Correlation Between Sugar and Wheat Futures
Can any of the company-specific risk be diversified away by investing in both Sugar and Wheat Futures at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining Sugar and Wheat Futures into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Sugar and Wheat Futures, you can compare the effects of market volatilities on Sugar and Wheat Futures and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in Sugar with a short position of Wheat Futures. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sugar and Wheat Futures.
Diversification Opportunities for Sugar and Wheat Futures
0.17 | Correlation Coefficient |
Average diversification
The 3 months correlation between Sugar and Wheat is 0.17. Overlapping area represents the amount of risk that can be diversified away by holding Sugar and Wheat Futures in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Wheat Futures and Sugar is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on Sugar are associated (or correlated) with Wheat Futures. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Wheat Futures has no effect on the direction of Sugar i.e., Sugar and Wheat Futures go up and down completely randomly.
Pair Corralation between Sugar and Wheat Futures
Assuming the 90 days horizon Sugar is expected to generate 1.01 times more return on investment than Wheat Futures. However, Sugar is 1.01 times more volatile than Wheat Futures. It trades about -0.05 of its potential returns per unit of risk. Wheat Futures is currently generating about -0.07 per unit of risk. If you would invest 2,247 in Sugar on August 29, 2024 and sell it today you would lose (82.00) from holding Sugar or give up 3.65% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Sugar vs. Wheat Futures
Performance |
| Timeline |
| Sugar |
| Wheat Futures |
Sugar and Wheat Futures Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Sugar and Wheat Futures
The main advantage of trading using opposite Sugar and Wheat Futures positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sugar position performs unexpectedly, Wheat Futures can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Wheat Futures will offset losses from the drop in Wheat Futures' long position.The idea behind Sugar and Wheat Futures pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.| Wheat Futures vs. Cotton | Wheat Futures vs. US Dollar | Wheat Futures vs. Palladium | Wheat Futures vs. Lumber Futures |
Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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