Correlation Between BioLight Life and Aquarius Engines
Can any of the company-specific risk be diversified away by investing in both BioLight Life and Aquarius Engines 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 BioLight Life and Aquarius Engines into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between BioLight Life Sciences and Aquarius Engines AM, you can compare the effects of market volatilities on BioLight Life and Aquarius Engines 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 BioLight Life with a short position of Aquarius Engines. Check out your portfolio center. Please also check ongoing floating volatility patterns of BioLight Life and Aquarius Engines.
Diversification Opportunities for BioLight Life and Aquarius Engines
-0.57 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between BioLight and Aquarius is -0.57. Overlapping area represents the amount of risk that can be diversified away by holding BioLight Life Sciences and Aquarius Engines AM in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Aquarius Engines and BioLight Life 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 BioLight Life Sciences are associated (or correlated) with Aquarius Engines. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Aquarius Engines has no effect on the direction of BioLight Life i.e., BioLight Life and Aquarius Engines go up and down completely randomly.
Pair Corralation between BioLight Life and Aquarius Engines
Assuming the 90 days trading horizon BioLight Life Sciences is expected to generate 1.37 times more return on investment than Aquarius Engines. However, BioLight Life is 1.37 times more volatile than Aquarius Engines AM. It trades about 0.07 of its potential returns per unit of risk. Aquarius Engines AM is currently generating about 0.01 per unit of risk. If you would invest 43,500 in BioLight Life Sciences on September 27, 2024 and sell it today you would earn a total of 6,400 from holding BioLight Life Sciences or generate 14.71% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
BioLight Life Sciences vs. Aquarius Engines AM
Performance |
Timeline |
BioLight Life Sciences |
Aquarius Engines |
BioLight Life and Aquarius Engines Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with BioLight Life and Aquarius Engines
The main advantage of trading using opposite BioLight Life and Aquarius Engines positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if BioLight Life position performs unexpectedly, Aquarius Engines 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 Aquarius Engines will offset losses from the drop in Aquarius Engines' long position.BioLight Life vs. Kamada | BioLight Life vs. Teva Pharmaceutical Industries | BioLight Life vs. Tower Semiconductor | BioLight Life vs. Elbit Systems |
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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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