Correlation Between Russell 2000 and Banking Fund
Can any of the company-specific risk be diversified away by investing in both Russell 2000 and Banking Fund 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 Russell 2000 and Banking Fund into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Russell 2000 15x and Banking Fund Class, you can compare the effects of market volatilities on Russell 2000 and Banking Fund 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 Russell 2000 with a short position of Banking Fund. Check out your portfolio center. Please also check ongoing floating volatility patterns of Russell 2000 and Banking Fund.
Diversification Opportunities for Russell 2000 and Banking Fund
0.79 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Russell and Banking is 0.79. Overlapping area represents the amount of risk that can be diversified away by holding Russell 2000 15x and Banking Fund Class in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Banking Fund Class and Russell 2000 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 Russell 2000 15x are associated (or correlated) with Banking Fund. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Banking Fund Class has no effect on the direction of Russell 2000 i.e., Russell 2000 and Banking Fund go up and down completely randomly.
Pair Corralation between Russell 2000 and Banking Fund
Assuming the 90 days horizon Russell 2000 15x is expected to generate 1.19 times more return on investment than Banking Fund. However, Russell 2000 is 1.19 times more volatile than Banking Fund Class. It trades about 0.05 of its potential returns per unit of risk. Banking Fund Class is currently generating about 0.05 per unit of risk. If you would invest 4,496 in Russell 2000 15x on August 27, 2024 and sell it today you would earn a total of 1,950 from holding Russell 2000 15x or generate 43.37% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Russell 2000 15x vs. Banking Fund Class
Performance |
| Timeline |
| Russell 2000 15x |
| Banking Fund Class |
Russell 2000 and Banking Fund Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Russell 2000 and Banking Fund
The main advantage of trading using opposite Russell 2000 and Banking Fund positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Russell 2000 position performs unexpectedly, Banking Fund 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 Banking Fund will offset losses from the drop in Banking Fund's long position.| Russell 2000 vs. Basic Materials Fund | Russell 2000 vs. Basic Materials Fund | Russell 2000 vs. Banking Fund Class | Russell 2000 vs. Basic Materials Fund |
| Banking Fund vs. Qs Small Capitalization | Banking Fund vs. Massmutual Select Small | Banking Fund vs. Baird Smallmid Cap | Banking Fund vs. Kinetics 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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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