Correlation Between China Petroleum and Suzhou Weizhixiang
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By analyzing existing cross correlation between China Petroleum Chemical and Suzhou Weizhixiang Food, you can compare the effects of market volatilities on China Petroleum and Suzhou Weizhixiang 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 China Petroleum with a short position of Suzhou Weizhixiang. Check out your portfolio center. Please also check ongoing floating volatility patterns of China Petroleum and Suzhou Weizhixiang.
Diversification Opportunities for China Petroleum and Suzhou Weizhixiang
-0.2 | Correlation Coefficient |
Good diversification
The 3 months correlation between China and Suzhou is -0.2. Overlapping area represents the amount of risk that can be diversified away by holding China Petroleum Chemical and Suzhou Weizhixiang Food in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Suzhou Weizhixiang Food and China Petroleum 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 China Petroleum Chemical are associated (or correlated) with Suzhou Weizhixiang. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Suzhou Weizhixiang Food has no effect on the direction of China Petroleum i.e., China Petroleum and Suzhou Weizhixiang go up and down completely randomly.
Pair Corralation between China Petroleum and Suzhou Weizhixiang
Assuming the 90 days trading horizon China Petroleum is expected to generate 10.83 times less return on investment than Suzhou Weizhixiang. But when comparing it to its historical volatility, China Petroleum Chemical is 2.29 times less risky than Suzhou Weizhixiang. It trades about 0.05 of its potential returns per unit of risk. Suzhou Weizhixiang Food is currently generating about 0.24 of returns per unit of risk over similar time horizon. If you would invest 1,742 in Suzhou Weizhixiang Food on September 12, 2024 and sell it today you would earn a total of 1,109 from holding Suzhou Weizhixiang Food or generate 63.66% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
China Petroleum Chemical vs. Suzhou Weizhixiang Food
Performance |
Timeline |
China Petroleum Chemical |
Suzhou Weizhixiang Food |
China Petroleum and Suzhou Weizhixiang Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with China Petroleum and Suzhou Weizhixiang
The main advantage of trading using opposite China Petroleum and Suzhou Weizhixiang positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if China Petroleum position performs unexpectedly, Suzhou Weizhixiang 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 Suzhou Weizhixiang will offset losses from the drop in Suzhou Weizhixiang's long position.China Petroleum vs. Western Superconducting Tech | China Petroleum vs. Holitech Technology Co | China Petroleum vs. Ping An Insurance | China Petroleum vs. Chengdu Xinzhu RoadBridge |
Suzhou Weizhixiang vs. China Petroleum Chemical | Suzhou Weizhixiang vs. PetroChina Co Ltd | Suzhou Weizhixiang vs. China State Construction | Suzhou Weizhixiang vs. China Railway Group |
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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