Correlation Between Zhangjiagang Freetrade and Thinkingdom Media
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By analyzing existing cross correlation between Zhangjiagang Freetrade Science and Thinkingdom Media Group, you can compare the effects of market volatilities on Zhangjiagang Freetrade and Thinkingdom Media 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 Zhangjiagang Freetrade with a short position of Thinkingdom Media. Check out your portfolio center. Please also check ongoing floating volatility patterns of Zhangjiagang Freetrade and Thinkingdom Media.
Diversification Opportunities for Zhangjiagang Freetrade and Thinkingdom Media
0.89 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Zhangjiagang and Thinkingdom is 0.89. Overlapping area represents the amount of risk that can be diversified away by holding Zhangjiagang Freetrade Science and Thinkingdom Media Group in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Thinkingdom Media and Zhangjiagang Freetrade 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 Zhangjiagang Freetrade Science are associated (or correlated) with Thinkingdom Media. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Thinkingdom Media has no effect on the direction of Zhangjiagang Freetrade i.e., Zhangjiagang Freetrade and Thinkingdom Media go up and down completely randomly.
Pair Corralation between Zhangjiagang Freetrade and Thinkingdom Media
Assuming the 90 days trading horizon Zhangjiagang Freetrade is expected to generate 1.34 times less return on investment than Thinkingdom Media. But when comparing it to its historical volatility, Zhangjiagang Freetrade Science is 1.13 times less risky than Thinkingdom Media. It trades about 0.19 of its potential returns per unit of risk. Thinkingdom Media Group is currently generating about 0.23 of returns per unit of risk over similar time horizon. If you would invest 1,550 in Thinkingdom Media Group on September 5, 2024 and sell it today you would earn a total of 750.00 from holding Thinkingdom Media Group or generate 48.39% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Zhangjiagang Freetrade Science vs. Thinkingdom Media Group
Performance |
Timeline |
Zhangjiagang Freetrade |
Thinkingdom Media |
Zhangjiagang Freetrade and Thinkingdom Media Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Zhangjiagang Freetrade and Thinkingdom Media
The main advantage of trading using opposite Zhangjiagang Freetrade and Thinkingdom Media positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Zhangjiagang Freetrade position performs unexpectedly, Thinkingdom Media 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 Thinkingdom Media will offset losses from the drop in Thinkingdom Media's long position.Zhangjiagang Freetrade vs. Industrial and Commercial | Zhangjiagang Freetrade vs. Kweichow Moutai Co | Zhangjiagang Freetrade vs. Agricultural Bank of | Zhangjiagang Freetrade vs. China Mobile Limited |
Thinkingdom Media vs. Ming Yang Smart | Thinkingdom Media vs. 159681 | Thinkingdom Media vs. 159005 | Thinkingdom Media vs. 516220 |
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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