Correlation Between Celestica and KULR Technology
Can any of the company-specific risk be diversified away by investing in both Celestica and KULR Technology 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 Celestica and KULR Technology into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Celestica and KULR Technology Group, you can compare the effects of market volatilities on Celestica and KULR Technology 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 Celestica with a short position of KULR Technology. Check out your portfolio center. Please also check ongoing floating volatility patterns of Celestica and KULR Technology.
Diversification Opportunities for Celestica and KULR Technology
0.78 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Celestica and KULR is 0.78. Overlapping area represents the amount of risk that can be diversified away by holding Celestica and KULR Technology Group in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on KULR Technology Group and Celestica 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 Celestica are associated (or correlated) with KULR Technology. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of KULR Technology Group has no effect on the direction of Celestica i.e., Celestica and KULR Technology go up and down completely randomly.
Pair Corralation between Celestica and KULR Technology
Considering the 90-day investment horizon Celestica is expected to generate 2.28 times less return on investment than KULR Technology. But when comparing it to its historical volatility, Celestica is 2.88 times less risky than KULR Technology. It trades about 0.13 of its potential returns per unit of risk. KULR Technology Group is currently generating about 0.1 of returns per unit of risk over similar time horizon. If you would invest 15.00 in KULR Technology Group on August 27, 2024 and sell it today you would earn a total of 30.00 from holding KULR Technology Group or generate 200.0% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Celestica vs. KULR Technology Group
Performance |
| Timeline |
| Celestica |
| KULR Technology Group |
Celestica and KULR Technology Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Celestica and KULR Technology
The main advantage of trading using opposite Celestica and KULR Technology positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Celestica position performs unexpectedly, KULR Technology 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 KULR Technology will offset losses from the drop in KULR Technology's long position.| Celestica vs. Plexus Corp | Celestica vs. Benchmark Electronics | Celestica vs. Jabil Circuit | Celestica vs. Sanmina |
| KULR Technology vs. Plexus Corp | KULR Technology vs. Benchmark Electronics | KULR Technology vs. Jabil Circuit | KULR Technology vs. Sanmina |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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