Correlation Between Fabrinet and Digi International
Can any of the company-specific risk be diversified away by investing in both Fabrinet and Digi International 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 Fabrinet and Digi International into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Fabrinet and Digi International, you can compare the effects of market volatilities on Fabrinet and Digi International 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 Fabrinet with a short position of Digi International. Check out your portfolio center. Please also check ongoing floating volatility patterns of Fabrinet and Digi International.
Diversification Opportunities for Fabrinet and Digi International
0.61 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Fabrinet and Digi is 0.61. Overlapping area represents the amount of risk that can be diversified away by holding Fabrinet and Digi International in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Digi International and Fabrinet 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 Fabrinet are associated (or correlated) with Digi International. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Digi International has no effect on the direction of Fabrinet i.e., Fabrinet and Digi International go up and down completely randomly.
Pair Corralation between Fabrinet and Digi International
Allowing for the 90-day total investment horizon Fabrinet is expected to generate 1.08 times less return on investment than Digi International. In addition to that, Fabrinet is 1.18 times more volatile than Digi International. It trades about 0.03 of its total potential returns per unit of risk. Digi International is currently generating about 0.03 per unit of volatility. If you would invest 2,956 in Digi International on August 27, 2024 and sell it today you would earn a total of 339.00 from holding Digi International or generate 11.47% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Fabrinet vs. Digi International
Performance |
| Timeline |
| Fabrinet |
| Digi International |
Fabrinet and Digi International Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Fabrinet and Digi International
The main advantage of trading using opposite Fabrinet and Digi International positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Fabrinet position performs unexpectedly, Digi International 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 Digi International will offset losses from the drop in Digi International's long position.| Fabrinet vs. Plexus Corp | Fabrinet vs. Benchmark Electronics | Fabrinet vs. Jabil Circuit | Fabrinet vs. Sanmina |
| Digi International vs. Ichor Holdings | Digi International vs. Fabrinet | Digi International vs. Hello Group | Digi International vs. Ultra Clean Holdings |
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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