Correlation Between Oracle and Sino AG
Can any of the company-specific risk be diversified away by investing in both Oracle and Sino AG 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 Oracle and Sino AG into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Oracle and Sino AG, you can compare the effects of market volatilities on Oracle and Sino AG 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 Oracle with a short position of Sino AG. Check out your portfolio center. Please also check ongoing floating volatility patterns of Oracle and Sino AG.
Diversification Opportunities for Oracle and Sino AG
Very weak diversification
The 3 months correlation between Oracle and Sino is 0.51. Overlapping area represents the amount of risk that can be diversified away by holding Oracle and Sino AG in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Sino AG and Oracle 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 Oracle are associated (or correlated) with Sino AG. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Sino AG has no effect on the direction of Oracle i.e., Oracle and Sino AG go up and down completely randomly.
Pair Corralation between Oracle and Sino AG
Given the investment horizon of 90 days Oracle is expected to generate 1.2 times less return on investment than Sino AG. But when comparing it to its historical volatility, Oracle is 1.54 times less risky than Sino AG. It trades about 0.16 of its potential returns per unit of risk. Sino AG is currently generating about 0.12 of returns per unit of risk over similar time horizon. If you would invest 3,760 in Sino AG on September 3, 2024 and sell it today you would earn a total of 2,590 from holding Sino AG or generate 68.88% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 96.69% |
| Values | Daily Returns |
Oracle vs. Sino AG
Performance |
| Timeline |
| Oracle |
| Sino AG |
Oracle and Sino AG Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Oracle and Sino AG
The main advantage of trading using opposite Oracle and Sino AG positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Oracle position performs unexpectedly, Sino AG 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 Sino AG will offset losses from the drop in Sino AG's long position.| Oracle vs. Palo Alto Networks | Oracle vs. Crowdstrike Holdings | Oracle vs. Microsoft | Oracle vs. Block Inc |
The effect of pair diversification on risk is to reduce it, but we should note this doesn't apply to all risk types. When we trade pairs against Sino AG as a counterpart, there is always some inherent risk that will never be diversified away no matter what. This volatility limits the effect of tactical diversification using pair trading. Sino AG's systematic risk is the inherent uncertainty of the entire market, and therefore cannot be mitigated even by pair-trading it against the equity that is not highly correlated to it. On the other hand, Sino AG's unsystematic risk describes the types of risk that we can protect against, at least to some degree, by selecting a matching pair that is not perfectly correlated to Sino AG.
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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