Correlation Between Samsung KODEX and Fine Besteel
Can any of the company-specific risk be diversified away by investing in both Samsung KODEX and Fine Besteel 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 Samsung KODEX and Fine Besteel into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Samsung KODEX IT and Fine Besteel Co, you can compare the effects of market volatilities on Samsung KODEX and Fine Besteel 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 Samsung KODEX with a short position of Fine Besteel. Check out your portfolio center. Please also check ongoing floating volatility patterns of Samsung KODEX and Fine Besteel.
Diversification Opportunities for Samsung KODEX and Fine Besteel
-0.15 | Correlation Coefficient |
Good diversification
The 3 months correlation between Samsung and Fine is -0.15. Overlapping area represents the amount of risk that can be diversified away by holding Samsung KODEX IT and Fine Besteel Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Fine Besteel and Samsung KODEX 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 Samsung KODEX IT are associated (or correlated) with Fine Besteel. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Fine Besteel has no effect on the direction of Samsung KODEX i.e., Samsung KODEX and Fine Besteel go up and down completely randomly.
Pair Corralation between Samsung KODEX and Fine Besteel
Assuming the 90 days trading horizon Samsung KODEX IT is expected to generate 0.57 times more return on investment than Fine Besteel. However, Samsung KODEX IT is 1.74 times less risky than Fine Besteel. It trades about 0.0 of its potential returns per unit of risk. Fine Besteel Co is currently generating about -0.04 per unit of risk. If you would invest 1,587,726 in Samsung KODEX IT on August 24, 2024 and sell it today you would lose (77,726) from holding Samsung KODEX IT or give up 4.9% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Samsung KODEX IT vs. Fine Besteel Co
Performance |
| Timeline |
| Samsung KODEX IT |
| Fine Besteel |
Samsung KODEX and Fine Besteel Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Samsung KODEX and Fine Besteel
The main advantage of trading using opposite Samsung KODEX and Fine Besteel positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Samsung KODEX position performs unexpectedly, Fine Besteel 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 Fine Besteel will offset losses from the drop in Fine Besteel's long position.| Samsung KODEX vs. Busan Industrial Co | Samsung KODEX vs. Busan Ind | Samsung KODEX vs. Mirae Asset Daewoo | Samsung KODEX vs. Shinhan WTI Futures |
| Fine Besteel vs. AptaBio Therapeutics | Fine Besteel vs. Daewoo SBI SPAC | Fine Besteel vs. Dream Security co | Fine Besteel vs. Microfriend |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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