CI Target Correlations

CTMB Etf

20.09 0.02 0.1%

The current 90-days correlation between CI Target 2029 and BetaPro SPTSX 60 is 0.01 (i.e., Significant diversification). A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as CI Target moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if CI Target 2029 moves in either direction, the perfectly negatively correlated security will move in the opposite direction.

CI Target Correlation With Market

Very weak diversification

The correlation between CI Target 2029 and DJI is 0.56 (i.e., Very weak diversification) for selected investment horizon. Overlapping area represents the amount of risk that can be diversified away by holding CI Target 2029 and DJI in the same portfolio, assuming nothing else is changed.

The ability to find closely correlated positions to CI Target could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace CI Target 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 CI Target - 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 CI Target 2029 to buy it.

Moving together with CTMB Etf

0.65	ZAG	BMO Aggregate Bond	Pair Corr
0.67	XBB	iShares Canadian Universe	Pair Corr
0.75	UDIV	Manulife Smart Dividend	Pair Corr
0.94	XSTB	iShares ESG Aware	Pair Corr
0.75	PDIV	Purpose Enhanced Dividend	Pair Corr
0.73	XEU	iShares MSCI Europe	Pair Corr
0.89	XSB	iShares Canadian Short	Pair Corr
0.82	GDV	Global Dividend Growth	Pair Corr
0.87	DXN	Dynamic Active Global	Pair Corr
0.85	WSHR	Wealthsimple Shariah	Pair Corr
0.74	MINT-B	Manulife Multifactor	Pair Corr
0.84	ZWU	BMO Covered Call	Pair Corr
0.88	XSH	iShares Core Canadian	Pair Corr
0.79	EIT-UN	Canoe EIT Income	Pair Corr
0.69	HAC	Global X Seasonal	Pair Corr
0.84	XEG	iShares SPTSX Capped	Pair Corr
0.74	ZEO	BMO Equal Weight	Pair Corr
0.85	NXF	First Asset Energy	Pair Corr
0.75	ZCON	BMO Conservative ETF	Pair Corr
0.69	HXX	Global X Europe	Pair Corr
0.7	DGRC	CI Canada Quality	Pair Corr
0.69	BMAX	Brompton Enhanced Multi	Pair Corr

Related Correlations Analysis

	META	MSFT	UBER	F	T	A	CRM	JPM	MRK	XOM
META		-0.41	-0.46	0.43	0.16	-0.53	-0.1	0.33	0.48	0.43	META
MSFT	-0.41		0.8	-0.53	-0.65	0.71	0.81	0.06	-0.85	-0.91	MSFT
UBER	-0.46	0.8		-0.46	-0.48	0.78	0.53	-0.09	-0.8	-0.74	UBER
F	0.43	-0.53	-0.46		0.06	-0.41	-0.23	0.3	0.68	0.6	F
T	0.16	-0.65	-0.48	0.06		-0.39	-0.75	-0.13	0.4	0.58	T
A	-0.53	0.71	0.78	-0.41	-0.39		0.48	-0.04	-0.63	-0.78	A
CRM	-0.1	0.81	0.53	-0.23	-0.75	0.48		0.44	-0.56	-0.81	CRM
JPM	0.33	0.06	-0.09	0.3	-0.13	-0.04	0.44		0.21	-0.08	JPM
MRK	0.48	-0.85	-0.8	0.68	0.4	-0.63	-0.56	0.21		0.82	MRK
XOM	0.43	-0.91	-0.74	0.6	0.58	-0.78	-0.81	-0.08	0.82		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

XOM	+ 0.82	MRK
CRM	+ 0.81	MSFT
UBER	+ 0.8	MSFT
A	+ 0.78	UBER
A	+ 0.71	MSFT
MRK	+ 0.68	F

High negative correlations

XOM	- 0.91	MSFT
MRK	- 0.85	MSFT
XOM	- 0.81	CRM
MRK	- 0.8	UBER
XOM	- 0.78	A
CRM	- 0.75	T

CI Target Competition Risk-Adjusted Indicators

There is a big difference between CTMB Etf performing well and CI Target 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 CI Target'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	1.51	0.00	(0.02)	0.06	1.53	(1.82)	3.43	(2.82)	13.69
MSFT	1.32	(0.36)	0.00	(0.92)	0.00	0.00	1.90	(2.74)	13.28
UBER	1.50	(0.46)	0.00	(0.90)	0.00	0.00	2.41	(3.82)	11.09
F	1.22	0.07	0.05	0.14	1.20	(1.48)	3.34	(2.30)	7.16
T	1.02	0.23	0.17	3.71	0.77	(1.19)	3.87	(1.54)	5.31
A	1.27	(0.30)	0.00	(0.17)	0.00	0.00	2.90	(2.73)	7.85
CRM	1.68	(0.41)	0.00	(0.35)	0.00	0.00	2.94	(4.75)	12.37
JPM	1.26	(0.15)	0.00	(0.04)	0.00	0.00	2.34	(3.11)	7.38
MRK	1.35	0.49	0.35	0.77	0.97	(1.72)	3.59	(1.98)	8.74
XOM	1.24	0.36	0.22	1.65	1.11	(1.42)	2.68	(2.12)	6.83

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

Global X Inovestor RBC Quant European Mackenzie International Equity Evolve Automobile Innovation Global X Copper Global X Conservative Brompton European Dividend Global X Big BetaPro SPTSX 60 American Airlines Group Alcoa Corp Apple Inc Best Buy Co Citigroup SentinelOne

Risk & Return

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