Correlation Between Mari Petroleum and Synthetic Products
Can any of the company-specific risk be diversified away by investing in both Mari Petroleum and Synthetic Products 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 Mari Petroleum and Synthetic Products into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mari Petroleum and Synthetic Products Enterprises, you can compare the effects of market volatilities on Mari Petroleum and Synthetic Products 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 Mari Petroleum with a short position of Synthetic Products. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mari Petroleum and Synthetic Products.
Diversification Opportunities for Mari Petroleum and Synthetic Products
-0.48 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Mari and Synthetic is -0.48. Overlapping area represents the amount of risk that can be diversified away by holding Mari Petroleum and Synthetic Products Enterprises in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Synthetic Products and Mari 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 Mari Petroleum are associated (or correlated) with Synthetic Products. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Synthetic Products has no effect on the direction of Mari Petroleum i.e., Mari Petroleum and Synthetic Products go up and down completely randomly.
Pair Corralation between Mari Petroleum and Synthetic Products
Assuming the 90 days trading horizon Mari Petroleum is expected to generate 0.73 times more return on investment than Synthetic Products. However, Mari Petroleum is 1.37 times less risky than Synthetic Products. It trades about 0.2 of its potential returns per unit of risk. Synthetic Products Enterprises is currently generating about -0.08 per unit of risk. If you would invest 42,547 in Mari Petroleum on August 25, 2024 and sell it today you would earn a total of 3,769 from holding Mari Petroleum or generate 8.86% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Mari Petroleum vs. Synthetic Products Enterprises
Performance |
Timeline |
Mari Petroleum |
Synthetic Products |
Mari Petroleum and Synthetic Products Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mari Petroleum and Synthetic Products
The main advantage of trading using opposite Mari Petroleum and Synthetic Products positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mari Petroleum position performs unexpectedly, Synthetic Products 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 Synthetic Products will offset losses from the drop in Synthetic Products' long position.Mari Petroleum vs. Agritech | Mari Petroleum vs. Habib Insurance | Mari Petroleum vs. Askari General Insurance | Mari Petroleum vs. Escorts Investment Bank |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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