Correlation Between Kyung-In Synthetic and PLAYWITH
Can any of the company-specific risk be diversified away by investing in both Kyung-In Synthetic and PLAYWITH 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 Kyung-In Synthetic and PLAYWITH into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Kyung In Synthetic Corp and PLAYWITH, you can compare the effects of market volatilities on Kyung-In Synthetic and PLAYWITH 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 Kyung-In Synthetic with a short position of PLAYWITH. Check out your portfolio center. Please also check ongoing floating volatility patterns of Kyung-In Synthetic and PLAYWITH.
Diversification Opportunities for Kyung-In Synthetic and PLAYWITH
0.73 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Kyung-In and PLAYWITH is 0.73. Overlapping area represents the amount of risk that can be diversified away by holding Kyung In Synthetic Corp and PLAYWITH in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PLAYWITH and Kyung-In Synthetic 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 Kyung In Synthetic Corp are associated (or correlated) with PLAYWITH. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PLAYWITH has no effect on the direction of Kyung-In Synthetic i.e., Kyung-In Synthetic and PLAYWITH go up and down completely randomly.
Pair Corralation between Kyung-In Synthetic and PLAYWITH
Assuming the 90 days trading horizon Kyung In Synthetic Corp is expected to generate 0.56 times more return on investment than PLAYWITH. However, Kyung In Synthetic Corp is 1.78 times less risky than PLAYWITH. It trades about -0.03 of its potential returns per unit of risk. PLAYWITH is currently generating about -0.02 per unit of risk. If you would invest 405,999 in Kyung In Synthetic Corp on September 26, 2024 and sell it today you would lose (124,499) from holding Kyung In Synthetic Corp or give up 30.66% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Kyung In Synthetic Corp vs. PLAYWITH
Performance |
Timeline |
Kyung In Synthetic |
PLAYWITH |
Kyung-In Synthetic and PLAYWITH Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Kyung-In Synthetic and PLAYWITH
The main advantage of trading using opposite Kyung-In Synthetic and PLAYWITH positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Kyung-In Synthetic position performs unexpectedly, PLAYWITH 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 PLAYWITH will offset losses from the drop in PLAYWITH's long position.Kyung-In Synthetic vs. AptaBio Therapeutics | Kyung-In Synthetic vs. Wonbang Tech Co | Kyung-In Synthetic vs. Busan Industrial Co | Kyung-In Synthetic vs. Busan Ind |
PLAYWITH vs. Daol Investment Securities | PLAYWITH vs. KPX Green Chemical | PLAYWITH vs. Youngbo Chemical Co | PLAYWITH vs. Kyung In Synthetic Corp |
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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