Correlation Between Inter Parfums and BlueScope Steel
Can any of the company-specific risk be diversified away by investing in both Inter Parfums 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 Inter Parfums and BlueScope Steel into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Inter Parfums and BlueScope Steel Limited, you can compare the effects of market volatilities on Inter Parfums 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 Inter Parfums with a short position of BlueScope Steel. Check out your portfolio center. Please also check ongoing floating volatility patterns of Inter Parfums and BlueScope Steel.
Diversification Opportunities for Inter Parfums and BlueScope Steel
-0.49 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Inter and BlueScope is -0.49. Overlapping area represents the amount of risk that can be diversified away by holding Inter Parfums and BlueScope Steel Limited in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BlueScope Steel and Inter Parfums 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 Inter Parfums 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 Inter Parfums i.e., Inter Parfums and BlueScope Steel go up and down completely randomly.
Pair Corralation between Inter Parfums and BlueScope Steel
Given the investment horizon of 90 days Inter Parfums is expected to generate 0.91 times more return on investment than BlueScope Steel. However, Inter Parfums is 1.1 times less risky than BlueScope Steel. It trades about 0.15 of its potential returns per unit of risk. BlueScope Steel Limited is currently generating about -0.15 per unit of risk. If you would invest 12,059 in Inter Parfums on October 23, 2024 and sell it today you would earn a total of 1,800 from holding Inter Parfums or generate 14.93% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Inter Parfums vs. BlueScope Steel Limited
Performance |
Timeline |
Inter Parfums |
BlueScope Steel |
Inter Parfums and BlueScope Steel Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Inter Parfums and BlueScope Steel
The main advantage of trading using opposite Inter Parfums and BlueScope Steel positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Inter Parfums 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.Inter Parfums vs. J J Snack | Inter Parfums vs. John B Sanfilippo | Inter Parfums vs. Innospec | Inter Parfums vs. Independent Bank |
BlueScope Steel vs. Nucor Corp | BlueScope Steel vs. United States Steel | BlueScope Steel vs. Reliance Steel Aluminum | BlueScope Steel vs. ArcelorMittal SA ADR |
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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