Correlation Between KB Financial and Trane Technologies
Can any of the company-specific risk be diversified away by investing in both KB Financial and Trane Technologies 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 KB Financial and Trane Technologies into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between KB Financial Group and Trane Technologies plc, you can compare the effects of market volatilities on KB Financial and Trane Technologies 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 KB Financial with a short position of Trane Technologies. Check out your portfolio center. Please also check ongoing floating volatility patterns of KB Financial and Trane Technologies.
Diversification Opportunities for KB Financial and Trane Technologies
0.12 | Correlation Coefficient |
Average diversification
The 3 months correlation between K1BF34 and Trane is 0.12. Overlapping area represents the amount of risk that can be diversified away by holding KB Financial Group and Trane Technologies plc in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Trane Technologies plc and KB 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 KB Financial Group are associated (or correlated) with Trane Technologies. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Trane Technologies plc has no effect on the direction of KB Financial i.e., KB Financial and Trane Technologies go up and down completely randomly.
Pair Corralation between KB Financial and Trane Technologies
Assuming the 90 days trading horizon KB Financial is expected to generate 1.08 times less return on investment than Trane Technologies. In addition to that, KB Financial is 1.28 times more volatile than Trane Technologies plc. It trades about 0.09 of its total potential returns per unit of risk. Trane Technologies plc is currently generating about 0.13 per unit of volatility. If you would invest 54,722 in Trane Technologies plc on October 8, 2024 and sell it today you would earn a total of 60,478 from holding Trane Technologies plc or generate 110.52% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
KB Financial Group vs. Trane Technologies plc
Performance |
Timeline |
KB Financial Group |
Trane Technologies plc |
KB Financial and Trane Technologies Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with KB Financial and Trane Technologies
The main advantage of trading using opposite KB Financial and Trane Technologies positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if KB Financial position performs unexpectedly, Trane Technologies 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 Trane Technologies will offset losses from the drop in Trane Technologies' long position.KB Financial vs. American Airlines Group | KB Financial vs. Waste Management | KB Financial vs. Metalurgica Gerdau SA | KB Financial vs. Burlington Stores, |
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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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