Correlation Between Li Kang and Sports Gear
Can any of the company-specific risk be diversified away by investing in both Li Kang and Sports Gear 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 Li Kang and Sports Gear into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Li Kang Biomedical and Sports Gear Co, you can compare the effects of market volatilities on Li Kang and Sports Gear 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 Li Kang with a short position of Sports Gear. Check out your portfolio center. Please also check ongoing floating volatility patterns of Li Kang and Sports Gear.
Diversification Opportunities for Li Kang and Sports Gear
-0.42 | Correlation Coefficient |
Very good diversification
The 3 months correlation between 6242 and Sports is -0.42. Overlapping area represents the amount of risk that can be diversified away by holding Li Kang Biomedical and Sports Gear Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Sports Gear and Li Kang 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 Li Kang Biomedical are associated (or correlated) with Sports Gear. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Sports Gear has no effect on the direction of Li Kang i.e., Li Kang and Sports Gear go up and down completely randomly.
Pair Corralation between Li Kang and Sports Gear
Assuming the 90 days trading horizon Li Kang Biomedical is expected to under-perform the Sports Gear. But the stock apears to be less risky and, when comparing its historical volatility, Li Kang Biomedical is 1.15 times less risky than Sports Gear. The stock trades about -0.01 of its potential returns per unit of risk. The Sports Gear Co is currently generating about 0.09 of returns per unit of risk over similar time horizon. If you would invest 6,348 in Sports Gear Co on October 5, 2024 and sell it today you would earn a total of 6,052 from holding Sports Gear Co or generate 95.34% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Li Kang Biomedical vs. Sports Gear Co
Performance |
Timeline |
Li Kang Biomedical |
Sports Gear |
Li Kang and Sports Gear Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Li Kang and Sports Gear
The main advantage of trading using opposite Li Kang and Sports Gear positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Li Kang position performs unexpectedly, Sports Gear 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 Sports Gear will offset losses from the drop in Sports Gear's long position.Li Kang vs. Standard Foods Corp | Li Kang vs. TTET Union Corp | Li Kang vs. Uni President Enterprises Corp | Li Kang vs. Charoen Pokphand Enterprise |
Sports Gear vs. Giant Manufacturing Co | Sports Gear vs. Merida Industry Co | Sports Gear vs. Johnson Health Tech | Sports Gear vs. Advanced International Multitech |
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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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