Correlation Between Dunham High and Alger Spectra
Can any of the company-specific risk be diversified away by investing in both Dunham High and Alger Spectra 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 Dunham High and Alger Spectra into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Dunham High Yield and Alger Spectra, you can compare the effects of market volatilities on Dunham High and Alger Spectra 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 Dunham High with a short position of Alger Spectra. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dunham High and Alger Spectra.
Diversification Opportunities for Dunham High and Alger Spectra
0.82 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Dunham and Alger is 0.82. Overlapping area represents the amount of risk that can be diversified away by holding Dunham High Yield and Alger Spectra in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Alger Spectra and Dunham High 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 Dunham High Yield are associated (or correlated) with Alger Spectra. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Alger Spectra has no effect on the direction of Dunham High i.e., Dunham High and Alger Spectra go up and down completely randomly.
Pair Corralation between Dunham High and Alger Spectra
Assuming the 90 days horizon Dunham High is expected to generate 11.79 times less return on investment than Alger Spectra. But when comparing it to its historical volatility, Dunham High Yield is 8.22 times less risky than Alger Spectra. It trades about 0.18 of its potential returns per unit of risk. Alger Spectra is currently generating about 0.26 of returns per unit of risk over similar time horizon. If you would invest 2,704 in Alger Spectra on September 2, 2024 and sell it today you would earn a total of 547.00 from holding Alger Spectra or generate 20.23% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Dunham High Yield vs. Alger Spectra
Performance |
| Timeline |
| Dunham High Yield |
| Alger Spectra |
Dunham High and Alger Spectra Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Dunham High and Alger Spectra
The main advantage of trading using opposite Dunham High and Alger Spectra positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dunham High position performs unexpectedly, Alger Spectra 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 Alger Spectra will offset losses from the drop in Alger Spectra's long position.| Dunham High vs. Hennessy Nerstone Mid | Dunham High vs. Columbia Small Cap | Dunham High vs. Palm Valley Capital | Dunham High vs. American Century Etf |
| Alger Spectra vs. Alger Midcap Growth | Alger Spectra vs. Alger Midcap Growth | Alger Spectra vs. Alger Mid Cap | Alger Spectra vs. Alger Small Cap |
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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