Correlation Between Kukdong Oil and Tae Kyung
Can any of the company-specific risk be diversified away by investing in both Kukdong Oil and Tae Kyung 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 Kukdong Oil and Tae Kyung into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Kukdong Oil Chemicals and Tae Kyung Chemical, you can compare the effects of market volatilities on Kukdong Oil and Tae Kyung 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 Kukdong Oil with a short position of Tae Kyung. Check out your portfolio center. Please also check ongoing floating volatility patterns of Kukdong Oil and Tae Kyung.
Diversification Opportunities for Kukdong Oil and Tae Kyung
0.46 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Kukdong and Tae is 0.46. Overlapping area represents the amount of risk that can be diversified away by holding Kukdong Oil Chemicals and Tae Kyung Chemical in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Tae Kyung Chemical and Kukdong Oil 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 Kukdong Oil Chemicals are associated (or correlated) with Tae Kyung. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Tae Kyung Chemical has no effect on the direction of Kukdong Oil i.e., Kukdong Oil and Tae Kyung go up and down completely randomly.
Pair Corralation between Kukdong Oil and Tae Kyung
Assuming the 90 days trading horizon Kukdong Oil Chemicals is expected to under-perform the Tae Kyung. But the stock apears to be less risky and, when comparing its historical volatility, Kukdong Oil Chemicals is 1.22 times less risky than Tae Kyung. The stock trades about -0.06 of its potential returns per unit of risk. The Tae Kyung Chemical is currently generating about -0.01 of returns per unit of risk over similar time horizon. If you would invest 1,088,000 in Tae Kyung Chemical on September 13, 2024 and sell it today you would lose (24,000) from holding Tae Kyung Chemical or give up 2.21% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Kukdong Oil Chemicals vs. Tae Kyung Chemical
Performance |
Timeline |
Kukdong Oil Chemicals |
Tae Kyung Chemical |
Kukdong Oil and Tae Kyung Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Kukdong Oil and Tae Kyung
The main advantage of trading using opposite Kukdong Oil and Tae Kyung positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Kukdong Oil position performs unexpectedly, Tae Kyung 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 Tae Kyung will offset losses from the drop in Tae Kyung's long position.Kukdong Oil vs. Samsung Electronics Co | Kukdong Oil vs. Samsung Electronics Co | Kukdong Oil vs. SK Hynix | Kukdong Oil vs. POSCO Holdings |
Tae Kyung vs. Samsung Electronics Co | Tae Kyung vs. Samsung Electronics Co | Tae Kyung vs. SK Hynix | Tae Kyung vs. POSCO Holdings |
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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