Correlation Between Qs Growth and Western Asset
Can any of the company-specific risk be diversified away by investing in both Qs Growth and Western Asset 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 Qs Growth and Western Asset into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Qs Growth Fund and Western Asset Intermediate, you can compare the effects of market volatilities on Qs Growth and Western Asset 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 Qs Growth with a short position of Western Asset. Check out your portfolio center. Please also check ongoing floating volatility patterns of Qs Growth and Western Asset.
Diversification Opportunities for Qs Growth and Western Asset
-0.62 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between SCHCX and Western is -0.62. Overlapping area represents the amount of risk that can be diversified away by holding Qs Growth Fund and Western Asset Intermediate in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Western Asset Interm and Qs Growth 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 Qs Growth Fund are associated (or correlated) with Western Asset. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Western Asset Interm has no effect on the direction of Qs Growth i.e., Qs Growth and Western Asset go up and down completely randomly.
Pair Corralation between Qs Growth and Western Asset
Assuming the 90 days horizon Qs Growth Fund is expected to generate 3.13 times more return on investment than Western Asset. However, Qs Growth is 3.13 times more volatile than Western Asset Intermediate. It trades about 0.1 of its potential returns per unit of risk. Western Asset Intermediate is currently generating about -0.13 per unit of risk. If you would invest 1,648 in Qs Growth Fund on August 24, 2024 and sell it today you would earn a total of 25.00 from holding Qs Growth Fund or generate 1.52% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Qs Growth Fund vs. Western Asset Intermediate
Performance |
| Timeline |
| Qs Growth Fund |
| Western Asset Interm |
Qs Growth and Western Asset Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Qs Growth and Western Asset
The main advantage of trading using opposite Qs Growth and Western Asset positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Qs Growth position performs unexpectedly, Western Asset 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 Western Asset will offset losses from the drop in Western Asset's long position.| Qs Growth vs. Biotechnology Ultrasector Profund | Qs Growth vs. Janus Global Technology | Qs Growth vs. Icon Information Technology | Qs Growth vs. Hennessy Technology Fund |
| Western Asset vs. Guggenheim Long Short | Western Asset vs. Astor Longshort Fund | Western Asset vs. Ultra Short Term Fixed | Western Asset vs. Old Westbury Short Term |
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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