Correlation Between Retailing Fund and Banking Fund
Can any of the company-specific risk be diversified away by investing in both Retailing Fund 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 Retailing Fund and Banking Fund into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Retailing Fund Investor and Banking Fund Class, you can compare the effects of market volatilities on Retailing Fund 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 Retailing Fund with a short position of Banking Fund. Check out your portfolio center. Please also check ongoing floating volatility patterns of Retailing Fund and Banking Fund.
Diversification Opportunities for Retailing Fund and Banking Fund
0.58 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Retailing and BANKING is 0.58. Overlapping area represents the amount of risk that can be diversified away by holding Retailing Fund Investor 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 Retailing Fund 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 Retailing Fund Investor 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 Retailing Fund i.e., Retailing Fund and Banking Fund go up and down completely randomly.
Pair Corralation between Retailing Fund and Banking Fund
Assuming the 90 days horizon Retailing Fund is expected to generate 1.95 times less return on investment than Banking Fund. But when comparing it to its historical volatility, Retailing Fund Investor is 2.79 times less risky than Banking Fund. It trades about 0.32 of its potential returns per unit of risk. Banking Fund Class is currently generating about 0.22 of returns per unit of risk over similar time horizon. If you would invest 9,055 in Banking Fund Class on August 30, 2024 and sell it today you would earn a total of 1,073 from holding Banking Fund Class or generate 11.85% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 95.65% |
Values | Daily Returns |
Retailing Fund Investor vs. Banking Fund Class
Performance |
Timeline |
Retailing Fund Investor |
Banking Fund Class |
Retailing Fund and Banking Fund Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Retailing Fund and Banking Fund
The main advantage of trading using opposite Retailing Fund and Banking Fund positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Retailing Fund 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.Retailing Fund vs. Leisure Fund Investor | Retailing Fund vs. Banking Fund Investor | Retailing Fund vs. Technology Fund Investor | Retailing Fund vs. Financial Services Fund |
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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 Portfolio Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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