Five Year Correlations

ZFUSD Commodity

107.74 0.11 0.10%

The current 90-days correlation between Five Year Treasury and US Dollar is -0.16 (i.e., Good diversification). The correlation of Five 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.

Five Year Correlation With Market

Very good diversification

The correlation between Five Year Treasury Note and DJI is -0.23 (i.e., Very good diversification) for selected investment horizon. Overlapping area represents the amount of risk that can be diversified away by holding Five Year Treasury Note and DJI in the same portfolio, assuming nothing else is changed.

The ability to find closely correlated positions to Five 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 Five 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 Five 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 Five Year Treasury Note to buy it.

Moving together with Five Commodity

0.63	BMYMP	Bristol Myers Squibb	Pair Corr
0.89	BRK-A	Berkshire Hathaway	Pair Corr
0.63	SKFOF	Sika AG	Pair Corr
0.71	WM	Waste Management	Pair Corr
0.61	AIMDW	Ainos Inc	Pair Corr
0.81	DNSKF	Danske Bank AS	Pair Corr
0.64	WVVI	Willamette Valley	Pair Corr
0.68	GDXU	MicroSectors Gold Miners	Pair Corr
0.83	TAIL	Cambria Tail Risk	Pair Corr
0.91	SPIB	SPDR Barclays Interm	Pair Corr
0.73	LIAE	Stone Ridge 2050	Pair Corr
0.66	EEMX	SPDR MSCI Emerging	Pair Corr
0.82	GHMS	Goose Hollow Multi	Pair Corr
0.82	ACWV	iShares MSCI Global	Pair Corr
0.85	JMST	JPMorgan Ultra Short	Pair Corr
0.9	VICSX	Vanguard Intermediate-ter	Pair Corr
0.64	DBIWX	Dws Global Macro	Pair Corr
0.68	HTD	John Hancock Tax	Pair Corr
0.63	SGDLX	Sprott Gold Equity	Pair Corr
0.82	GIOIX	Guggenheim Macro Opp	Pair Corr

Moving against Five Commodity

0.85	GOOG	Alphabet Class C Aggressive Push	Pair Corr
0.81	MSFT	Microsoft Aggressive Push	Pair Corr
0.81	NVDA	NVIDIA Aggressive Push	Pair Corr
0.78	AMZN	Amazon Inc Aggressive Push	Pair Corr
0.51	AAPL	Apple Inc Aggressive Push	Pair Corr
0.5	38141E4D8	GOLDMAN SACHS GROUP	Pair Corr
0.32	ISPOW	Thayer Ventures Acqu	Pair Corr

Related Correlations Analysis

	DXUSD	ZBUSD	HOUSD	CCUSD	BZUSD	ZCUSX	ZFUSD
DXUSD		-0.78	0.69	0.85	0.82	0.25	-0.87	DXUSD
ZBUSD	-0.78		-0.58	-0.82	-0.82	-0.12	0.94	ZBUSD
HOUSD	0.69	-0.58		0.57	0.91	0.68	-0.66	HOUSD
CCUSD	0.85	-0.82	0.57		0.74	0.29	-0.88	CCUSD
BZUSD	0.82	-0.82	0.91	0.74		0.44	-0.83	BZUSD
ZCUSX	0.25	-0.12	0.68	0.29	0.44		-0.31	ZCUSX
ZFUSD	-0.87	0.94	-0.66	-0.88	-0.83	-0.31		ZFUSD
	DXUSD	ZBUSD	HOUSD	CCUSD	BZUSD	ZCUSX	ZFUSD

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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

ZFUSD	+ 0.94	ZBUSD
BZUSD	+ 0.91	HOUSD
CCUSD	+ 0.85	DXUSD
BZUSD	+ 0.82	DXUSD
BZUSD	+ 0.74	CCUSD
HOUSD	+ 0.69	DXUSD

High negative correlations

ZFUSD	- 0.88	CCUSD
ZFUSD	- 0.87	DXUSD
ZFUSD	- 0.83	BZUSD
BZUSD	- 0.82	ZBUSD
CCUSD	- 0.82	ZBUSD
ZBUSD	- 0.78	DXUSD

Risk-Adjusted Indicators

There is a big difference between Five Commodity performing well and Five 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 Five 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
DXUSD	0.34	(0.07)	0.00	(1.67)	0.00	0.00	0.55	(0.92)	2.20
ZBUSD	0.46	0.03	0.05	(0.29)	0.45	(0.53)	1.13	(0.82)	2.65
HOUSD	1.19	0.04	0.02	0.25	1.48	(1.31)	2.50	(2.39)	8.17
CCUSD	2.82	(0.53)	0.00	(0.95)	0.00	0.00	4.53	(7.20)	24.64
BZUSD	1.04	0.00	0.00	0.01	1.40	(0.96)	1.73	(2.36)	6.65
ZCUSX	1.02	0.01	0.01	0.10	1.26	(1.02)	2.05	(1.78)	6.00
ZFUSD	0.16	0.01	0.06	(0.24)	0.09	(0.19)	0.37	(0.26)	1.00

Five 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 Five Year, pairing it with other commodities or financial instruments to create a balanced, market-neutral setup.

US Dollar 30 Year Treasury Heating Oil Cocoa Brent Crude Oil Corn Futures Five Year Treasury Note

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