Correlation Between BW LPG and REC Silicon
Can any of the company-specific risk be diversified away by investing in both BW LPG and REC Silicon 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 BW LPG and REC Silicon into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between BW LPG and REC Silicon ASA, you can compare the effects of market volatilities on BW LPG and REC Silicon 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 BW LPG with a short position of REC Silicon. Check out your portfolio center. Please also check ongoing floating volatility patterns of BW LPG and REC Silicon.
Diversification Opportunities for BW LPG and REC Silicon
0.53 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between BWLPG and REC is 0.53. Overlapping area represents the amount of risk that can be diversified away by holding BW LPG and REC Silicon ASA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on REC Silicon ASA and BW LPG 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 BW LPG are associated (or correlated) with REC Silicon. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of REC Silicon ASA has no effect on the direction of BW LPG i.e., BW LPG and REC Silicon go up and down completely randomly.
Pair Corralation between BW LPG and REC Silicon
Assuming the 90 days trading horizon BW LPG is expected to generate 0.25 times more return on investment than REC Silicon. However, BW LPG is 3.95 times less risky than REC Silicon. It trades about 0.0 of its potential returns per unit of risk. REC Silicon ASA is currently generating about -0.33 per unit of risk. If you would invest 14,570 in BW LPG on August 29, 2024 and sell it today you would lose (70.00) from holding BW LPG or give up 0.48% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
BW LPG vs. REC Silicon ASA
Performance |
| Timeline |
| BW LPG |
| REC Silicon ASA |
BW LPG and REC Silicon Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with BW LPG and REC Silicon
The main advantage of trading using opposite BW LPG and REC Silicon positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if BW LPG position performs unexpectedly, REC Silicon 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 REC Silicon will offset losses from the drop in REC Silicon's long position.The idea behind BW LPG and REC Silicon ASA pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.| REC Silicon vs. Aker Horizons AS | REC Silicon vs. MPC Container Ships | REC Silicon vs. Aker Carbon Capture | REC Silicon vs. Nordic Semiconductor ASA |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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