Coffee Correlations

Commodities . USA . 
Commodity . Coffee
KCUSX Commodity   367.25  11.00  3.09%   
The current 90-days correlation between Coffee and Class III Milk is -0.04 (i.e., Good diversification). The correlation of Coffee 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. If the correlation is 0, the equities are not correlated; they are entirely random.

Coffee Correlation With Market

Excellent diversification

The correlation between Coffee and DJI is -0.61 (i.e., Excellent diversification) for selected investment horizon. Overlapping area represents the amount of risk that can be diversified away by holding Coffee and DJI in the same portfolio, assuming nothing else is changed.
  
The ability to find closely correlated positions to Coffee could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Coffee 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 Coffee - 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 Coffee to buy it.

Moving together with Coffee Commodity

  0.71MSFT Microsoft Earnings Call TodayPairCorr

Moving against Coffee Commodity

  0.81PNTRF Pantera Silver Corp Earnings Call TomorrowPairCorr
  0.8JNJ Johnson JohnsonPairCorr
  0.77BMYMP Bristol Myers SquibbPairCorr
  0.74TSGZF Tristar GoldPairCorr
  0.74SBSW Sibanye GoldPairCorr
  0.73NEM Newmont Goldcorp Corp Aggressive PushPairCorr
  0.72GOOG Alphabet Class C Earnings Call This WeekPairCorr
  0.69COCSF Coca Cola FEMSAPairCorr
  0.66MGPUF MG PlcPairCorr
  0.53ZIJMF Zijin Mining GroupPairCorr
  0.49CIMDF CIMB Group HoldingsPairCorr
  0.46FELE Franklin ElectricPairCorr
  0.39SSRM SSR MiningPairCorr
  0.34TSM Taiwan SemiconductorPairCorr
  0.32EEMX SPDR MSCI EmergingPairCorr
  0.83CUSDX Six Circles UltraPairCorr
  0.81CREMX Redwood Real EstatePairCorr
  0.81ARRFX Amg River RoadPairCorr
  0.8SPVM Invesco SP 500PairCorr
  0.79JANH Innovator Equity PremiumPairCorr
  0.79DBLSX Doubleline Low DurationPairCorr
  0.78SNWCX Snow Capital SmallPairCorr
  0.78SMDIX Hartford SchrodersPairCorr
  0.76SDGFX Sdit Short DurationPairCorr
  0.75CHCGX Chesapeake GrowthPairCorr
  0.74TWCGX Growth Fund InvestorPairCorr
  0.71LITL Simplify Exchange TradedPairCorr
  0.71PLAAX Pace Large GrowthPairCorr
  0.68IWD iShares Russell 1000PairCorr
  0.68LIT Global X LithiumPairCorr

Related Correlations Analysis


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

OJUSX
+ 0.71
PAUSD
ESUSD
+ 0.7
PAUSD
OJUSX
+ 0.6
ESUSD
BZUSD
+ 0.3
OJUSX
BZUSD
+ 0.22
CTUSX
OJUSX
+ 0.21
CTUSX
  

High negative correlations

DCUSD
- 0.87
PAUSD
DCUSD
- 0.69
ESUSD
BZUSD
- 0.64
ZCUSX
DCUSD
- 0.57
OJUSX
OJUSX
- 0.16
ZCUSX
ZCUSX
- 0.12
CTUSX

Risk-Adjusted Indicators

There is a big difference between Coffee Commodity performing well and Coffee 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 Coffee'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.

Coffee 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 Coffee, pairing it with other commodities or financial instruments to create a balanced, market-neutral setup.
 Risk & Return  Correlation
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