Correlation Between Gome Telecom and Rongcheer Industrial
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By analyzing existing cross correlation between Gome Telecom Equipment and Rongcheer Industrial Technology, you can compare the effects of market volatilities on Gome Telecom and Rongcheer Industrial 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 Gome Telecom with a short position of Rongcheer Industrial. Check out your portfolio center. Please also check ongoing floating volatility patterns of Gome Telecom and Rongcheer Industrial.
Diversification Opportunities for Gome Telecom and Rongcheer Industrial
0.46 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Gome and Rongcheer is 0.46. Overlapping area represents the amount of risk that can be diversified away by holding Gome Telecom Equipment and Rongcheer Industrial Technolog in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Rongcheer Industrial and Gome Telecom 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 Gome Telecom Equipment are associated (or correlated) with Rongcheer Industrial. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Rongcheer Industrial has no effect on the direction of Gome Telecom i.e., Gome Telecom and Rongcheer Industrial go up and down completely randomly.
Pair Corralation between Gome Telecom and Rongcheer Industrial
Assuming the 90 days trading horizon Gome Telecom Equipment is expected to under-perform the Rongcheer Industrial. But the stock apears to be less risky and, when comparing its historical volatility, Gome Telecom Equipment is 1.28 times less risky than Rongcheer Industrial. The stock trades about -0.04 of its potential returns per unit of risk. The Rongcheer Industrial Technology is currently generating about -0.01 of returns per unit of risk over similar time horizon. If you would invest 8,749 in Rongcheer Industrial Technology on September 4, 2024 and sell it today you would lose (3,246) from holding Rongcheer Industrial Technology or give up 37.1% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 99.72% |
| Values | Daily Returns |
Gome Telecom Equipment vs. Rongcheer Industrial Technolog
Performance |
| Timeline |
| Gome Telecom Equipment |
| Rongcheer Industrial |
Gome Telecom and Rongcheer Industrial Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Gome Telecom and Rongcheer Industrial
The main advantage of trading using opposite Gome Telecom and Rongcheer Industrial positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Gome Telecom position performs unexpectedly, Rongcheer Industrial 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 Rongcheer Industrial will offset losses from the drop in Rongcheer Industrial's long position.| Gome Telecom vs. Biwin Storage Technology | Gome Telecom vs. PetroChina Co Ltd | Gome Telecom vs. Industrial and Commercial | Gome Telecom vs. China Construction Bank |
| Rongcheer Industrial vs. Chengdu Kanghua Biological | Rongcheer Industrial vs. Beijing Wantai Biological | Rongcheer Industrial vs. Suzhou Novoprotein Scientific | Rongcheer Industrial vs. Aluminum Corp of |
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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