Correlation Between Fathom Holdings and Grand City
Can any of the company-specific risk be diversified away by investing in both Fathom Holdings and Grand City 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 Fathom Holdings and Grand City into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Fathom Holdings and Grand City Properties, you can compare the effects of market volatilities on Fathom Holdings and Grand City 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 Fathom Holdings with a short position of Grand City. Check out your portfolio center. Please also check ongoing floating volatility patterns of Fathom Holdings and Grand City.
Diversification Opportunities for Fathom Holdings and Grand City
0.74 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Fathom and Grand is 0.74. Overlapping area represents the amount of risk that can be diversified away by holding Fathom Holdings and Grand City Properties in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Grand City Properties and Fathom Holdings 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 Fathom Holdings are associated (or correlated) with Grand City. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Grand City Properties has no effect on the direction of Fathom Holdings i.e., Fathom Holdings and Grand City go up and down completely randomly.
Pair Corralation between Fathom Holdings and Grand City
Given the investment horizon of 90 days Fathom Holdings is expected to under-perform the Grand City. In addition to that, Fathom Holdings is 4.17 times more volatile than Grand City Properties. It trades about -0.16 of its total potential returns per unit of risk. Grand City Properties is currently generating about -0.2 per unit of volatility. If you would invest 1,400 in Grand City Properties on September 20, 2024 and sell it today you would lose (191.00) from holding Grand City Properties or give up 13.64% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Fathom Holdings vs. Grand City Properties
Performance |
| Timeline |
| Fathom Holdings |
| Grand City Properties |
Fathom Holdings and Grand City Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Fathom Holdings and Grand City
The main advantage of trading using opposite Fathom Holdings and Grand City positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Fathom Holdings position performs unexpectedly, Grand City 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 Grand City will offset losses from the drop in Grand City's long position.| Fathom Holdings vs. Frp Holdings Ord | Fathom Holdings vs. Marcus Millichap | Fathom Holdings vs. Transcontinental Realty Investors | Fathom Holdings vs. Anywhere Real Estate |
| Grand City vs. J W Mays | Grand City vs. Frp Holdings Ord | Grand City vs. Maui Land Pineapple | Grand City vs. Fathom Holdings |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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