10 Year Correlations

ZNUSD Commodity

111.06 0.03 0.03%

The current 90-days correlation between 10 Year T and Rough Rice Futures is 0.07 (i.e., Significant diversification). The correlation of 10 Year 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.

10 Year Correlation With Market

Good diversification

The correlation between 10 Year T Note Futures and DJI is -0.07 (i.e., Good diversification) for selected investment horizon. Overlapping area represents the amount of risk that can be diversified away by holding 10 Year T Note Futures and DJI in the same portfolio, assuming nothing else is changed.

The ability to find closely correlated positions to 10 Year could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace 10 Year 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 10 Year - 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 10 Year T Note Futures to buy it.

Moving together with ZNUSD Commodity

0.61	BMYMP	Bristol Myers Squibb	Pair Corr
0.9	BRK-A	Berkshire Hathaway	Pair Corr
0.65	SKFOF	Sika AG	Pair Corr
0.76	WM	Waste Management	Pair Corr
0.65	AIMDW	Ainos Inc	Pair Corr
0.78	DNSKF	Danske Bank AS Normal Trading	Pair Corr
0.67	WVVI	Willamette Valley Potential Growth	Pair Corr
0.69	GDXU	MicroSectors Gold Miners	Pair Corr
0.79	TAIL	Cambria Tail Risk	Pair Corr
0.65	BBEM	JP Morgan Exchange	Pair Corr
0.9	SPIB	SPDR Barclays Interm Sell-off Trend	Pair Corr
0.9	LIAE	Stone Ridge 2050	Pair Corr
0.68	EEMX	SPDR MSCI Emerging	Pair Corr
0.84	GHMS	Goose Hollow Multi	Pair Corr
0.85	ACWV	iShares MSCI Global	Pair Corr
0.85	JMST	JPMorgan Ultra Short	Pair Corr
0.92	VICSX	Vanguard Intermediate-ter	Pair Corr
0.68	DBIWX	Dws Global Macro	Pair Corr
0.71	HTD	John Hancock Tax	Pair Corr
0.65	SGDLX	Sprott Gold Equity	Pair Corr
0.84	GIOIX	Guggenheim Macro Opp	Pair Corr

Moving against ZNUSD Commodity

0.84	GOOG	Alphabet Class C Aggressive Push	Pair Corr
0.79	NVDA	NVIDIA Aggressive Push	Pair Corr
0.78	MSFT	Microsoft Aggressive Push	Pair Corr
0.73	AMZN	Amazon Inc Aggressive Push	Pair Corr
0.47	AAPL	Apple Inc Aggressive Push	Pair Corr

Related Correlations Analysis

	ZRUSD	DXUSD	CCUSD	RTYUSD	LBUSD	PAUSD	HEUSX
ZRUSD		0.64	0.72	0.59	-0.59	0.07	-0.42	ZRUSD
DXUSD	0.64		0.84	0.83	-0.86	0.0	-0.48	DXUSD
CCUSD	0.72	0.84		0.88	-0.91	0.09	-0.42	CCUSD
RTYUSD	0.59	0.83	0.88		-0.82	0.3	-0.2	RTYUSD
LBUSD	-0.59	-0.86	-0.91	-0.82		0.05	0.49	LBUSD
PAUSD	0.07	0.0	0.09	0.3	0.05		0.34	PAUSD
HEUSX	-0.42	-0.48	-0.42	-0.2	0.49	0.34		HEUSX
	ZRUSD	DXUSD	CCUSD	RTYUSD	LBUSD	PAUSD	HEUSX

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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

RTYUSD	+ 0.88	CCUSD
CCUSD	+ 0.84	DXUSD
RTYUSD	+ 0.83	DXUSD
CCUSD	+ 0.72	ZRUSD
DXUSD	+ 0.64	ZRUSD
RTYUSD	+ 0.59	ZRUSD

High negative correlations

LBUSD	- 0.91	CCUSD
LBUSD	- 0.86	DXUSD
LBUSD	- 0.82	RTYUSD
LBUSD	- 0.59	ZRUSD
HEUSX	- 0.48	DXUSD
HEUSX	- 0.42	CCUSD

Risk-Adjusted Indicators

There is a big difference between ZNUSD Commodity performing well and 10 Year Commodity 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 10 Year'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
ZRUSD	0.95	(0.13)	0.00	1.08	0.00	0.00	1.88	(1.85)	5.26
DXUSD	0.35	(0.06)	0.00	(5.11)	0.00	0.00	0.55	(0.92)	2.20
CCUSD	2.82	(0.53)	0.00	(1.05)	0.00	0.00	4.53	(7.20)	24.64
RTYUSD	0.87	(0.11)	0.00	(0.23)	0.00	0.00	1.95	(1.98)	4.94
LBUSD	1.38	0.36	0.26	(1.65)	1.33	(1.61)	3.59	(1.95)	11.20
PAUSD	1.50	0.08	0.06	(0.32)	1.79	(1.55)	3.49	(2.91)	10.97
HEUSX	1.05	0.06	0.05	0.15	1.41	(1.13)	2.75	(2.31)	8.52

10 Year Related Commodities

One prevalent trading approach among algorithmic traders in the commodities sector involves employing market-neutral strategies, wherein each trade is designed to hedge away specific risks. Given that this approach necessitates two distinct transactions, if one position underperforms unexpectedly, the other can potentially offset some of the losses. This method can be applied to commodities such as 10 Year, pairing it with other commodities or financial instruments to create a balanced, market-neutral setup.

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