Correlation Between BSP Financial and Retail Food
Can any of the company-specific risk be diversified away by investing in both BSP Financial and Retail Food 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 BSP Financial and Retail Food into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between BSP Financial Group and Retail Food Group, you can compare the effects of market volatilities on BSP Financial and Retail Food 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 BSP Financial with a short position of Retail Food. Check out your portfolio center. Please also check ongoing floating volatility patterns of BSP Financial and Retail Food.
Diversification Opportunities for BSP Financial and Retail Food
0.0 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between BSP and Retail is 0.0. Overlapping area represents the amount of risk that can be diversified away by holding BSP Financial Group and Retail Food Group in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Retail Food Group and BSP Financial 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 BSP Financial Group are associated (or correlated) with Retail Food. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Retail Food Group has no effect on the direction of BSP Financial i.e., BSP Financial and Retail Food go up and down completely randomly.
Pair Corralation between BSP Financial and Retail Food
Assuming the 90 days trading horizon BSP Financial is expected to generate 1.23 times less return on investment than Retail Food. But when comparing it to its historical volatility, BSP Financial Group is 1.71 times less risky than Retail Food. It trades about 0.06 of its potential returns per unit of risk. Retail Food Group is currently generating about 0.05 of returns per unit of risk over similar time horizon. If you would invest 5.00 in Retail Food Group on August 31, 2024 and sell it today you would earn a total of 2.20 from holding Retail Food Group or generate 44.0% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Flat |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
BSP Financial Group vs. Retail Food Group
Performance |
| Timeline |
| BSP Financial Group |
| Retail Food Group |
BSP Financial and Retail Food Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with BSP Financial and Retail Food
The main advantage of trading using opposite BSP Financial and Retail Food positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if BSP Financial position performs unexpectedly, Retail Food 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 Retail Food will offset losses from the drop in Retail Food's long position.| BSP Financial vs. K2 Asset Management | BSP Financial vs. Mount Gibson Iron | BSP Financial vs. Bluescope Steel | BSP Financial vs. Hawsons Iron |
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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 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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