Correlation Between BW Offshore and Bitcoin Depot
Can any of the company-specific risk be diversified away by investing in both BW Offshore and Bitcoin Depot 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 Offshore and Bitcoin Depot into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between BW Offshore Limited and Bitcoin Depot, you can compare the effects of market volatilities on BW Offshore and Bitcoin Depot 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 Offshore with a short position of Bitcoin Depot. Check out your portfolio center. Please also check ongoing floating volatility patterns of BW Offshore and Bitcoin Depot.
Diversification Opportunities for BW Offshore and Bitcoin Depot
0.27 | Correlation Coefficient |
Modest diversification
The 3 months correlation between BWOFY and Bitcoin is 0.27. Overlapping area represents the amount of risk that can be diversified away by holding BW Offshore Limited and Bitcoin Depot in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bitcoin Depot and BW Offshore 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 Offshore Limited are associated (or correlated) with Bitcoin Depot. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bitcoin Depot has no effect on the direction of BW Offshore i.e., BW Offshore and Bitcoin Depot go up and down completely randomly.
Pair Corralation between BW Offshore and Bitcoin Depot
Assuming the 90 days horizon BW Offshore is expected to generate 1.98 times less return on investment than Bitcoin Depot. But when comparing it to its historical volatility, BW Offshore Limited is 2.56 times less risky than Bitcoin Depot. It trades about 0.11 of its potential returns per unit of risk. Bitcoin Depot is currently generating about 0.08 of returns per unit of risk over similar time horizon. If you would invest 153.00 in Bitcoin Depot on September 2, 2024 and sell it today you would earn a total of 46.00 from holding Bitcoin Depot or generate 30.07% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
BW Offshore Limited vs. Bitcoin Depot
Performance |
| Timeline |
| BW Offshore Limited |
| Bitcoin Depot |
BW Offshore and Bitcoin Depot Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with BW Offshore and Bitcoin Depot
The main advantage of trading using opposite BW Offshore and Bitcoin Depot positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if BW Offshore position performs unexpectedly, Bitcoin Depot 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 Bitcoin Depot will offset losses from the drop in Bitcoin Depot's long position.| BW Offshore vs. Legacy Education | BW Offshore vs. Apple Inc | BW Offshore vs. NVIDIA | BW Offshore vs. Microsoft |
| Bitcoin Depot vs. AMCON Distributing | Bitcoin Depot vs. Microbot Medical | Bitcoin Depot vs. NH Foods Ltd | Bitcoin Depot vs. Tyson Foods |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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