Correlation Between Sky Metals and FireFly Metals
Can any of the company-specific risk be diversified away by investing in both Sky Metals and FireFly Metals 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 Sky Metals and FireFly Metals into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Sky Metals and FireFly Metals, you can compare the effects of market volatilities on Sky Metals and FireFly Metals 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 Sky Metals with a short position of FireFly Metals. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sky Metals and FireFly Metals.
Diversification Opportunities for Sky Metals and FireFly Metals
0.06 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Sky and FireFly is 0.06. Overlapping area represents the amount of risk that can be diversified away by holding Sky Metals and FireFly Metals in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on FireFly Metals and Sky Metals 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 Sky Metals are associated (or correlated) with FireFly Metals. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of FireFly Metals has no effect on the direction of Sky Metals i.e., Sky Metals and FireFly Metals go up and down completely randomly.
Pair Corralation between Sky Metals and FireFly Metals
Assuming the 90 days trading horizon Sky Metals is expected to generate 3.63 times less return on investment than FireFly Metals. But when comparing it to its historical volatility, Sky Metals is 1.42 times less risky than FireFly Metals. It trades about 0.06 of its potential returns per unit of risk. FireFly Metals is currently generating about 0.16 of returns per unit of risk over similar time horizon. If you would invest 91.00 in FireFly Metals on October 21, 2024 and sell it today you would earn a total of 7.00 from holding FireFly Metals or generate 7.69% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Sky Metals vs. FireFly Metals
Performance |
| Timeline |
| Sky Metals |
| FireFly Metals |
Sky Metals and FireFly Metals Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Sky Metals and FireFly Metals
The main advantage of trading using opposite Sky Metals and FireFly Metals positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sky Metals position performs unexpectedly, FireFly Metals 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 FireFly Metals will offset losses from the drop in FireFly Metals' long position.| Sky Metals vs. Platinum Asset Management | Sky Metals vs. Neurotech International | Sky Metals vs. Dicker Data | Sky Metals vs. Australian Strategic Materials |
| FireFly Metals vs. Iron Road | FireFly Metals vs. Farm Pride Foods | FireFly Metals vs. Charter Hall Retail | FireFly Metals vs. Phoslock Environmental Technologies |
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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