Correlation Between Bowler Metcalf and Thungela Resources
Can any of the company-specific risk be diversified away by investing in both Bowler Metcalf and Thungela Resources 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 Bowler Metcalf and Thungela Resources into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bowler Metcalf and Thungela Resources Limited, you can compare the effects of market volatilities on Bowler Metcalf and Thungela Resources 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 Bowler Metcalf with a short position of Thungela Resources. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bowler Metcalf and Thungela Resources.
Diversification Opportunities for Bowler Metcalf and Thungela Resources
0.52 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Bowler and Thungela is 0.52. Overlapping area represents the amount of risk that can be diversified away by holding Bowler Metcalf and Thungela Resources Limited in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Thungela Resources and Bowler Metcalf 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 Bowler Metcalf are associated (or correlated) with Thungela Resources. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Thungela Resources has no effect on the direction of Bowler Metcalf i.e., Bowler Metcalf and Thungela Resources go up and down completely randomly.
Pair Corralation between Bowler Metcalf and Thungela Resources
Assuming the 90 days trading horizon Bowler Metcalf is expected to generate 3.49 times more return on investment than Thungela Resources. However, Bowler Metcalf is 3.49 times more volatile than Thungela Resources Limited. It trades about 0.05 of its potential returns per unit of risk. Thungela Resources Limited is currently generating about 0.09 per unit of risk. If you would invest 110,000 in Bowler Metcalf on September 24, 2024 and sell it today you would earn a total of 22,500 from holding Bowler Metcalf or generate 20.45% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Bowler Metcalf vs. Thungela Resources Limited
Performance |
Timeline |
Bowler Metcalf |
Thungela Resources |
Bowler Metcalf and Thungela Resources Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bowler Metcalf and Thungela Resources
The main advantage of trading using opposite Bowler Metcalf and Thungela Resources positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bowler Metcalf position performs unexpectedly, Thungela Resources 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 Thungela Resources will offset losses from the drop in Thungela Resources' long position.Bowler Metcalf vs. Lesaka Technologies | Bowler Metcalf vs. Harmony Gold Mining | Bowler Metcalf vs. Bytes Technology | Bowler Metcalf vs. Capitec Bank Holdings |
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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 Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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