Correlation Between Yuanta SP and Yuanta Daily
Can any of the company-specific risk be diversified away by investing in both Yuanta SP and Yuanta Daily 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 Yuanta SP and Yuanta Daily into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Yuanta SP GSCI and Yuanta Daily Taiwan, you can compare the effects of market volatilities on Yuanta SP and Yuanta Daily 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 Yuanta SP with a short position of Yuanta Daily. Check out your portfolio center. Please also check ongoing floating volatility patterns of Yuanta SP and Yuanta Daily.
Diversification Opportunities for Yuanta SP and Yuanta Daily
0.65 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Yuanta and Yuanta is 0.65. Overlapping area represents the amount of risk that can be diversified away by holding Yuanta SP GSCI and Yuanta Daily Taiwan in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Yuanta Daily Taiwan and Yuanta SP 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 Yuanta SP GSCI are associated (or correlated) with Yuanta Daily. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Yuanta Daily Taiwan has no effect on the direction of Yuanta SP i.e., Yuanta SP and Yuanta Daily go up and down completely randomly.
Pair Corralation between Yuanta SP and Yuanta Daily
Assuming the 90 days trading horizon Yuanta SP is expected to generate 2.71 times less return on investment than Yuanta Daily. But when comparing it to its historical volatility, Yuanta SP GSCI is 2.06 times less risky than Yuanta Daily. It trades about 0.06 of its potential returns per unit of risk. Yuanta Daily Taiwan is currently generating about 0.08 of returns per unit of risk over similar time horizon. If you would invest 21,960 in Yuanta Daily Taiwan on September 14, 2024 and sell it today you would earn a total of 2,180 from holding Yuanta Daily Taiwan or generate 9.93% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Yuanta SP GSCI vs. Yuanta Daily Taiwan
Performance |
Timeline |
Yuanta SP GSCI |
Yuanta Daily Taiwan |
Yuanta SP and Yuanta Daily Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Yuanta SP and Yuanta Daily
The main advantage of trading using opposite Yuanta SP and Yuanta Daily positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Yuanta SP position performs unexpectedly, Yuanta Daily 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 Yuanta Daily will offset losses from the drop in Yuanta Daily's long position.Yuanta SP vs. Yuanta Daily SP | Yuanta SP vs. Yuanta Securities Investment | Yuanta SP vs. Yuanta Global NexGen | Yuanta SP vs. Yuanta SP GSCI |
Yuanta Daily vs. Yuanta Daily SP | Yuanta Daily vs. Yuanta Securities Investment | Yuanta Daily vs. Yuanta SP GSCI | Yuanta Daily vs. Yuanta Global NexGen |
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 Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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