Correlation Between Southern PublishingMedia and Shanxi Lanhua
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By analyzing existing cross correlation between Southern PublishingMedia Co and Shanxi Lanhua Sci Tech, you can compare the effects of market volatilities on Southern PublishingMedia and Shanxi Lanhua 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 Southern PublishingMedia with a short position of Shanxi Lanhua. Check out your portfolio center. Please also check ongoing floating volatility patterns of Southern PublishingMedia and Shanxi Lanhua.
Diversification Opportunities for Southern PublishingMedia and Shanxi Lanhua
0.1 | Correlation Coefficient |
Average diversification
The 3 months correlation between Southern and Shanxi is 0.1. Overlapping area represents the amount of risk that can be diversified away by holding Southern PublishingMedia Co and Shanxi Lanhua Sci Tech in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Shanxi Lanhua Sci and Southern PublishingMedia 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 Southern PublishingMedia Co are associated (or correlated) with Shanxi Lanhua. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Shanxi Lanhua Sci has no effect on the direction of Southern PublishingMedia i.e., Southern PublishingMedia and Shanxi Lanhua go up and down completely randomly.
Pair Corralation between Southern PublishingMedia and Shanxi Lanhua
Assuming the 90 days trading horizon Southern PublishingMedia Co is expected to generate 1.93 times more return on investment than Shanxi Lanhua. However, Southern PublishingMedia is 1.93 times more volatile than Shanxi Lanhua Sci Tech. It trades about 0.05 of its potential returns per unit of risk. Shanxi Lanhua Sci Tech is currently generating about -0.01 per unit of risk. If you would invest 840.00 in Southern PublishingMedia Co on November 6, 2024 and sell it today you would earn a total of 772.00 from holding Southern PublishingMedia Co or generate 91.9% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Southern PublishingMedia Co vs. Shanxi Lanhua Sci Tech
Performance |
| Timeline |
| Southern PublishingMedia |
| Shanxi Lanhua Sci |
Southern PublishingMedia and Shanxi Lanhua Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Southern PublishingMedia and Shanxi Lanhua
The main advantage of trading using opposite Southern PublishingMedia and Shanxi Lanhua positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Southern PublishingMedia position performs unexpectedly, Shanxi Lanhua 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 Shanxi Lanhua will offset losses from the drop in Shanxi Lanhua's long position.The idea behind Southern PublishingMedia Co and Shanxi Lanhua Sci Tech 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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