Correlation Between GOODYEAR T and INDOFOOD AGRI
Can any of the company-specific risk be diversified away by investing in both GOODYEAR T and INDOFOOD AGRI 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 GOODYEAR T and INDOFOOD AGRI into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between GOODYEAR T RUBBER and INDOFOOD AGRI RES, you can compare the effects of market volatilities on GOODYEAR T and INDOFOOD AGRI 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 GOODYEAR T with a short position of INDOFOOD AGRI. Check out your portfolio center. Please also check ongoing floating volatility patterns of GOODYEAR T and INDOFOOD AGRI.
Diversification Opportunities for GOODYEAR T and INDOFOOD AGRI
0.33 | Correlation Coefficient |
Weak diversification
The 3 months correlation between GOODYEAR and INDOFOOD is 0.33. Overlapping area represents the amount of risk that can be diversified away by holding GOODYEAR T RUBBER and INDOFOOD AGRI RES in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on INDOFOOD AGRI RES and GOODYEAR T 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 GOODYEAR T RUBBER are associated (or correlated) with INDOFOOD AGRI. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of INDOFOOD AGRI RES has no effect on the direction of GOODYEAR T i.e., GOODYEAR T and INDOFOOD AGRI go up and down completely randomly.
Pair Corralation between GOODYEAR T and INDOFOOD AGRI
Assuming the 90 days trading horizon GOODYEAR T is expected to generate 5.67 times less return on investment than INDOFOOD AGRI. In addition to that, GOODYEAR T is 1.32 times more volatile than INDOFOOD AGRI RES. It trades about 0.0 of its total potential returns per unit of risk. INDOFOOD AGRI RES is currently generating about 0.02 per unit of volatility. If you would invest 19.00 in INDOFOOD AGRI RES on October 26, 2024 and sell it today you would earn a total of 3.00 from holding INDOFOOD AGRI RES or generate 15.79% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
GOODYEAR T RUBBER vs. INDOFOOD AGRI RES
Performance |
Timeline |
GOODYEAR T RUBBER |
INDOFOOD AGRI RES |
GOODYEAR T and INDOFOOD AGRI Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with GOODYEAR T and INDOFOOD AGRI
The main advantage of trading using opposite GOODYEAR T and INDOFOOD AGRI positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GOODYEAR T position performs unexpectedly, INDOFOOD AGRI 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 INDOFOOD AGRI will offset losses from the drop in INDOFOOD AGRI's long position.GOODYEAR T vs. COSMOSTEEL HLDGS | GOODYEAR T vs. KOBE STEEL LTD | GOODYEAR T vs. BANK OF CHINA | GOODYEAR T vs. United States Steel |
INDOFOOD AGRI vs. BE Semiconductor Industries | INDOFOOD AGRI vs. Clean Energy Fuels | INDOFOOD AGRI vs. Hua Hong Semiconductor | INDOFOOD AGRI vs. CVW CLEANTECH INC |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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