Correlation Between Ford and Leaguer Shenzhen
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By analyzing existing cross correlation between Ford Motor and Leaguer Shenzhen MicroElectronics, you can compare the effects of market volatilities on Ford and Leaguer Shenzhen 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 Ford with a short position of Leaguer Shenzhen. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ford and Leaguer Shenzhen.
Diversification Opportunities for Ford and Leaguer Shenzhen
0.02 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Ford and Leaguer is 0.02. Overlapping area represents the amount of risk that can be diversified away by holding Ford Motor and Leaguer Shenzhen MicroElectron in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Leaguer Shenzhen Mic and Ford 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 Ford Motor are associated (or correlated) with Leaguer Shenzhen. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Leaguer Shenzhen Mic has no effect on the direction of Ford i.e., Ford and Leaguer Shenzhen go up and down completely randomly.
Pair Corralation between Ford and Leaguer Shenzhen
Taking into account the 90-day investment horizon Ford is expected to generate 1.0 times less return on investment than Leaguer Shenzhen. But when comparing it to its historical volatility, Ford Motor is 1.32 times less risky than Leaguer Shenzhen. It trades about 0.02 of its potential returns per unit of risk. Leaguer Shenzhen MicroElectronics is currently generating about 0.02 of returns per unit of risk over similar time horizon. If you would invest 2,939 in Leaguer Shenzhen MicroElectronics on December 29, 2024 and sell it today you would earn a total of 18.00 from holding Leaguer Shenzhen MicroElectronics or generate 0.61% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 95.08% |
Values | Daily Returns |
Ford Motor vs. Leaguer Shenzhen MicroElectron
Performance |
Timeline |
Ford Motor |
Leaguer Shenzhen Mic |
Ford and Leaguer Shenzhen Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Ford and Leaguer Shenzhen
The main advantage of trading using opposite Ford and Leaguer Shenzhen positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ford position performs unexpectedly, Leaguer Shenzhen 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 Leaguer Shenzhen will offset losses from the drop in Leaguer Shenzhen's long position.The idea behind Ford Motor and Leaguer Shenzhen MicroElectronics 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.Leaguer Shenzhen vs. Dingli Communications Corp | Leaguer Shenzhen vs. Aba Chemicals Corp | Leaguer Shenzhen vs. Shenzhen Noposion Agrochemicals | Leaguer Shenzhen vs. Do Fluoride Chemicals Co |
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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