Correlation Between Travelers Companies and FT Cboe
Can any of the company-specific risk be diversified away by investing in both Travelers Companies and FT Cboe 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 Travelers Companies and FT Cboe into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between The Travelers Companies and FT Cboe Vest, you can compare the effects of market volatilities on Travelers Companies and FT Cboe 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 Travelers Companies with a short position of FT Cboe. Check out your portfolio center. Please also check ongoing floating volatility patterns of Travelers Companies and FT Cboe.
Diversification Opportunities for Travelers Companies and FT Cboe
0.82 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Travelers and XNOV is 0.82. Overlapping area represents the amount of risk that can be diversified away by holding The Travelers Companies and FT Cboe Vest in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on FT Cboe Vest and Travelers Companies 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 The Travelers Companies are associated (or correlated) with FT Cboe. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of FT Cboe Vest has no effect on the direction of Travelers Companies i.e., Travelers Companies and FT Cboe go up and down completely randomly.
Pair Corralation between Travelers Companies and FT Cboe
Considering the 90-day investment horizon The Travelers Companies is expected to generate 25.54 times more return on investment than FT Cboe. However, Travelers Companies is 25.54 times more volatile than FT Cboe Vest. It trades about 0.15 of its potential returns per unit of risk. FT Cboe Vest is currently generating about 0.58 per unit of risk. If you would invest 23,412 in The Travelers Companies on August 29, 2024 and sell it today you would earn a total of 2,965 from holding The Travelers Companies or generate 12.66% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
The Travelers Companies vs. FT Cboe Vest
Performance |
| Timeline |
| The Travelers Companies |
| FT Cboe Vest |
Travelers Companies and FT Cboe Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Travelers Companies and FT Cboe
The main advantage of trading using opposite Travelers Companies and FT Cboe positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Travelers Companies position performs unexpectedly, FT Cboe 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 FT Cboe will offset losses from the drop in FT Cboe's long position.| Travelers Companies vs. Argo Group International | Travelers Companies vs. Donegal Group A | Travelers Companies vs. Selective Insurance Group |
| FT Cboe vs. ABIVAX Socit Anonyme | FT Cboe vs. Pinnacle Sherman Multi Strategy | FT Cboe vs. Morningstar Unconstrained Allocation | FT Cboe vs. SPACE |
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 Cryptocurrency Center module to build and monitor diversified portfolio of extremely risky digital assets and cryptocurrency.
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