Correlation Between GM and BANPU POWER
Can any of the company-specific risk be diversified away by investing in both GM and BANPU POWER 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 GM and BANPU POWER into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between General Motors and BANPU POWER, you can compare the effects of market volatilities on GM and BANPU POWER 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 GM with a short position of BANPU POWER. Check out your portfolio center. Please also check ongoing floating volatility patterns of GM and BANPU POWER.
Diversification Opportunities for GM and BANPU POWER
-0.28 | Correlation Coefficient |
Very good diversification
The 3 months correlation between GM and BANPU is -0.28. Overlapping area represents the amount of risk that can be diversified away by holding General Motors and BANPU POWER in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BANPU POWER and GM 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 General Motors are associated (or correlated) with BANPU POWER. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of BANPU POWER has no effect on the direction of GM i.e., GM and BANPU POWER go up and down completely randomly.
Pair Corralation between GM and BANPU POWER
Allowing for the 90-day total investment horizon General Motors is expected to generate 0.61 times more return on investment than BANPU POWER. However, General Motors is 1.64 times less risky than BANPU POWER. It trades about -0.16 of its potential returns per unit of risk. BANPU POWER is currently generating about -0.17 per unit of risk. If you would invest 5,728 in General Motors on September 13, 2024 and sell it today you would lose (515.50) from holding General Motors or give up 9.0% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 95.45% |
| Values | Daily Returns |
General Motors vs. BANPU POWER
Performance |
| Timeline |
| General Motors |
| BANPU POWER |
GM and BANPU POWER Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with GM and BANPU POWER
The main advantage of trading using opposite GM and BANPU POWER positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GM position performs unexpectedly, BANPU POWER 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 BANPU POWER will offset losses from the drop in BANPU POWER's long position.The idea behind General Motors and BANPU POWER pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.| BANPU POWER vs. Super Energy | BANPU POWER vs. The Erawan Group | BANPU POWER vs. XSpring Capital Public | BANPU POWER vs. Ditto 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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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