Correlation Between ALGOMA STEEL and Brockhaus Capital
Can any of the company-specific risk be diversified away by investing in both ALGOMA STEEL and Brockhaus Capital 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 Brockhaus Capital 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 Brockhaus Capital Management, you can compare the effects of market volatilities on ALGOMA STEEL and Brockhaus Capital 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 Brockhaus Capital. Check out your portfolio center. Please also check ongoing floating volatility patterns of ALGOMA STEEL and Brockhaus Capital.
Diversification Opportunities for ALGOMA STEEL and Brockhaus Capital
-0.26 | Correlation Coefficient |
Very good diversification
The 3 months correlation between ALGOMA and Brockhaus is -0.26. Overlapping area represents the amount of risk that can be diversified away by holding ALGOMA STEEL GROUP and Brockhaus Capital Management in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Brockhaus Capital 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 Brockhaus Capital. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Brockhaus Capital has no effect on the direction of ALGOMA STEEL i.e., ALGOMA STEEL and Brockhaus Capital go up and down completely randomly.
Pair Corralation between ALGOMA STEEL and Brockhaus Capital
Assuming the 90 days horizon ALGOMA STEEL GROUP is expected to under-perform the Brockhaus Capital. In addition to that, ALGOMA STEEL is 1.08 times more volatile than Brockhaus Capital Management. It trades about -0.28 of its total potential returns per unit of risk. Brockhaus Capital Management is currently generating about 0.0 per unit of volatility. If you would invest 2,350 in Brockhaus Capital Management on October 18, 2024 and sell it today you would lose (10.00) from holding Brockhaus Capital Management or give up 0.43% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
ALGOMA STEEL GROUP vs. Brockhaus Capital Management
Performance |
Timeline |
ALGOMA STEEL GROUP |
Brockhaus Capital |
ALGOMA STEEL and Brockhaus Capital Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with ALGOMA STEEL and Brockhaus Capital
The main advantage of trading using opposite ALGOMA STEEL and Brockhaus Capital positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if ALGOMA STEEL position performs unexpectedly, Brockhaus Capital 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 Brockhaus Capital will offset losses from the drop in Brockhaus Capital's long position.ALGOMA STEEL vs. Micron Technology | ALGOMA STEEL vs. COLUMBIA SPORTSWEAR | ALGOMA STEEL vs. NTG Nordic Transport | ALGOMA STEEL vs. United Utilities Group |
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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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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