Correlation Between Daewoo SBI and Kisan Telecom
Can any of the company-specific risk be diversified away by investing in both Daewoo SBI and Kisan Telecom 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 Daewoo SBI and Kisan Telecom into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Daewoo SBI SPAC and Kisan Telecom Co, you can compare the effects of market volatilities on Daewoo SBI and Kisan Telecom 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 Daewoo SBI with a short position of Kisan Telecom. Check out your portfolio center. Please also check ongoing floating volatility patterns of Daewoo SBI and Kisan Telecom.
Diversification Opportunities for Daewoo SBI and Kisan Telecom
0.28 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Daewoo and Kisan is 0.28. Overlapping area represents the amount of risk that can be diversified away by holding Daewoo SBI SPAC and Kisan Telecom Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kisan Telecom and Daewoo SBI 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 Daewoo SBI SPAC are associated (or correlated) with Kisan Telecom. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kisan Telecom has no effect on the direction of Daewoo SBI i.e., Daewoo SBI and Kisan Telecom go up and down completely randomly.
Pair Corralation between Daewoo SBI and Kisan Telecom
Assuming the 90 days trading horizon Daewoo SBI SPAC is expected to generate 1.87 times more return on investment than Kisan Telecom. However, Daewoo SBI is 1.87 times more volatile than Kisan Telecom Co. It trades about 0.04 of its potential returns per unit of risk. Kisan Telecom Co is currently generating about 0.01 per unit of risk. If you would invest 278,000 in Daewoo SBI SPAC on October 5, 2024 and sell it today you would earn a total of 11,500 from holding Daewoo SBI SPAC or generate 4.14% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Daewoo SBI SPAC vs. Kisan Telecom Co
Performance |
Timeline |
Daewoo SBI SPAC |
Kisan Telecom |
Daewoo SBI and Kisan Telecom Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Daewoo SBI and Kisan Telecom
The main advantage of trading using opposite Daewoo SBI and Kisan Telecom positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Daewoo SBI position performs unexpectedly, Kisan Telecom 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 Kisan Telecom will offset losses from the drop in Kisan Telecom's long position.Daewoo SBI vs. Daou Data Corp | Daewoo SBI vs. Korean Reinsurance Co | Daewoo SBI vs. Hannong Chemicals | Daewoo SBI vs. Ssangyong Information Communication |
Kisan Telecom vs. Innowireless Co | Kisan Telecom vs. Coloray International Investment | Kisan Telecom vs. EBEST Investment Securities | Kisan Telecom vs. Hannong Chemicals |
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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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