Correlation Between Silicon Laboratories and Nano Labs
Can any of the company-specific risk be diversified away by investing in both Silicon Laboratories and Nano Labs 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 Silicon Laboratories and Nano Labs into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Silicon Laboratories and Nano Labs, you can compare the effects of market volatilities on Silicon Laboratories and Nano Labs 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 Silicon Laboratories with a short position of Nano Labs. Check out your portfolio center. Please also check ongoing floating volatility patterns of Silicon Laboratories and Nano Labs.
Diversification Opportunities for Silicon Laboratories and Nano Labs
0.4 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Silicon and Nano is 0.4. Overlapping area represents the amount of risk that can be diversified away by holding Silicon Laboratories and Nano Labs in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Nano Labs and Silicon Laboratories 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 Silicon Laboratories are associated (or correlated) with Nano Labs. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Nano Labs has no effect on the direction of Silicon Laboratories i.e., Silicon Laboratories and Nano Labs go up and down completely randomly.
Pair Corralation between Silicon Laboratories and Nano Labs
Given the investment horizon of 90 days Silicon Laboratories is expected to generate 0.35 times more return on investment than Nano Labs. However, Silicon Laboratories is 2.89 times less risky than Nano Labs. It trades about 0.19 of its potential returns per unit of risk. Nano Labs is currently generating about -0.23 per unit of risk. If you would invest 12,505 in Silicon Laboratories on November 2, 2024 and sell it today you would earn a total of 1,078 from holding Silicon Laboratories or generate 8.62% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Silicon Laboratories vs. Nano Labs
Performance |
| Timeline |
| Silicon Laboratories |
| Nano Labs |
Silicon Laboratories and Nano Labs Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Silicon Laboratories and Nano Labs
The main advantage of trading using opposite Silicon Laboratories and Nano Labs positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Silicon Laboratories position performs unexpectedly, Nano Labs 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 Nano Labs will offset losses from the drop in Nano Labs' long position.| Silicon Laboratories vs. Diodes Incorporated | Silicon Laboratories vs. MACOM Technology Solutions | Silicon Laboratories vs. FormFactor | Silicon Laboratories vs. Amkor Technology |
| Nano Labs vs. SEALSQ Corp | Nano Labs vs. GSI Technology | Nano Labs vs. SemiLEDS | Nano Labs vs. ChipMOS Technologies |
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 Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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