Correlation Between SGSG Sciencetechnolog and Shenzhen Fortune
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By analyzing existing cross correlation between SGSG Sciencetechnology Co and Shenzhen Fortune Trend, you can compare the effects of market volatilities on SGSG Sciencetechnolog and Shenzhen Fortune 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 SGSG Sciencetechnolog with a short position of Shenzhen Fortune. Check out your portfolio center. Please also check ongoing floating volatility patterns of SGSG Sciencetechnolog and Shenzhen Fortune.
Diversification Opportunities for SGSG Sciencetechnolog and Shenzhen Fortune
0.66 | Correlation Coefficient |
Poor diversification
The 3 months correlation between SGSG and Shenzhen is 0.66. Overlapping area represents the amount of risk that can be diversified away by holding SGSG Sciencetechnology Co and Shenzhen Fortune Trend in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Shenzhen Fortune Trend and SGSG Sciencetechnolog 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 SGSG Sciencetechnology Co are associated (or correlated) with Shenzhen Fortune. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Shenzhen Fortune Trend has no effect on the direction of SGSG Sciencetechnolog i.e., SGSG Sciencetechnolog and Shenzhen Fortune go up and down completely randomly.
Pair Corralation between SGSG Sciencetechnolog and Shenzhen Fortune
Assuming the 90 days trading horizon SGSG Sciencetechnology Co is expected to generate 2.11 times more return on investment than Shenzhen Fortune. However, SGSG Sciencetechnolog is 2.11 times more volatile than Shenzhen Fortune Trend. It trades about 0.21 of its potential returns per unit of risk. Shenzhen Fortune Trend is currently generating about -0.28 per unit of risk. If you would invest 4,377 in SGSG Sciencetechnology Co on October 6, 2024 and sell it today you would earn a total of 1,462 from holding SGSG Sciencetechnology Co or generate 33.4% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
SGSG Sciencetechnology Co vs. Shenzhen Fortune Trend
Performance |
Timeline |
SGSG Sciencetechnology |
Shenzhen Fortune Trend |
SGSG Sciencetechnolog and Shenzhen Fortune Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with SGSG Sciencetechnolog and Shenzhen Fortune
The main advantage of trading using opposite SGSG Sciencetechnolog and Shenzhen Fortune positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SGSG Sciencetechnolog position performs unexpectedly, Shenzhen Fortune 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 Shenzhen Fortune will offset losses from the drop in Shenzhen Fortune's long position.The idea behind SGSG Sciencetechnology Co and Shenzhen Fortune Trend 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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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