Correlation Between Bristol-Myers Squibb and Nova Lithium
Can any of the company-specific risk be diversified away by investing in both Bristol-Myers Squibb and Nova Lithium 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 Bristol-Myers Squibb and Nova Lithium into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bristol Myers Squibb and Nova Lithium Corp, you can compare the effects of market volatilities on Bristol-Myers Squibb and Nova Lithium 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 Bristol-Myers Squibb with a short position of Nova Lithium. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bristol-Myers Squibb and Nova Lithium.
Diversification Opportunities for Bristol-Myers Squibb and Nova Lithium
-0.36 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Bristol-Myers and Nova is -0.36. Overlapping area represents the amount of risk that can be diversified away by holding Bristol Myers Squibb and Nova Lithium Corp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Nova Lithium Corp and Bristol-Myers Squibb 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 Bristol Myers Squibb are associated (or correlated) with Nova Lithium. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Nova Lithium Corp has no effect on the direction of Bristol-Myers Squibb i.e., Bristol-Myers Squibb and Nova Lithium go up and down completely randomly.
Pair Corralation between Bristol-Myers Squibb and Nova Lithium
Assuming the 90 days horizon Bristol Myers Squibb is expected to generate 0.8 times more return on investment than Nova Lithium. However, Bristol Myers Squibb is 1.25 times less risky than Nova Lithium. It trades about 0.15 of its potential returns per unit of risk. Nova Lithium Corp is currently generating about -0.14 per unit of risk. If you would invest 90,051 in Bristol Myers Squibb on September 3, 2024 and sell it today you would earn a total of 10,504 from holding Bristol Myers Squibb or generate 11.66% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 95.0% |
Values | Daily Returns |
Bristol Myers Squibb vs. Nova Lithium Corp
Performance |
Timeline |
Bristol Myers Squibb |
Nova Lithium Corp |
Bristol-Myers Squibb and Nova Lithium Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bristol-Myers Squibb and Nova Lithium
The main advantage of trading using opposite Bristol-Myers Squibb and Nova Lithium positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bristol-Myers Squibb position performs unexpectedly, Nova Lithium 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 Nova Lithium will offset losses from the drop in Nova Lithium's long position.Bristol-Myers Squibb vs. Novartis AG | Bristol-Myers Squibb vs. Bayer AG | Bristol-Myers Squibb vs. Astellas Pharma | Bristol-Myers Squibb vs. Roche Holding AG |
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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 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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