IShares SAMPP Correlations

XMC Etf

CAD 35.31 0.16 0.46%

The current 90-days correlation between iShares SAMPP Mid and TD Q Small Mid Cap is 0.9 (i.e., Almost no diversification).The correlation of IShares SAMPP is a statistical measure of how it moves in relation to other instruments. The correlation coefficient ranges between -1 and +1. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5.

Market Correlation Summary - IShares SAMPP

Poor diversification

Across the chosen horizon, XMC and DJI show a correlation of 0.75 and fall into the Poor diversification bucket. In portfolio terms, the overlap visualization shows how much shared movement remains after both positions are combined.

This correlation view provides context for how IShares SAMPP relates to similar exposures. Where wash sale rules apply, substantially identical replacements can be restricted; this view is informational context only.

Moving together with IShares Etf

0.88	XSU	iShares Small Cap	Pair Corr
0.96	XMH	iShares SAMPP Mid	Pair Corr
0.78	UMI	CI MidCap Dividend	Pair Corr
0.85	MUMC	Manulife Multifactor Mid	Pair Corr
0.93	XSMH	iShares SAMPP Small	Pair Corr
0.72	FHF	First Trust Nasdaq	Pair Corr
0.93	DXZ	Dynamic Active Mid	Pair Corr
0.61	HGU	BetaPro Canadian Gold	Pair Corr
0.68	ZGD	BMO Equal Weight	Pair Corr
0.67	ZJG	BMO Junior Gold	Pair Corr
0.68	HGGG	Harvest Global Gold	Pair Corr
0.73	XMD	iShares SAMPPTSX	Pair Corr
0.82	ONEQ	CI ONE Global	Pair Corr

Related Correlations Analysis

	META	MSFT	UBER	F	T	A	CRM	JPM	MRK	XOM
META		0.03	-0.03	0.15	0.06	0.03	0.0	0.21	-0.07	0.0	META
MSFT	0.03		0.84	0.06	-0.92	0.83	0.97	0.59	-0.91	-0.95	MSFT
UBER	-0.03	0.84		0.08	-0.87	0.83	0.81	0.43	-0.81	-0.81	UBER
F	0.15	0.06	0.08		-0.15	0.47	0.02	0.47	0.11	-0.15	F
T	0.06	-0.92	-0.87	-0.15		-0.86	-0.86	-0.5	0.84	0.88	T
A	0.03	0.83	0.83	0.47	-0.86		0.8	0.75	-0.68	-0.85	A
CRM	0.0	0.97	0.81	0.02	-0.86	0.8		0.63	-0.89	-0.96	CRM
JPM	0.21	0.59	0.43	0.47	-0.5	0.75	0.63		-0.39	-0.66	JPM
MRK	-0.07	-0.91	-0.81	0.11	0.84	-0.68	-0.89	-0.39		0.89	MRK
XOM	0.0	-0.95	-0.81	-0.15	0.88	-0.85	-0.96	-0.66	0.89		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

CRM	+ 0.97	MSFT
XOM	+ 0.89	MRK
XOM	+ 0.88	T
UBER	+ 0.84	MSFT
MRK	+ 0.84	T
A	+ 0.83	MSFT

High negative correlations

XOM	- 0.96	CRM
XOM	- 0.95	MSFT
T	- 0.92	MSFT
MRK	- 0.91	MSFT
MRK	- 0.89	CRM
T	- 0.87	UBER

IShares SAMPP Competition Risk-Adjusted Indicators

Evaluating IShares Etf requires separating price momentum from underlying business quality relative to competitors. Without reviewing risk-adjusted indicators, investors may overweight recent returns and underweight the volatility required to achieve them. 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	1.48	-0.03	0.00	-0.06	0.00	0.00	2.33	-2.82	14.24
MSFT	1.29	-0.29	0.00	-0.75	0.00	0.00	2.19	-2.87	13.28
UBER	1.56	-0.35	0.00	0.73	0.00	0.00	2.70	-3.82	11.09
F	1.37	-0.11	0.00	-0.12	0.00	0.00	3.61	-3.07	10.01
T	1.10	0.20	0.17	-0.74	1.10	-1.24	3.87	-1.92	8.53
A	1.26	-0.31	0.00	-0.33	0.00	0.00	2.48	-3.01	7.20
CRM	1.82	-0.37	0.00	-0.59	0.00	0.00	3.41	-4.75	9.78
JPM	1.19	-0.02	0.00	-0.04	0.00	0.00	2.34	-2.63	8.17
MRK	1.14	0.30	0.22	0.62	1.21	-1.27	2.54	-1.98	7.29
XOM	1.33	0.45	0.30	14.43	1.14	-1.54	2.90	-2.44	6.83

Be your own money manager

A disciplined portfolio workflow around iShares SAMPP Mid Cap should test whether the position strengthens diversification, return efficiency, and overall portfolio fit. Used correctly, optimization turns position sizing and rebalancing into measurable decisions rather than guesswork.

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