Correlation Between Microsoft and Buriram Sugar
Can any of the company-specific risk be diversified away by investing in both Microsoft and Buriram Sugar 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 Microsoft and Buriram Sugar into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Microsoft and Buriram Sugar Public, you can compare the effects of market volatilities on Microsoft and Buriram Sugar 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 Microsoft with a short position of Buriram Sugar. Check out your portfolio center. Please also check ongoing floating volatility patterns of Microsoft and Buriram Sugar.
Diversification Opportunities for Microsoft and Buriram Sugar
0.14 | Correlation Coefficient |
Average diversification
The 3 months correlation between Microsoft and Buriram is 0.14. Overlapping area represents the amount of risk that can be diversified away by holding Microsoft and Buriram Sugar Public in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Buriram Sugar Public and Microsoft 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 Microsoft are associated (or correlated) with Buriram Sugar. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Buriram Sugar Public has no effect on the direction of Microsoft i.e., Microsoft and Buriram Sugar go up and down completely randomly.
Pair Corralation between Microsoft and Buriram Sugar
Given the investment horizon of 90 days Microsoft is expected to under-perform the Buriram Sugar. But the stock apears to be less risky and, when comparing its historical volatility, Microsoft is 1.04 times less risky than Buriram Sugar. The stock trades about -0.04 of its potential returns per unit of risk. The Buriram Sugar Public is currently generating about 0.23 of returns per unit of risk over similar time horizon. If you would invest 438.00 in Buriram Sugar Public on August 31, 2024 and sell it today you would earn a total of 40.00 from holding Buriram Sugar Public or generate 9.13% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Microsoft vs. Buriram Sugar Public
Performance |
| Timeline |
| Microsoft |
| Buriram Sugar Public |
Microsoft and Buriram Sugar Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Microsoft and Buriram Sugar
The main advantage of trading using opposite Microsoft and Buriram Sugar positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Microsoft position performs unexpectedly, Buriram Sugar 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 Buriram Sugar will offset losses from the drop in Buriram Sugar's long position.| Microsoft vs. Palo Alto Networks | Microsoft vs. Uipath Inc | Microsoft vs. Block Inc | Microsoft vs. Adobe Systems Incorporated |
| Buriram Sugar vs. MK Restaurant Group | Buriram Sugar vs. TRC Construction Public | Buriram Sugar vs. Bangkok Expressway and | Buriram Sugar vs. Lohakit Metal Public |
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 Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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