fixed Income and DJI is 0.72 (i.e., Poor diversification) for selected investment horizon. Overlapping area represents the amount of risk that can be diversified away by holding Cambria Fixed Income and DJI in the same portfolio, assuming nothing else is changed.

Build AI portfolio with Cambria Etf

Check out Trending Equities to better understand how to build diversified portfolios, which includes a position in Cambria Fixed Income. Also, note that the market value of any etf could be closely tied with the direction of predictive economic indicators such as signals in gross domestic product.

Moving together with Cambria Etf

0.69	VUG	Vanguard Growth Index	Pair Corr
0.64	VO	Vanguard Mid Cap	Pair Corr
0.72	VWO	Vanguard FTSE Emerging	Pair Corr
0.62	TOT	Advisor Managed Port	Pair Corr
0.65	EMC	Global X Funds	Pair Corr
0.66	UCRD	VictoryShares ESG	Pair Corr
0.66	QQQM	Invesco NASDAQ 100	Pair Corr
0.73	QQH	HCM Defender 100	Pair Corr
0.63	FFLG	Fidelity Covington Trust Low Volatility	Pair Corr
0.66	AGEM	abrdn Emerging Markets	Pair Corr

Related Correlations Analysis

	MFSB	MGOV	VGIT	VGLT	VGMS	VGSH	VGVT	DUKZ	DYFI
MFSB		0.83	0.91	0.6	0.68	0.72	0.94	0.73	0.5	MFSB
MGOV	0.83		0.92	0.31	0.77	0.89	0.92	0.4	0.38	MGOV
VGIT	0.91	0.92		0.44	0.74	0.86	0.97	0.46	0.43	VGIT
VGLT	0.6	0.31	0.44		-0.12	-0.03	0.55	0.79	-0.17	VGLT
VGMS	0.68	0.77	0.74	-0.12		0.91	0.7	0.19	0.74	VGMS
VGSH	0.72	0.89	0.86	-0.03	0.91		0.8	0.16	0.56	VGSH
VGVT	0.94	0.92	0.97	0.55	0.7	0.8		0.57	0.38	VGVT
DUKZ	0.73	0.4	0.46	0.79	0.19	0.16	0.57		0.25	DUKZ
DYFI	0.5	0.38	0.43	-0.17	0.74	0.56	0.38	0.25		DYFI
	MFSB	MGOV	VGIT	VGLT	VGMS	VGSH	VGVT	DUKZ	DYFI

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

VGVT	+ 0.97	VGIT
VGVT	+ 0.94	MFSB
VGIT	+ 0.92	MGOV
VGVT	+ 0.92	MGOV
VGIT	+ 0.91	MFSB
VGSH	+ 0.91	VGMS

High negative correlations

DYFI	- 0.17	VGLT
VGMS	- 0.12	VGLT
VGSH	- 0.03	VGLT

Cambria Fixed Constituents Risk-Adjusted Indicators

There is a big difference between Cambria Etf performing well and Cambria Fixed 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 Cambria Fixed'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
MFSB	0.14	0.00	(0.39)	0.10	0.09	(0.16)	0.28	(0.24)	0.71
MGOV	0.20	0.02	(0.22)	0.83	0.14	(0.23)	0.39	(0.44)	1.08
VGIT	0.14	0.00	(0.36)	0.39	0.12	(0.15)	0.29	(0.23)	0.96
VGLT	0.36	(0.01)	(0.16)	(0.18)	0.47	(0.36)	0.74	(0.86)	2.55
VGMS	0.12	0.01	(0.38)	(2.04)	0.00	(0.14)	0.25	(0.23)	0.71
VGSH	0.05	0.01	(0.99)	(1.27)	0.00	(0.06)	0.12	(0.09)	0.36
VGVT	0.13	0.01	(0.35)	0.40	0.10	(0.14)	0.22	(0.27)	1.00
DUKZ	0.16	(0.01)	(0.35)	(0.01)	0.17	(0.18)	0.32	(0.32)	1.07
DYFI	0.10	(0.01)	(0.48)	(0.02)	0.09	(0.11)	0.18	(0.22)	0.52

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