JPMorgan ETFs Correlations

JUHC Etf

54.49 0.11 0.20%

The current 90-days correlation between JPMorgan ETFs ICAV and UBSFund Solutions MSCI is 0.08 (i.e., Significant diversification). The correlation of JPMorgan ETFs 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.

JPMorgan ETFs Correlation With Market

Weak diversification

The correlation between JPMorgan ETFs ICAV and DJI is 0.35 (i.e., Weak diversification) for selected investment horizon. Overlapping area represents the amount of risk that can be diversified away by holding JPMorgan ETFs ICAV and DJI in the same portfolio, assuming nothing else is changed.

The ability to find closely correlated positions to JPMorgan ETFs could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace JPMorgan ETFs when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back JPMorgan ETFs - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling JPMorgan ETFs ICAV to buy it.

Moving together with JPMorgan Etf

0.96	VUSA	Vanguard SP 500	Pair Corr
0.67	CSNKY	iShares VII PLC	Pair Corr
0.99	CSSPX	iShares Core SP	Pair Corr
0.66	LYJPN	Lyxor Japan UCITS	Pair Corr
0.99	IUSA	iShares SP 500	Pair Corr

Related Correlations Analysis

	META	MSFT	UBER	F	T	A	CRM	JPM	MRK	XOM
META		0.26	0.55	0.07	0.53	0.05	0.64	0.28	-0.53	0.73	META
MSFT	0.26		0.21	0.17	0.16	-0.01	0.03	-0.11	0.13	-0.2	MSFT
UBER	0.55	0.21		-0.06	-0.09	0.27	-0.03	-0.16	0.09	0.35	UBER
F	0.07	0.17	-0.06		0.28	-0.41	0.5	0.7	-0.37	0.32	F
T	0.53	0.16	-0.09	0.28		-0.5	0.81	0.64	-0.79	0.39	T
A	0.05	-0.01	0.27	-0.41	-0.5		-0.46	-0.6	0.63	0.0	A
CRM	0.64	0.03	-0.03	0.5	0.81	-0.46		0.86	-0.91	0.65	CRM
JPM	0.28	-0.11	-0.16	0.7	0.64	-0.6	0.86		-0.83	0.47	JPM
MRK	-0.53	0.13	0.09	-0.37	-0.79	0.63	-0.91	-0.83		-0.56	MRK
XOM	0.73	-0.2	0.35	0.32	0.39	0.0	0.65	0.47	-0.56		XOM
	META	MSFT	UBER	F	T	A	CRM	JPM	MRK	XOM

Click cells to compare fundamentals

Check Volatility

Backtest Portfolio

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

JPM	+ 0.86	CRM
CRM	+ 0.81	T
XOM	+ 0.73	META
JPM	+ 0.7	F
XOM	+ 0.65	CRM
CRM	+ 0.64	META

High negative correlations

MRK	- 0.91	CRM
MRK	- 0.83	JPM
MRK	- 0.79	T
JPM	- 0.6	A
XOM	- 0.56	MRK
MRK	- 0.53	META

JPMorgan ETFs Competition Risk-Adjusted Indicators

There is a big difference between JPMorgan Etf performing well and JPMorgan ETFs 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 JPMorgan ETFs' 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	1.07	0.07	0.02	0.23	1.41	(1.14)	2.62	(3.15)	8.02
MSFT	0.90	(0.04)	(0.05)	0.07	1.50	(0.86)	2.09	(1.85)	8.19
UBER	1.61	(0.11)	(0.04)	0.02	2.32	(1.70)	2.69	(2.53)	20.10
F	1.42	(0.15)	(0.04)	0.03	2.23	(1.39)	2.53	(2.90)	11.21
T	0.92	0.26	0.12	(7.83)	0.86	(1.06)	2.56	(1.72)	6.47
A	1.17	(0.09)	0.00	(0.06)	0.00	0.00	2.71	(2.42)	9.02
CRM	1.31	0.23	0.18	0.34	1.08	(1.53)	3.18	(1.91)	9.98
JPM	1.12	(0.04)	0.05	0.11	1.38	(1.23)	2.05	(2.00)	15.87
MRK	0.91	(0.24)	0.00	(0.86)	0.00	0.00	2.00	(2.13)	4.89
XOM	1.00	(0.03)	(0.07)	0.06	1.31	(1.04)	2.10	(2.09)	5.74

JPMorgan ETFs Related Equities

One of the popular trading techniques among algorithmic traders is to use market-neutral strategies where every trade hedges away some risk. Because there are two separate transactions required, even if one position performs unexpectedly, the other equity can make up some of the losses. Below are some of the equities that can be combined with JPMorgan ETFs etf to make a market-neutral strategy. Peer analysis of JPMorgan ETFs could also be used in its relative valuation, which is a method of valuing JPMorgan ETFs by comparing valuation metrics with similar companies.

UBSFund Solutions MSCI Vanguard SP 500 iShares VII PLC iShares Core SP Lyxor Japan UCITS iShares Core MSCI iShares SP 500 Lyxor UCITS Stoxx iShares Core Corp iShares JP Morgan American Airlines Group Alcoa Corp Apple Inc Best Buy Co Citigroup

Risk & Return

Correlation

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

2024 Macroaxis LLC