Correlation Between Franklin Credit and FactSet Research
Can any of the company-specific risk be diversified away by investing in both Franklin Credit and FactSet Research 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 Franklin Credit and FactSet Research into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Franklin Credit Management and FactSet Research Systems, you can compare the effects of market volatilities on Franklin Credit and FactSet Research 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 Franklin Credit with a short position of FactSet Research. Check out your portfolio center. Please also check ongoing floating volatility patterns of Franklin Credit and FactSet Research.
Diversification Opportunities for Franklin Credit and FactSet Research
0.0 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Franklin and FactSet is 0.0. Overlapping area represents the amount of risk that can be diversified away by holding Franklin Credit Management and FactSet Research Systems in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on FactSet Research Systems and Franklin Credit 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 Franklin Credit Management are associated (or correlated) with FactSet Research. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of FactSet Research Systems has no effect on the direction of Franklin Credit i.e., Franklin Credit and FactSet Research go up and down completely randomly.
Pair Corralation between Franklin Credit and FactSet Research
Given the investment horizon of 90 days Franklin Credit Management is expected to generate 3.66 times more return on investment than FactSet Research. However, Franklin Credit is 3.66 times more volatile than FactSet Research Systems. It trades about 0.06 of its potential returns per unit of risk. FactSet Research Systems is currently generating about 0.09 per unit of risk. If you would invest 10.00 in Franklin Credit Management on September 30, 2024 and sell it today you would earn a total of 1.00 from holding Franklin Credit Management or generate 10.0% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Flat |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Franklin Credit Management vs. FactSet Research Systems
Performance |
Timeline |
Franklin Credit Mana |
FactSet Research Systems |
Franklin Credit and FactSet Research Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Franklin Credit and FactSet Research
The main advantage of trading using opposite Franklin Credit and FactSet Research positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Franklin Credit position performs unexpectedly, FactSet Research 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 FactSet Research will offset losses from the drop in FactSet Research's long position.Franklin Credit vs. Citizens Financial Corp | Franklin Credit vs. Farmers Bancorp | Franklin Credit vs. Alpine Banks of | Franklin Credit vs. First Financial |
FactSet Research vs. Dun Bradstreet Holdings | FactSet Research vs. Moodys | FactSet Research vs. MSCI Inc | FactSet Research vs. Intercontinental Exchange |
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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