IShares IBoxx Correlations

HYG Etf

USD 80.83 0.22 0.27%

The current 90-days correlation between iShares iBoxx High and iShares iBoxx Investment is 0.69 (i.e., Poor diversification). The correlation of IShares IBoxx 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.

IShares IBoxx Correlation With Market

Poor diversification

The correlation between iShares iBoxx High and DJI is 0.65 (i.e., Poor diversification) for selected investment horizon. Overlapping area represents the amount of risk that can be diversified away by holding iShares iBoxx High and DJI in the same portfolio, assuming nothing else is changed.

Build AI portfolio with IShares Etf

Check out Risk vs Return Analysis to better understand how to build diversified portfolios, which includes a position in iShares iBoxx High. Also, note that the market value of any etf could be closely tied with the direction of predictive economic indicators such as signals in interest.

Moving together with IShares Etf

0.97	USHY	iShares Broad USD	Pair Corr
1.0	JNK	SPDR Bloomberg High	Pair Corr
0.65	SHYG	iShares 0 5	Pair Corr
0.75	HYLB	Xtrackers USD High	Pair Corr
0.65	SJNK	SPDR Bloomberg Short	Pair Corr
0.66	ANGL	VanEck Fallen Angel	Pair Corr
0.98	FALN	iShares Fallen Angels	Pair Corr
0.96	HYLS	First Trust Tactical	Pair Corr
0.78	HYDW	Xtrackers Low Beta	Pair Corr
0.92	USD	ProShares Ultra Semi	Pair Corr
0.61	GBTC	Grayscale Bitcoin Trust Potential Growth	Pair Corr
0.88	DFEN	Direxion Daily Aerospace	Pair Corr
0.85	ETHE	Grayscale Ethereum Trust	Pair Corr
0.84	DUSL	Direxion Daily Indus	Pair Corr
0.89	IJT	iShares SP Small	Pair Corr
0.7	GSJY	Goldman Sachs ActiveBeta	Pair Corr
0.83	JNJ	Johnson Johnson	Pair Corr
0.84	MSFT	Microsoft	Pair Corr
0.74	CSCO	Cisco Systems	Pair Corr
0.75	DD	Dupont De Nemours	Pair Corr
0.75	BA	Boeing	Pair Corr
0.69	PFE	Pfizer Inc	Pair Corr
0.91	JPM	JPMorgan Chase	Pair Corr
0.81	BAC	Bank of America	Pair Corr
0.75	MMM	3M Company	Pair Corr
0.82	GE	GE Aerospace	Pair Corr

Moving against IShares Etf

0.63	FNGU	MicroSectors FANG Index Symbol Change	Pair Corr
0.57	IBM	International Business	Pair Corr
0.55	PG	Procter Gamble	Pair Corr
0.51	KO	Coca Cola	Pair Corr

Related Correlations Analysis

	META	MSFT	UBER	F	T	A	CRM	JPM	MRK	XOM
META		0.8	0.54	0.6	0.49	0.2	-0.72	0.64	0.41	0.04	META
MSFT	0.8		0.53	0.64	0.22	0.12	-0.56	0.85	0.49	0.22	MSFT
UBER	0.54	0.53		0.87	0.5	0.55	-0.22	0.7	0.7	0.38	UBER
F	0.6	0.64	0.87		0.55	0.6	-0.4	0.8	0.83	0.5	F
T	0.49	0.22	0.5	0.55		0.63	-0.43	0.39	0.64	0.11	T
A	0.2	0.12	0.55	0.6	0.63		0.05	0.41	0.67	0.47	A
CRM	-0.72	-0.56	-0.22	-0.4	-0.43	0.05		-0.34	-0.34	0.1	CRM
JPM	0.64	0.85	0.7	0.8	0.39	0.41	-0.34		0.64	0.45	JPM
MRK	0.41	0.49	0.7	0.83	0.64	0.67	-0.34	0.64		0.48	MRK
XOM	0.04	0.22	0.38	0.5	0.11	0.47	0.1	0.45	0.48		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

F	+ 0.87	UBER
JPM	+ 0.85	MSFT
MRK	+ 0.83	F
MSFT	+ 0.8	META
JPM	+ 0.8	F
JPM	+ 0.7	UBER

High negative correlations

CRM	- 0.72	META
CRM	- 0.56	MSFT
CRM	- 0.43	T
CRM	- 0.4	F
MRK	- 0.34	CRM
JPM	- 0.34	CRM

IShares IBoxx Competition Risk-Adjusted Indicators

There is a big difference between IShares Etf performing well and IShares IBoxx 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 IShares IBoxx'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	1.34	0.08	0.05	0.20	1.20	(1.66)	3.15	(2.27)	14.28
MSFT	0.68	0.17	0.04	(0.45)	0.57	(0.78)	1.58	(1.42)	5.71
UBER	1.35	0.08	0.03	0.24	1.43	(1.43)	2.72	(2.02)	11.37
F	1.20	0.13	0.10	0.21	1.29	(1.25)	2.55	(2.20)	7.46
T	0.76	0.04	(0.03)	0.20	0.94	(0.78)	1.75	(1.96)	5.41
A	1.39	0.05	0.07	0.14	1.56	(1.46)	3.24	(2.46)	9.19
CRM	1.22	0.00	0.00	0.11	0.00	0.00	2.63	(2.94)	6.27
JPM	0.80	0.23	0.08	(0.57)	0.83	(0.89)	1.78	(1.36)	5.19
MRK	1.19	0.07	0.04	0.18	1.41	(1.20)	2.90	(2.36)	7.79
XOM	1.01	0.17	0.03	(0.89)	1.32	(1.01)	2.14	(2.42)	6.25

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