Correlation Between Heilongjiang Publishing and Guilin Seamild
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By analyzing existing cross correlation between Heilongjiang Publishing Media and Guilin Seamild Foods, you can compare the effects of market volatilities on Heilongjiang Publishing and Guilin Seamild 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 Heilongjiang Publishing with a short position of Guilin Seamild. Check out your portfolio center. Please also check ongoing floating volatility patterns of Heilongjiang Publishing and Guilin Seamild.
Diversification Opportunities for Heilongjiang Publishing and Guilin Seamild
0.42 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Heilongjiang and Guilin is 0.42. Overlapping area represents the amount of risk that can be diversified away by holding Heilongjiang Publishing Media and Guilin Seamild Foods in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Guilin Seamild Foods and Heilongjiang Publishing 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 Heilongjiang Publishing Media are associated (or correlated) with Guilin Seamild. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Guilin Seamild Foods has no effect on the direction of Heilongjiang Publishing i.e., Heilongjiang Publishing and Guilin Seamild go up and down completely randomly.
Pair Corralation between Heilongjiang Publishing and Guilin Seamild
Assuming the 90 days trading horizon Heilongjiang Publishing is expected to generate 439.0 times less return on investment than Guilin Seamild. In addition to that, Heilongjiang Publishing is 1.22 times more volatile than Guilin Seamild Foods. It trades about 0.0 of its total potential returns per unit of risk. Guilin Seamild Foods is currently generating about 0.12 per unit of volatility. If you would invest 1,286 in Guilin Seamild Foods on October 10, 2024 and sell it today you would earn a total of 279.00 from holding Guilin Seamild Foods or generate 21.7% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Heilongjiang Publishing Media vs. Guilin Seamild Foods
Performance |
Timeline |
Heilongjiang Publishing |
Guilin Seamild Foods |
Heilongjiang Publishing and Guilin Seamild Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Heilongjiang Publishing and Guilin Seamild
The main advantage of trading using opposite Heilongjiang Publishing and Guilin Seamild positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Heilongjiang Publishing position performs unexpectedly, Guilin Seamild 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 Guilin Seamild will offset losses from the drop in Guilin Seamild's long position.The idea behind Heilongjiang Publishing Media and Guilin Seamild Foods pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.
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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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