Correlation Between Suzhou Novoprotein and Fujian Longzhou
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By analyzing existing cross correlation between Suzhou Novoprotein Scientific and Fujian Longzhou Transportation, you can compare the effects of market volatilities on Suzhou Novoprotein and Fujian Longzhou 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 Suzhou Novoprotein with a short position of Fujian Longzhou. Check out your portfolio center. Please also check ongoing floating volatility patterns of Suzhou Novoprotein and Fujian Longzhou.
Diversification Opportunities for Suzhou Novoprotein and Fujian Longzhou
0.45 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Suzhou and Fujian is 0.45. Overlapping area represents the amount of risk that can be diversified away by holding Suzhou Novoprotein Scientific and Fujian Longzhou Transportation in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Fujian Longzhou Tran and Suzhou Novoprotein 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 Suzhou Novoprotein Scientific are associated (or correlated) with Fujian Longzhou. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Fujian Longzhou Tran has no effect on the direction of Suzhou Novoprotein i.e., Suzhou Novoprotein and Fujian Longzhou go up and down completely randomly.
Pair Corralation between Suzhou Novoprotein and Fujian Longzhou
Assuming the 90 days trading horizon Suzhou Novoprotein is expected to generate 2.0 times less return on investment than Fujian Longzhou. But when comparing it to its historical volatility, Suzhou Novoprotein Scientific is 1.3 times less risky than Fujian Longzhou. It trades about 0.07 of its potential returns per unit of risk. Fujian Longzhou Transportation is currently generating about 0.11 of returns per unit of risk over similar time horizon. If you would invest 365.00 in Fujian Longzhou Transportation on September 24, 2024 and sell it today you would earn a total of 88.00 from holding Fujian Longzhou Transportation or generate 24.11% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 98.36% |
Values | Daily Returns |
Suzhou Novoprotein Scientific vs. Fujian Longzhou Transportation
Performance |
Timeline |
Suzhou Novoprotein |
Fujian Longzhou Tran |
Suzhou Novoprotein and Fujian Longzhou Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Suzhou Novoprotein and Fujian Longzhou
The main advantage of trading using opposite Suzhou Novoprotein and Fujian Longzhou positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Suzhou Novoprotein position performs unexpectedly, Fujian Longzhou 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 Fujian Longzhou will offset losses from the drop in Fujian Longzhou's long position.Suzhou Novoprotein vs. Industrial and Commercial | Suzhou Novoprotein vs. Agricultural Bank of | Suzhou Novoprotein vs. China Construction Bank | Suzhou Novoprotein vs. Bank of China |
Fujian Longzhou vs. Xiamen Bank Co | Fujian Longzhou vs. Northking Information Technology | Fujian Longzhou vs. Niutech Environment Technology | Fujian Longzhou vs. Western Superconducting Tech |
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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