Correlation Between Olympic Circuit and Shanghai Suochen
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By analyzing existing cross correlation between Olympic Circuit Technology and Shanghai Suochen Information, you can compare the effects of market volatilities on Olympic Circuit and Shanghai Suochen 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 Olympic Circuit with a short position of Shanghai Suochen. Check out your portfolio center. Please also check ongoing floating volatility patterns of Olympic Circuit and Shanghai Suochen.
Diversification Opportunities for Olympic Circuit and Shanghai Suochen
0.92 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Olympic and Shanghai is 0.92. Overlapping area represents the amount of risk that can be diversified away by holding Olympic Circuit Technology and Shanghai Suochen Information in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Shanghai Suochen Inf and Olympic Circuit 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 Olympic Circuit Technology are associated (or correlated) with Shanghai Suochen. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Shanghai Suochen Inf has no effect on the direction of Olympic Circuit i.e., Olympic Circuit and Shanghai Suochen go up and down completely randomly.
Pair Corralation between Olympic Circuit and Shanghai Suochen
Assuming the 90 days trading horizon Olympic Circuit is expected to generate 1.08 times less return on investment than Shanghai Suochen. But when comparing it to its historical volatility, Olympic Circuit Technology is 1.16 times less risky than Shanghai Suochen. It trades about 0.19 of its potential returns per unit of risk. Shanghai Suochen Information is currently generating about 0.18 of returns per unit of risk over similar time horizon. If you would invest 4,031 in Shanghai Suochen Information on September 17, 2024 and sell it today you would earn a total of 2,689 from holding Shanghai Suochen Information or generate 66.71% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Olympic Circuit Technology vs. Shanghai Suochen Information
Performance |
Timeline |
Olympic Circuit Tech |
Shanghai Suochen Inf |
Olympic Circuit and Shanghai Suochen Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Olympic Circuit and Shanghai Suochen
The main advantage of trading using opposite Olympic Circuit and Shanghai Suochen positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Olympic Circuit position performs unexpectedly, Shanghai Suochen 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 Shanghai Suochen will offset losses from the drop in Shanghai Suochen's long position.Olympic Circuit vs. Beijing Kaiwen Education | Olympic Circuit vs. Chinese Universe Publishing | Olympic Circuit vs. China Publishing Media | Olympic Circuit vs. Yuan Longping High tech |
Shanghai Suochen vs. Hubei Forbon Technology | Shanghai Suochen vs. Olympic Circuit Technology | Shanghai Suochen vs. Guangzhou KingTeller Technology | Shanghai Suochen vs. Zijin Mining Group |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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