Correlation Between Tigo Energy and Cannae Holdings
Can any of the company-specific risk be diversified away by investing in both Tigo Energy and Cannae Holdings 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 Tigo Energy and Cannae Holdings into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Tigo Energy and Cannae Holdings, you can compare the effects of market volatilities on Tigo Energy and Cannae Holdings 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 Tigo Energy with a short position of Cannae Holdings. Check out your portfolio center. Please also check ongoing floating volatility patterns of Tigo Energy and Cannae Holdings.
Diversification Opportunities for Tigo Energy and Cannae Holdings
-0.73 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Tigo and Cannae is -0.73. Overlapping area represents the amount of risk that can be diversified away by holding Tigo Energy and Cannae Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Cannae Holdings and Tigo Energy 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 Tigo Energy are associated (or correlated) with Cannae Holdings. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Cannae Holdings has no effect on the direction of Tigo Energy i.e., Tigo Energy and Cannae Holdings go up and down completely randomly.
Pair Corralation between Tigo Energy and Cannae Holdings
Given the investment horizon of 90 days Tigo Energy is expected to generate 5.39 times more return on investment than Cannae Holdings. However, Tigo Energy is 5.39 times more volatile than Cannae Holdings. It trades about 0.04 of its potential returns per unit of risk. Cannae Holdings is currently generating about -0.2 per unit of risk. If you would invest 93.00 in Tigo Energy on September 23, 2024 and sell it today you would earn a total of 1.00 from holding Tigo Energy or generate 1.08% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Tigo Energy vs. Cannae Holdings
Performance |
Timeline |
Tigo Energy |
Cannae Holdings |
Tigo Energy and Cannae Holdings Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Tigo Energy and Cannae Holdings
The main advantage of trading using opposite Tigo Energy and Cannae Holdings positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Tigo Energy position performs unexpectedly, Cannae Holdings 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 Cannae Holdings will offset losses from the drop in Cannae Holdings' long position.Tigo Energy vs. Diodes Incorporated | Tigo Energy vs. Daqo New Energy | Tigo Energy vs. MagnaChip Semiconductor | Tigo Energy vs. Nano Labs |
Cannae Holdings vs. Brightsphere Investment Group | Cannae Holdings vs. Adtalem Global Education | Cannae Holdings vs. ConnectOne Bancorp | Cannae Holdings vs. Aquagold International |
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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