Correlation Between Settlebank and LS Materials
Can any of the company-specific risk be diversified away by investing in both Settlebank and LS Materials 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 Settlebank and LS Materials into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Settlebank and LS Materials, you can compare the effects of market volatilities on Settlebank and LS Materials 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 Settlebank with a short position of LS Materials. Check out your portfolio center. Please also check ongoing floating volatility patterns of Settlebank and LS Materials.
Diversification Opportunities for Settlebank and LS Materials
0.62 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Settlebank and 417200 is 0.62. Overlapping area represents the amount of risk that can be diversified away by holding Settlebank and LS Materials in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on LS Materials and Settlebank 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 Settlebank are associated (or correlated) with LS Materials. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of LS Materials has no effect on the direction of Settlebank i.e., Settlebank and LS Materials go up and down completely randomly.
Pair Corralation between Settlebank and LS Materials
Assuming the 90 days trading horizon Settlebank is expected to under-perform the LS Materials. But the stock apears to be less risky and, when comparing its historical volatility, Settlebank is 5.56 times less risky than LS Materials. The stock trades about -0.01 of its potential returns per unit of risk. The LS Materials is currently generating about 0.05 of returns per unit of risk over similar time horizon. If you would invest 599,449 in LS Materials on November 6, 2024 and sell it today you would earn a total of 645,551 from holding LS Materials or generate 107.69% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 69.77% |
| Values | Daily Returns |
Settlebank vs. LS Materials
Performance |
| Timeline |
| Settlebank |
| LS Materials |
Settlebank and LS Materials Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Settlebank and LS Materials
The main advantage of trading using opposite Settlebank and LS Materials positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Settlebank position performs unexpectedly, LS Materials 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 LS Materials will offset losses from the drop in LS Materials' long position.| Settlebank vs. SK Chemicals Co | Settlebank vs. Sung Bo Chemicals | Settlebank vs. Kukil Metal Co | Settlebank vs. Jinro Distillers Co |
| LS Materials vs. Samsung Electronics Co | LS Materials vs. Samsung Electronics Co | LS Materials vs. LG Energy Solution | LS Materials vs. SK Hynix |
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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