159857 Correlations

159857 Etf

0.62 0.01 1.59%

The current 90-days correlation between 159857 and 159695 is 0.53 (i.e., Very weak diversification). The correlation of 159857 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.

159857 Correlation With Market

Average diversification

The correlation between 159857 and DJI is 0.14 (i.e., Average diversification) for selected investment horizon. Overlapping area represents the amount of risk that can be diversified away by holding 159857 and DJI in the same portfolio, assuming nothing else is changed.

The ability to find closely correlated positions to 159857 could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace 159857 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 159857 - 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 159857 to buy it.

Moving against 159857 Etf

0.84	159972	159972	Pair Corr
0.55	159831	159831	Pair Corr
0.52	159687	159687	Pair Corr
0.33	513910	513910	Pair Corr
0.31	159741	159741	Pair Corr

Related Correlations Analysis

	META	MSFT	UBER	F	T	A	CRM	JPM	MRK	XOM
META		-0.49	0.66	-0.58	0.71	0.2	-0.2	0.87	-0.84	-0.13	META
MSFT	-0.49		-0.67	0.53	-0.69	0.39	0.82	-0.48	0.63	0.04	MSFT
UBER	0.66	-0.67		-0.3	0.77	-0.16	-0.57	0.73	-0.78	0.36	UBER
F	-0.58	0.53	-0.3		-0.39	0.21	0.47	-0.38	0.67	0.63	F
T	0.71	-0.69	0.77	-0.39		-0.33	-0.52	0.63	-0.76	0.1	T
A	0.2	0.39	-0.16	0.21	-0.33		0.47	0.38	0.11	0.07	A
CRM	-0.2	0.82	-0.57	0.47	-0.52	0.47		-0.26	0.46	0.05	CRM
JPM	0.87	-0.48	0.73	-0.38	0.63	0.38	-0.26		-0.78	0.09	JPM
MRK	-0.84	0.63	-0.78	0.67	-0.76	0.11	0.46	-0.78		0.08	MRK
XOM	-0.13	0.04	0.36	0.63	0.1	0.07	0.05	0.09	0.08		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	+ 0.87	META
CRM	+ 0.82	MSFT
T	+ 0.77	UBER
JPM	+ 0.73	UBER
T	+ 0.71	META
MRK	+ 0.67	F

High negative correlations

MRK	- 0.84	META
MRK	- 0.78	JPM
MRK	- 0.78	UBER
MRK	- 0.76	T
T	- 0.69	MSFT
UBER	- 0.67	MSFT

159857 Competition Risk-Adjusted Indicators

There is a big difference between 159857 Etf performing well and 159857 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 159857'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	1.43	0.26	0.16	0.31	1.56	(1.45)	3.22	(2.30)	7.11
MSFT	1.05	(0.06)	0.00	(0.21)	0.00	0.00	2.56	(2.14)	10.31
UBER	1.90	0.13	0.07	5.75	2.78	(1.88)	4.72	(3.13)	12.28
F	1.38	(0.08)	0.00	(0.14)	0.00	0.00	2.55	(2.89)	10.14
T	1.03	0.26	0.18	0.32	1.36	(1.13)	1.90	(1.97)	11.66
A	1.14	(0.04)	0.00	(0.11)	0.00	0.00	2.81	(2.53)	9.03
CRM	1.45	(0.18)	0.00	(0.29)	0.00	0.00	2.21	(3.81)	15.92
JPM	0.95	0.08	0.05	0.02	1.46	(0.95)	1.97	(1.73)	6.85
MRK	1.24	(0.11)	0.00	(2.67)	0.00	0.00	2.15	(2.24)	11.57
XOM	0.94	(0.13)	0.00	(0.31)	0.00	0.00	1.76	(2.50)	5.89

159857 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 159857 etf to make a market-neutral strategy. Peer analysis of 159857 could also be used in its relative valuation, which is a method of valuing 159857 by comparing valuation metrics with similar companies.

159695 159792 159551 CCB Principal SSE 159560 518600 562930 159783 American Airlines Group Alcoa Corp Apple Inc Best Buy Co Citigroup SentinelOne CVS Health Corp

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