Correlation Between Travelers Companies and GEO JS
Can any of the company-specific risk be diversified away by investing in both Travelers Companies and GEO JS 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 GEO JS 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 GEO JS Tech, you can compare the effects of market volatilities on Travelers Companies and GEO JS 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 GEO JS. Check out your portfolio center. Please also check ongoing floating volatility patterns of Travelers Companies and GEO JS.
Diversification Opportunities for Travelers Companies and GEO JS
0.24 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Travelers and GEO is 0.24. Overlapping area represents the amount of risk that can be diversified away by holding The Travelers Companies and GEO JS Tech in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on GEO JS Tech 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 GEO JS. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of GEO JS Tech has no effect on the direction of Travelers Companies i.e., Travelers Companies and GEO JS go up and down completely randomly.
Pair Corralation between Travelers Companies and GEO JS
Considering the 90-day investment horizon Travelers Companies is expected to generate 21.02 times less return on investment than GEO JS. But when comparing it to its historical volatility, The Travelers Companies is 3.54 times less risky than GEO JS. It trades about 0.04 of its potential returns per unit of risk. GEO JS Tech is currently generating about 0.22 of returns per unit of risk over similar time horizon. If you would invest 0.30 in GEO JS Tech on October 20, 2024 and sell it today you would earn a total of 0.06 from holding GEO JS Tech or generate 20.0% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 95.24% |
| Values | Daily Returns |
The Travelers Companies vs. GEO JS Tech
Performance |
| Timeline |
| The Travelers Companies |
| GEO JS Tech |
Travelers Companies and GEO JS Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Travelers Companies and GEO JS
The main advantage of trading using opposite Travelers Companies and GEO JS positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Travelers Companies position performs unexpectedly, GEO JS 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 GEO JS will offset losses from the drop in GEO JS's long position.| Travelers Companies vs. Progressive Corp | Travelers Companies vs. Chubb | Travelers Companies vs. Cincinnati Financial | Travelers Companies vs. W R Berkley |
| GEO JS vs. Durango Resources | GEO JS vs. Avarone Metals | GEO JS vs. Pampa Metals | GEO JS vs. Sun Summit Minerals |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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