Correlation Between ON Semiconductor and Wolfspeed
Can any of the company-specific risk be diversified away by investing in both ON Semiconductor and Wolfspeed 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 ON Semiconductor and Wolfspeed into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between ON Semiconductor and Wolfspeed, you can compare the effects of market volatilities on ON Semiconductor and Wolfspeed 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 ON Semiconductor with a short position of Wolfspeed. Check out your portfolio center. Please also check ongoing floating volatility patterns of ON Semiconductor and Wolfspeed.
Diversification Opportunities for ON Semiconductor and Wolfspeed
0.22 | Correlation Coefficient |
Modest diversification
The 3 months correlation between ON Semiconductor and Wolfspeed is 0.22. Overlapping area represents the amount of risk that can be diversified away by holding ON Semiconductor and Wolfspeed in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Wolfspeed and ON Semiconductor 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 ON Semiconductor are associated (or correlated) with Wolfspeed. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Wolfspeed has no effect on the direction of ON Semiconductor i.e., ON Semiconductor and Wolfspeed go up and down completely randomly.
Pair Corralation between ON Semiconductor and Wolfspeed
Allowing for the 90-day total investment horizon ON Semiconductor is expected to generate 0.15 times more return on investment than Wolfspeed. However, ON Semiconductor is 6.61 times less risky than Wolfspeed. It trades about -0.07 of its potential returns per unit of risk. Wolfspeed is currently generating about -0.08 per unit of risk. If you would invest 7,224 in ON Semiconductor on August 27, 2024 and sell it today you would lose (262.00) from holding ON Semiconductor or give up 3.63% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
ON Semiconductor vs. Wolfspeed
Performance |
| Timeline |
| ON Semiconductor |
| Wolfspeed |
ON Semiconductor and Wolfspeed Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with ON Semiconductor and Wolfspeed
The main advantage of trading using opposite ON Semiconductor and Wolfspeed positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if ON Semiconductor position performs unexpectedly, Wolfspeed 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 Wolfspeed will offset losses from the drop in Wolfspeed's long position.| ON Semiconductor vs. Texas Instruments Incorporated | ON Semiconductor vs. Microchip Technology | ON Semiconductor vs. Analog Devices | ON Semiconductor vs. Qorvo Inc |
| Wolfspeed vs. NXP Semiconductors NV | Wolfspeed vs. Analog Devices | Wolfspeed vs. Microchip Technology | Wolfspeed vs. Monolithic Power Systems |
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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