Correlation Between Materials Petroleum and Tay Ninh
Can any of the company-specific risk be diversified away by investing in both Materials Petroleum and Tay Ninh 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 Materials Petroleum and Tay Ninh into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Materials Petroleum JSC and Tay Ninh Rubber, you can compare the effects of market volatilities on Materials Petroleum and Tay Ninh 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 Materials Petroleum with a short position of Tay Ninh. Check out your portfolio center. Please also check ongoing floating volatility patterns of Materials Petroleum and Tay Ninh.
Diversification Opportunities for Materials Petroleum and Tay Ninh
0.02 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Materials and Tay is 0.02. Overlapping area represents the amount of risk that can be diversified away by holding Materials Petroleum JSC and Tay Ninh Rubber in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Tay Ninh Rubber and Materials Petroleum 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 Materials Petroleum JSC are associated (or correlated) with Tay Ninh. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Tay Ninh Rubber has no effect on the direction of Materials Petroleum i.e., Materials Petroleum and Tay Ninh go up and down completely randomly.
Pair Corralation between Materials Petroleum and Tay Ninh
Assuming the 90 days trading horizon Materials Petroleum JSC is expected to under-perform the Tay Ninh. In addition to that, Materials Petroleum is 1.19 times more volatile than Tay Ninh Rubber. It trades about -0.03 of its total potential returns per unit of risk. Tay Ninh Rubber is currently generating about 0.04 per unit of volatility. If you would invest 5,200,000 in Tay Ninh Rubber on October 8, 2024 and sell it today you would earn a total of 70,000 from holding Tay Ninh Rubber or generate 1.35% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 55.0% |
Values | Daily Returns |
Materials Petroleum JSC vs. Tay Ninh Rubber
Performance |
Timeline |
Materials Petroleum JSC |
Tay Ninh Rubber |
Materials Petroleum and Tay Ninh Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Materials Petroleum and Tay Ninh
The main advantage of trading using opposite Materials Petroleum and Tay Ninh positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Materials Petroleum position performs unexpectedly, Tay Ninh 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 Tay Ninh will offset losses from the drop in Tay Ninh's long position.Materials Petroleum vs. FIT INVEST JSC | Materials Petroleum vs. Damsan JSC | Materials Petroleum vs. An Phat Plastic | Materials Petroleum vs. APG Securities Joint |
Tay Ninh vs. FIT INVEST JSC | Tay Ninh vs. Damsan JSC | Tay Ninh vs. An Phat Plastic | Tay Ninh vs. APG Securities Joint |
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 Volatility Analysis module to get historical volatility and risk analysis based on latest market data.
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