Correlation Between Mind Technology and FormFactor
Can any of the company-specific risk be diversified away by investing in both Mind Technology and FormFactor 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 Mind Technology and FormFactor into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mind Technology and FormFactor, you can compare the effects of market volatilities on Mind Technology and FormFactor 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 Mind Technology with a short position of FormFactor. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mind Technology and FormFactor.
Diversification Opportunities for Mind Technology and FormFactor
0.13 | Correlation Coefficient |
Average diversification
The 3 months correlation between Mind and FormFactor is 0.13. Overlapping area represents the amount of risk that can be diversified away by holding Mind Technology and FormFactor in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on FormFactor and Mind Technology 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 Mind Technology are associated (or correlated) with FormFactor. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of FormFactor has no effect on the direction of Mind Technology i.e., Mind Technology and FormFactor go up and down completely randomly.
Pair Corralation between Mind Technology and FormFactor
Given the investment horizon of 90 days Mind Technology is expected to under-perform the FormFactor. But the stock apears to be less risky and, when comparing its historical volatility, Mind Technology is 1.05 times less risky than FormFactor. The stock trades about -0.05 of its potential returns per unit of risk. The FormFactor is currently generating about -0.04 of returns per unit of risk over similar time horizon. If you would invest 5,580 in FormFactor on September 3, 2024 and sell it today you would lose (1,324) from holding FormFactor or give up 23.73% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Mind Technology vs. FormFactor
Performance |
Timeline |
Mind Technology |
FormFactor |
Mind Technology and FormFactor Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mind Technology and FormFactor
The main advantage of trading using opposite Mind Technology and FormFactor positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mind Technology position performs unexpectedly, FormFactor 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 FormFactor will offset losses from the drop in FormFactor's long position.Mind Technology vs. Spectris plc | Mind Technology vs. Electro Sensors | Mind Technology vs. Sono Tek Corp | Mind Technology vs. Vishay Precision Group |
FormFactor vs. Silicon Laboratories | FormFactor vs. Diodes Incorporated | FormFactor vs. MACOM Technology Solutions | FormFactor vs. Amkor Technology |
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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