Correlation Between San Fu and China Petrochemical
Can any of the company-specific risk be diversified away by investing in both San Fu and China Petrochemical 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 San Fu and China Petrochemical into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between San Fu Chemical and China Petrochemical Development, you can compare the effects of market volatilities on San Fu and China Petrochemical 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 San Fu with a short position of China Petrochemical. Check out your portfolio center. Please also check ongoing floating volatility patterns of San Fu and China Petrochemical.
Diversification Opportunities for San Fu and China Petrochemical
0.53 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between San and China is 0.53. Overlapping area represents the amount of risk that can be diversified away by holding San Fu Chemical and China Petrochemical Developmen in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on China Petrochemical and San Fu 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 San Fu Chemical are associated (or correlated) with China Petrochemical. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of China Petrochemical has no effect on the direction of San Fu i.e., San Fu and China Petrochemical go up and down completely randomly.
Pair Corralation between San Fu and China Petrochemical
Assuming the 90 days trading horizon San Fu Chemical is expected to generate 1.4 times more return on investment than China Petrochemical. However, San Fu is 1.4 times more volatile than China Petrochemical Development. It trades about -0.01 of its potential returns per unit of risk. China Petrochemical Development is currently generating about -0.14 per unit of risk. If you would invest 13,800 in San Fu Chemical on September 22, 2024 and sell it today you would lose (850.00) from holding San Fu Chemical or give up 6.16% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
San Fu Chemical vs. China Petrochemical Developmen
Performance |
Timeline |
San Fu Chemical |
China Petrochemical |
San Fu and China Petrochemical Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with San Fu and China Petrochemical
The main advantage of trading using opposite San Fu and China Petrochemical positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if San Fu position performs unexpectedly, China Petrochemical 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 China Petrochemical will offset losses from the drop in China Petrochemical's long position.San Fu vs. Nan Ya Plastics | San Fu vs. China Petrochemical Development | San Fu vs. Eternal Materials Co | San Fu vs. TSRC Corp |
China Petrochemical vs. Taiwan Styrene Monomer | China Petrochemical vs. China Steel Corp | China Petrochemical vs. China Man Made Fiber |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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