Correlation Between Marfrig Global and Willamette Valley
Can any of the company-specific risk be diversified away by investing in both Marfrig Global and Willamette Valley 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 Marfrig Global and Willamette Valley into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Marfrig Global Foods and Willamette Valley Vineyards, you can compare the effects of market volatilities on Marfrig Global and Willamette Valley 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 Marfrig Global with a short position of Willamette Valley. Check out your portfolio center. Please also check ongoing floating volatility patterns of Marfrig Global and Willamette Valley.
Diversification Opportunities for Marfrig Global and Willamette Valley
-0.08 | Correlation Coefficient |
Good diversification
The 3 months correlation between Marfrig and Willamette is -0.08. Overlapping area represents the amount of risk that can be diversified away by holding Marfrig Global Foods and Willamette Valley Vineyards in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Willamette Valley and Marfrig Global 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 Marfrig Global Foods are associated (or correlated) with Willamette Valley. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Willamette Valley has no effect on the direction of Marfrig Global i.e., Marfrig Global and Willamette Valley go up and down completely randomly.
Pair Corralation between Marfrig Global and Willamette Valley
Assuming the 90 days horizon Marfrig Global Foods is expected to generate 1.23 times more return on investment than Willamette Valley. However, Marfrig Global is 1.23 times more volatile than Willamette Valley Vineyards. It trades about 0.07 of its potential returns per unit of risk. Willamette Valley Vineyards is currently generating about -0.03 per unit of risk. If you would invest 227.00 in Marfrig Global Foods on October 10, 2024 and sell it today you would earn a total of 31.00 from holding Marfrig Global Foods or generate 13.66% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Marfrig Global Foods vs. Willamette Valley Vineyards
Performance |
Timeline |
Marfrig Global Foods |
Willamette Valley |
Marfrig Global and Willamette Valley Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Marfrig Global and Willamette Valley
The main advantage of trading using opposite Marfrig Global and Willamette Valley positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Marfrig Global position performs unexpectedly, Willamette Valley 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 Willamette Valley will offset losses from the drop in Willamette Valley's long position.Marfrig Global vs. BRF SA ADR | Marfrig Global vs. Pilgrims Pride Corp | Marfrig Global vs. John B Sanfilippo | Marfrig Global vs. Seneca Foods Corp |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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