Correlation Between INDOFOOD AGRI and GREENX METALS
Can any of the company-specific risk be diversified away by investing in both INDOFOOD AGRI and GREENX METALS 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 INDOFOOD AGRI and GREENX METALS into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between INDOFOOD AGRI RES and GREENX METALS LTD, you can compare the effects of market volatilities on INDOFOOD AGRI and GREENX METALS 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 INDOFOOD AGRI with a short position of GREENX METALS. Check out your portfolio center. Please also check ongoing floating volatility patterns of INDOFOOD AGRI and GREENX METALS.
Diversification Opportunities for INDOFOOD AGRI and GREENX METALS
0.07 | Correlation Coefficient |
Significant diversification
The 3 months correlation between INDOFOOD and GREENX is 0.07. Overlapping area represents the amount of risk that can be diversified away by holding INDOFOOD AGRI RES and GREENX METALS LTD in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on GREENX METALS LTD and INDOFOOD AGRI 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 INDOFOOD AGRI RES are associated (or correlated) with GREENX METALS. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of GREENX METALS LTD has no effect on the direction of INDOFOOD AGRI i.e., INDOFOOD AGRI and GREENX METALS go up and down completely randomly.
Pair Corralation between INDOFOOD AGRI and GREENX METALS
Assuming the 90 days trading horizon INDOFOOD AGRI RES is expected to generate 0.44 times more return on investment than GREENX METALS. However, INDOFOOD AGRI RES is 2.29 times less risky than GREENX METALS. It trades about 0.04 of its potential returns per unit of risk. GREENX METALS LTD is currently generating about -0.01 per unit of risk. If you would invest 21.00 in INDOFOOD AGRI RES on September 4, 2024 and sell it today you would earn a total of 1.00 from holding INDOFOOD AGRI RES or generate 4.76% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
INDOFOOD AGRI RES vs. GREENX METALS LTD
Performance |
Timeline |
INDOFOOD AGRI RES |
GREENX METALS LTD |
INDOFOOD AGRI and GREENX METALS Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with INDOFOOD AGRI and GREENX METALS
The main advantage of trading using opposite INDOFOOD AGRI and GREENX METALS positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if INDOFOOD AGRI position performs unexpectedly, GREENX METALS 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 GREENX METALS will offset losses from the drop in GREENX METALS's long position.INDOFOOD AGRI vs. NEWELL RUBBERMAID | INDOFOOD AGRI vs. PENN NATL GAMING | INDOFOOD AGRI vs. Mitsubishi Materials | INDOFOOD AGRI vs. Penn National Gaming |
GREENX METALS vs. PICKN PAY STORES | GREENX METALS vs. HK Electric Investments | GREENX METALS vs. RETAIL FOOD GROUP | GREENX METALS vs. Zijin Mining Group |
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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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