Correlation Between ALGOMA STEEL and BlueScope Steel
Can any of the company-specific risk be diversified away by investing in both ALGOMA STEEL and BlueScope Steel 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 ALGOMA STEEL and BlueScope Steel into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between ALGOMA STEEL GROUP and BlueScope Steel Limited, you can compare the effects of market volatilities on ALGOMA STEEL and BlueScope Steel 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 ALGOMA STEEL with a short position of BlueScope Steel. Check out your portfolio center. Please also check ongoing floating volatility patterns of ALGOMA STEEL and BlueScope Steel.
Diversification Opportunities for ALGOMA STEEL and BlueScope Steel
0.22 | Correlation Coefficient |
Modest diversification
The 3 months correlation between ALGOMA and BlueScope is 0.22. Overlapping area represents the amount of risk that can be diversified away by holding ALGOMA STEEL GROUP and BlueScope Steel Limited in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BlueScope Steel and ALGOMA STEEL 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 ALGOMA STEEL GROUP are associated (or correlated) with BlueScope Steel. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of BlueScope Steel has no effect on the direction of ALGOMA STEEL i.e., ALGOMA STEEL and BlueScope Steel go up and down completely randomly.
Pair Corralation between ALGOMA STEEL and BlueScope Steel
Assuming the 90 days horizon ALGOMA STEEL is expected to generate 2.68 times less return on investment than BlueScope Steel. But when comparing it to its historical volatility, ALGOMA STEEL GROUP is 1.06 times less risky than BlueScope Steel. It trades about 0.07 of its potential returns per unit of risk. BlueScope Steel Limited is currently generating about 0.18 of returns per unit of risk over similar time horizon. If you would invest 1,220 in BlueScope Steel Limited on September 1, 2024 and sell it today you would earn a total of 140.00 from holding BlueScope Steel Limited or generate 11.48% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
ALGOMA STEEL GROUP vs. BlueScope Steel Limited
Performance |
| Timeline |
| ALGOMA STEEL GROUP |
| BlueScope Steel |
ALGOMA STEEL and BlueScope Steel Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with ALGOMA STEEL and BlueScope Steel
The main advantage of trading using opposite ALGOMA STEEL and BlueScope Steel positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if ALGOMA STEEL position performs unexpectedly, BlueScope Steel 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 BlueScope Steel will offset losses from the drop in BlueScope Steel's long position.| ALGOMA STEEL vs. ScanSource | ALGOMA STEEL vs. Tower Semiconductor | ALGOMA STEEL vs. LION ONE METALS | ALGOMA STEEL vs. PRECISION DRILLING P |
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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