Correlation Between FTC Solar and POET Technologies
Can any of the company-specific risk be diversified away by investing in both FTC Solar and POET Technologies 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 FTC Solar and POET Technologies into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between FTC Solar and POET Technologies, you can compare the effects of market volatilities on FTC Solar and POET Technologies 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 FTC Solar with a short position of POET Technologies. Check out your portfolio center. Please also check ongoing floating volatility patterns of FTC Solar and POET Technologies.
Diversification Opportunities for FTC Solar and POET Technologies
-0.37 | Correlation Coefficient |
Very good diversification
The 3 months correlation between FTC and POET is -0.37. Overlapping area represents the amount of risk that can be diversified away by holding FTC Solar and POET Technologies in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on POET Technologies and FTC Solar 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 FTC Solar are associated (or correlated) with POET Technologies. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of POET Technologies has no effect on the direction of FTC Solar i.e., FTC Solar and POET Technologies go up and down completely randomly.
Pair Corralation between FTC Solar and POET Technologies
Given the investment horizon of 90 days FTC Solar is expected to generate 1.75 times less return on investment than POET Technologies. In addition to that, FTC Solar is 1.3 times more volatile than POET Technologies. It trades about 0.05 of its total potential returns per unit of risk. POET Technologies is currently generating about 0.12 per unit of volatility. If you would invest 137.00 in POET Technologies on October 2, 2024 and sell it today you would earn a total of 458.00 from holding POET Technologies or generate 334.31% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
FTC Solar vs. POET Technologies
Performance |
Timeline |
FTC Solar |
POET Technologies |
FTC Solar and POET Technologies Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with FTC Solar and POET Technologies
The main advantage of trading using opposite FTC Solar and POET Technologies positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if FTC Solar position performs unexpectedly, POET Technologies 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 POET Technologies will offset losses from the drop in POET Technologies' long position.FTC Solar vs. Sunnova Energy International | FTC Solar vs. JinkoSolar Holding | FTC Solar vs. Nextracker Class A | FTC Solar vs. Canadian Solar |
POET Technologies vs. Gold Fields Ltd | POET Technologies vs. Exagen Inc | POET Technologies vs. Amylyx Pharmaceuticals | POET Technologies vs. Collegium Pharmaceutical |
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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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