Correlation Between LK Engineering and I Sheng
Can any of the company-specific risk be diversified away by investing in both LK Engineering and I Sheng 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 LK Engineering and I Sheng into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between LK Engineering Co and I Sheng Electric Wire, you can compare the effects of market volatilities on LK Engineering and I Sheng 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 LK Engineering with a short position of I Sheng. Check out your portfolio center. Please also check ongoing floating volatility patterns of LK Engineering and I Sheng.
Diversification Opportunities for LK Engineering and I Sheng
0.29 | Correlation Coefficient |
Modest diversification
The 3 months correlation between 6139 and 6115 is 0.29. Overlapping area represents the amount of risk that can be diversified away by holding LK Engineering Co and I Sheng Electric Wire in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on I Sheng Electric and LK Engineering 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 LK Engineering Co are associated (or correlated) with I Sheng. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of I Sheng Electric has no effect on the direction of LK Engineering i.e., LK Engineering and I Sheng go up and down completely randomly.
Pair Corralation between LK Engineering and I Sheng
Assuming the 90 days trading horizon LK Engineering Co is expected to generate 3.97 times more return on investment than I Sheng. However, LK Engineering is 3.97 times more volatile than I Sheng Electric Wire. It trades about 0.12 of its potential returns per unit of risk. I Sheng Electric Wire is currently generating about 0.04 per unit of risk. If you would invest 6,040 in LK Engineering Co on September 2, 2024 and sell it today you would earn a total of 16,960 from holding LK Engineering Co or generate 280.79% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
LK Engineering Co vs. I Sheng Electric Wire
Performance |
| Timeline |
| LK Engineering |
| I Sheng Electric |
LK Engineering and I Sheng Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with LK Engineering and I Sheng
The main advantage of trading using opposite LK Engineering and I Sheng positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if LK Engineering position performs unexpectedly, I Sheng 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 I Sheng will offset losses from the drop in I Sheng's long position.| LK Engineering vs. United Integrated Services | LK Engineering vs. Topco Scientific Co | LK Engineering vs. Marketech International Corp | LK Engineering vs. Asia Optical Co |
| I Sheng vs. Unitech Computer Co | I Sheng vs. Far EasTone Telecommunications | I Sheng vs. Tai Tung Communication | I Sheng vs. Arima Communications 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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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