Correlation Between BSP Financial and MA Financial
Can any of the company-specific risk be diversified away by investing in both BSP Financial and MA Financial 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 MA Financial 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 MA Financial Group, you can compare the effects of market volatilities on BSP Financial and MA Financial 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 MA Financial. Check out your portfolio center. Please also check ongoing floating volatility patterns of BSP Financial and MA Financial.
Diversification Opportunities for BSP Financial and MA Financial
0.27 | Correlation Coefficient |
Modest diversification
The 3 months correlation between BSP and MAF is 0.27. Overlapping area represents the amount of risk that can be diversified away by holding BSP Financial Group and MA Financial Group in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on MA Financial 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 MA Financial. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of MA Financial Group has no effect on the direction of BSP Financial i.e., BSP Financial and MA Financial go up and down completely randomly.
Pair Corralation between BSP Financial and MA Financial
Assuming the 90 days trading horizon BSP Financial Group is expected to generate 0.98 times more return on investment than MA Financial. However, BSP Financial Group is 1.03 times less risky than MA Financial. It trades about 0.13 of its potential returns per unit of risk. MA Financial Group is currently generating about -0.27 per unit of risk. If you would invest 620.00 in BSP Financial Group on September 13, 2024 and sell it today you would earn a total of 29.00 from holding BSP Financial Group or generate 4.68% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
BSP Financial Group vs. MA Financial Group
Performance |
| Timeline |
| BSP Financial Group |
| MA Financial Group |
BSP Financial and MA Financial Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with BSP Financial and MA Financial
The main advantage of trading using opposite BSP Financial and MA Financial positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if BSP Financial position performs unexpectedly, MA Financial 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 MA Financial will offset losses from the drop in MA Financial's long position.| BSP Financial vs. Stelar Metals | BSP Financial vs. Truscott Mining Corp | BSP Financial vs. Iron Road | BSP Financial vs. Falcon Metals |
| MA Financial vs. Westpac Banking | MA Financial vs. National Australia Bank | MA Financial vs. National Australia Bank | MA Financial vs. National Australia Bank |
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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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