Correlation Between Golden Goliath and Lotus Resources
Can any of the company-specific risk be diversified away by investing in both Golden Goliath and Lotus 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 Golden Goliath and Lotus Resources into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Golden Goliath Resources and Lotus Resources Limited, you can compare the effects of market volatilities on Golden Goliath and Lotus 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 Golden Goliath with a short position of Lotus Resources. Check out your portfolio center. Please also check ongoing floating volatility patterns of Golden Goliath and Lotus Resources.
Diversification Opportunities for Golden Goliath and Lotus Resources
0.36 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Golden and Lotus is 0.36. Overlapping area represents the amount of risk that can be diversified away by holding Golden Goliath Resources and Lotus Resources Limited in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Lotus Resources and Golden Goliath 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 Golden Goliath Resources are associated (or correlated) with Lotus Resources. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Lotus Resources has no effect on the direction of Golden Goliath i.e., Golden Goliath and Lotus Resources go up and down completely randomly.
Pair Corralation between Golden Goliath and Lotus Resources
Assuming the 90 days horizon Golden Goliath Resources is expected to generate 21.82 times more return on investment than Lotus Resources. However, Golden Goliath is 21.82 times more volatile than Lotus Resources Limited. It trades about 0.19 of its potential returns per unit of risk. Lotus Resources Limited is currently generating about 0.03 per unit of risk. If you would invest 4.00 in Golden Goliath Resources on September 5, 2024 and sell it today you would earn a total of 3.50 from holding Golden Goliath Resources or generate 87.5% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 91.09% |
Values | Daily Returns |
Golden Goliath Resources vs. Lotus Resources Limited
Performance |
Timeline |
Golden Goliath Resources |
Lotus Resources |
Golden Goliath and Lotus Resources Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Golden Goliath and Lotus Resources
The main advantage of trading using opposite Golden Goliath and Lotus Resources positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Golden Goliath position performs unexpectedly, Lotus 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 Lotus Resources will offset losses from the drop in Lotus Resources' long position.Golden Goliath vs. Qubec Nickel Corp | Golden Goliath vs. IGO Limited | Golden Goliath vs. Avarone Metals | Golden Goliath vs. Elcora Advanced Materials |
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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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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