Correlation Between GBS Software and AUST AGRICULTURAL
Can any of the company-specific risk be diversified away by investing in both GBS Software and AUST AGRICULTURAL 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 GBS Software and AUST AGRICULTURAL into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between GBS Software AG and AUST AGRICULTURAL, you can compare the effects of market volatilities on GBS Software and AUST AGRICULTURAL 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 GBS Software with a short position of AUST AGRICULTURAL. Check out your portfolio center. Please also check ongoing floating volatility patterns of GBS Software and AUST AGRICULTURAL.
Diversification Opportunities for GBS Software and AUST AGRICULTURAL
-0.59 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between GBS and AUST is -0.59. Overlapping area represents the amount of risk that can be diversified away by holding GBS Software AG and AUST AGRICULTURAL in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on AUST AGRICULTURAL and GBS Software 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 GBS Software AG are associated (or correlated) with AUST AGRICULTURAL. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of AUST AGRICULTURAL has no effect on the direction of GBS Software i.e., GBS Software and AUST AGRICULTURAL go up and down completely randomly.
Pair Corralation between GBS Software and AUST AGRICULTURAL
Assuming the 90 days trading horizon GBS Software AG is expected to generate 2.32 times more return on investment than AUST AGRICULTURAL. However, GBS Software is 2.32 times more volatile than AUST AGRICULTURAL. It trades about 0.02 of its potential returns per unit of risk. AUST AGRICULTURAL is currently generating about 0.01 per unit of risk. If you would invest 276.00 in GBS Software AG on November 3, 2024 and sell it today you would earn a total of 2.00 from holding GBS Software AG or generate 0.72% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
GBS Software AG vs. AUST AGRICULTURAL
Performance |
Timeline |
GBS Software AG |
AUST AGRICULTURAL |
GBS Software and AUST AGRICULTURAL Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with GBS Software and AUST AGRICULTURAL
The main advantage of trading using opposite GBS Software and AUST AGRICULTURAL positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GBS Software position performs unexpectedly, AUST AGRICULTURAL 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 AUST AGRICULTURAL will offset losses from the drop in AUST AGRICULTURAL's long position.GBS Software vs. SIVERS SEMICONDUCTORS AB | GBS Software vs. NorAm Drilling AS | GBS Software vs. Volkswagen AG | GBS Software vs. Darden Restaurants |
AUST AGRICULTURAL vs. Apple Inc | AUST AGRICULTURAL vs. Apple Inc | AUST AGRICULTURAL vs. Apple Inc | AUST AGRICULTURAL vs. Apple Inc |
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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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