Correlation Between CIMB Thai and Indara Insurance
Can any of the company-specific risk be diversified away by investing in both CIMB Thai and Indara Insurance 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 CIMB Thai and Indara Insurance into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between CIMB Thai Bank and Indara Insurance Public, you can compare the effects of market volatilities on CIMB Thai and Indara Insurance 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 CIMB Thai with a short position of Indara Insurance. Check out your portfolio center. Please also check ongoing floating volatility patterns of CIMB Thai and Indara Insurance.
Diversification Opportunities for CIMB Thai and Indara Insurance
0.75 | Correlation Coefficient |
Poor diversification
The 3 months correlation between CIMB and Indara is 0.75. Overlapping area represents the amount of risk that can be diversified away by holding CIMB Thai Bank and Indara Insurance Public in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Indara Insurance Public and CIMB Thai 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 CIMB Thai Bank are associated (or correlated) with Indara Insurance. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Indara Insurance Public has no effect on the direction of CIMB Thai i.e., CIMB Thai and Indara Insurance go up and down completely randomly.
Pair Corralation between CIMB Thai and Indara Insurance
Assuming the 90 days trading horizon CIMB Thai Bank is expected to under-perform the Indara Insurance. In addition to that, CIMB Thai is 1.14 times more volatile than Indara Insurance Public. It trades about -0.23 of its total potential returns per unit of risk. Indara Insurance Public is currently generating about 0.08 per unit of volatility. If you would invest 7,575 in Indara Insurance Public on October 20, 2024 and sell it today you would earn a total of 175.00 from holding Indara Insurance Public or generate 2.31% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 95.24% |
| Values | Daily Returns |
CIMB Thai Bank vs. Indara Insurance Public
Performance |
| Timeline |
| CIMB Thai Bank |
| Indara Insurance Public |
CIMB Thai and Indara Insurance Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with CIMB Thai and Indara Insurance
The main advantage of trading using opposite CIMB Thai and Indara Insurance positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if CIMB Thai position performs unexpectedly, Indara Insurance 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 Indara Insurance will offset losses from the drop in Indara Insurance's long position.| CIMB Thai vs. Bank of Ayudhya | CIMB Thai vs. Krung Thai Bank | CIMB Thai vs. Kiatnakin Phatra Bank | CIMB Thai vs. Asia Aviation Public |
| Indara Insurance vs. IFS Capital Public | Indara Insurance vs. Internet Thailand Public | Indara Insurance vs. Hwa Fong Rubber | Indara Insurance vs. Haad Thip 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 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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