Correlation Between Old Westbury and Franklin Federal
Can any of the company-specific risk be diversified away by investing in both Old Westbury and Franklin Federal 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 Old Westbury and Franklin Federal into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Old Westbury Large and Franklin Federal Tax Free, you can compare the effects of market volatilities on Old Westbury and Franklin Federal 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 Old Westbury with a short position of Franklin Federal. Check out your portfolio center. Please also check ongoing floating volatility patterns of Old Westbury and Franklin Federal.
Diversification Opportunities for Old Westbury and Franklin Federal
0.18 | Correlation Coefficient |
Average diversification
The 3 months correlation between Old and Franklin is 0.18. Overlapping area represents the amount of risk that can be diversified away by holding Old Westbury Large and Franklin Federal Tax Free in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Franklin Federal Tax and Old Westbury 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 Old Westbury Large are associated (or correlated) with Franklin Federal. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Franklin Federal Tax has no effect on the direction of Old Westbury i.e., Old Westbury and Franklin Federal go up and down completely randomly.
Pair Corralation between Old Westbury and Franklin Federal
Assuming the 90 days horizon Old Westbury Large is expected to generate 2.86 times more return on investment than Franklin Federal. However, Old Westbury is 2.86 times more volatile than Franklin Federal Tax Free. It trades about 0.11 of its potential returns per unit of risk. Franklin Federal Tax Free is currently generating about 0.08 per unit of risk. If you would invest 1,442 in Old Westbury Large on September 12, 2024 and sell it today you would earn a total of 720.00 from holding Old Westbury Large or generate 49.93% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Old Westbury Large vs. Franklin Federal Tax Free
Performance |
| Timeline |
| Old Westbury Large |
| Franklin Federal Tax |
Old Westbury and Franklin Federal Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Old Westbury and Franklin Federal
The main advantage of trading using opposite Old Westbury and Franklin Federal positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Old Westbury position performs unexpectedly, Franklin Federal 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 Franklin Federal will offset losses from the drop in Franklin Federal's long position.| Old Westbury vs. Lord Abbett Government | Old Westbury vs. Us Government Securities | Old Westbury vs. Dreyfus Government Cash | Old Westbury vs. Goldman Sachs Government |
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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