Correlation Between Lalin Property and Precious Shipping
Can any of the company-specific risk be diversified away by investing in both Lalin Property and Precious Shipping 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 Lalin Property and Precious Shipping into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Lalin Property Public and Precious Shipping Public, you can compare the effects of market volatilities on Lalin Property and Precious Shipping 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 Lalin Property with a short position of Precious Shipping. Check out your portfolio center. Please also check ongoing floating volatility patterns of Lalin Property and Precious Shipping.
Diversification Opportunities for Lalin Property and Precious Shipping
0.78 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Lalin and Precious is 0.78. Overlapping area represents the amount of risk that can be diversified away by holding Lalin Property Public and Precious Shipping Public in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Precious Shipping Public and Lalin Property 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 Lalin Property Public are associated (or correlated) with Precious Shipping. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Precious Shipping Public has no effect on the direction of Lalin Property i.e., Lalin Property and Precious Shipping go up and down completely randomly.
Pair Corralation between Lalin Property and Precious Shipping
Assuming the 90 days trading horizon Lalin Property Public is expected to generate 0.39 times more return on investment than Precious Shipping. However, Lalin Property Public is 2.55 times less risky than Precious Shipping. It trades about -0.09 of its potential returns per unit of risk. Precious Shipping Public is currently generating about -0.08 per unit of risk. If you would invest 696.00 in Lalin Property Public on September 1, 2024 and sell it today you would lose (76.00) from holding Lalin Property Public or give up 10.92% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Lalin Property Public vs. Precious Shipping Public
Performance |
Timeline |
Lalin Property Public |
Precious Shipping Public |
Lalin Property and Precious Shipping Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Lalin Property and Precious Shipping
The main advantage of trading using opposite Lalin Property and Precious Shipping positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Lalin Property position performs unexpectedly, Precious Shipping 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 Precious Shipping will offset losses from the drop in Precious Shipping's long position.Lalin Property vs. AP Public | Lalin Property vs. Land and Houses | Lalin Property vs. LPN Development Public | Lalin Property vs. Supalai Public |
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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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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