Correlation Between COMMERCIAL VEHICLE and Siamgas
Can any of the company-specific risk be diversified away by investing in both COMMERCIAL VEHICLE and Siamgas 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 COMMERCIAL VEHICLE and Siamgas into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between COMMERCIAL VEHICLE and Siamgas And Petrochemicals, you can compare the effects of market volatilities on COMMERCIAL VEHICLE and Siamgas 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 COMMERCIAL VEHICLE with a short position of Siamgas. Check out your portfolio center. Please also check ongoing floating volatility patterns of COMMERCIAL VEHICLE and Siamgas.
Diversification Opportunities for COMMERCIAL VEHICLE and Siamgas
-0.11 | Correlation Coefficient |
Good diversification
The 3 months correlation between COMMERCIAL and Siamgas is -0.11. Overlapping area represents the amount of risk that can be diversified away by holding COMMERCIAL VEHICLE and Siamgas And Petrochemicals in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Siamgas And Petroche and COMMERCIAL VEHICLE 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 COMMERCIAL VEHICLE are associated (or correlated) with Siamgas. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Siamgas And Petroche has no effect on the direction of COMMERCIAL VEHICLE i.e., COMMERCIAL VEHICLE and Siamgas go up and down completely randomly.
Pair Corralation between COMMERCIAL VEHICLE and Siamgas
Assuming the 90 days trading horizon COMMERCIAL VEHICLE is expected to under-perform the Siamgas. But the stock apears to be less risky and, when comparing its historical volatility, COMMERCIAL VEHICLE is 2.19 times less risky than Siamgas. The stock trades about -0.05 of its potential returns per unit of risk. The Siamgas And Petrochemicals is currently generating about 0.04 of returns per unit of risk over similar time horizon. If you would invest 11.00 in Siamgas And Petrochemicals on September 4, 2024 and sell it today you would earn a total of 7.00 from holding Siamgas And Petrochemicals or generate 63.64% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
COMMERCIAL VEHICLE vs. Siamgas And Petrochemicals
Performance |
| Timeline |
| COMMERCIAL VEHICLE |
| Siamgas And Petroche |
COMMERCIAL VEHICLE and Siamgas Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with COMMERCIAL VEHICLE and Siamgas
The main advantage of trading using opposite COMMERCIAL VEHICLE and Siamgas positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if COMMERCIAL VEHICLE position performs unexpectedly, Siamgas 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 Siamgas will offset losses from the drop in Siamgas' long position.| COMMERCIAL VEHICLE vs. TOTAL GABON | COMMERCIAL VEHICLE vs. Walgreens Boots Alliance | COMMERCIAL VEHICLE vs. Peak Resources Limited |
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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