Correlation Between Industrial and Guangdong Advertising
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By analyzing existing cross correlation between Industrial and Commercial and Guangdong Advertising Co, you can compare the effects of market volatilities on Industrial and Guangdong Advertising 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 Industrial with a short position of Guangdong Advertising. Check out your portfolio center. Please also check ongoing floating volatility patterns of Industrial and Guangdong Advertising.
Diversification Opportunities for Industrial and Guangdong Advertising
0.16 | Correlation Coefficient |
Average diversification
The 3 months correlation between Industrial and Guangdong is 0.16. Overlapping area represents the amount of risk that can be diversified away by holding Industrial and Commercial and Guangdong Advertising Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Guangdong Advertising and Industrial 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 Industrial and Commercial are associated (or correlated) with Guangdong Advertising. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Guangdong Advertising has no effect on the direction of Industrial i.e., Industrial and Guangdong Advertising go up and down completely randomly.
Pair Corralation between Industrial and Guangdong Advertising
Assuming the 90 days trading horizon Industrial is expected to generate 23.13 times less return on investment than Guangdong Advertising. But when comparing it to its historical volatility, Industrial and Commercial is 6.5 times less risky than Guangdong Advertising. It trades about 0.07 of its potential returns per unit of risk. Guangdong Advertising Co is currently generating about 0.26 of returns per unit of risk over similar time horizon. If you would invest 620.00 in Guangdong Advertising Co on August 29, 2024 and sell it today you would earn a total of 234.00 from holding Guangdong Advertising Co or generate 37.74% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Industrial and Commercial vs. Guangdong Advertising Co
Performance |
| Timeline |
| Industrial and Commercial |
| Guangdong Advertising |
Industrial and Guangdong Advertising Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Industrial and Guangdong Advertising
The main advantage of trading using opposite Industrial and Guangdong Advertising positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Industrial position performs unexpectedly, Guangdong Advertising 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 Guangdong Advertising will offset losses from the drop in Guangdong Advertising's long position.| Industrial vs. Sinofibers Technology Co | Industrial vs. Saurer Intelligent Technology | Industrial vs. Sinocelltech Group | Industrial vs. Dhc Software Co |
| Guangdong Advertising vs. Industrial and Commercial | Guangdong Advertising vs. Agricultural Bank of | Guangdong Advertising vs. China Construction Bank | Guangdong Advertising vs. Bank of China |
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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