Correlation Between Ford and Aqua Metals
Can any of the company-specific risk be diversified away by investing in both Ford and Aqua Metals at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining Ford and Aqua Metals into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ford Motor and Aqua Metals, you can compare the effects of market volatilities on Ford and Aqua Metals 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 Aqua Metals. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ford and Aqua Metals.
Diversification Opportunities for Ford and Aqua Metals
0.04 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Ford and Aqua is 0.04. Overlapping area represents the amount of risk that can be diversified away by holding Ford Motor and Aqua Metals in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Aqua Metals 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 Aqua Metals. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Aqua Metals has no effect on the direction of Ford i.e., Ford and Aqua Metals go up and down completely randomly.
Pair Corralation between Ford and Aqua Metals
Taking into account the 90-day investment horizon Ford Motor is expected to generate 0.35 times more return on investment than Aqua Metals. However, Ford Motor is 2.86 times less risky than Aqua Metals. It trades about 0.1 of its potential returns per unit of risk. Aqua Metals is currently generating about -0.28 per unit of risk. If you would invest 990.00 in Ford Motor on November 1, 2024 and sell it today you would earn a total of 31.00 from holding Ford Motor or generate 3.13% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 95.0% |
| Values | Daily Returns |
Ford Motor vs. Aqua Metals
Performance |
| Timeline |
| Ford Motor |
| Aqua Metals |
Ford and Aqua Metals Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Ford and Aqua Metals
The main advantage of trading using opposite Ford and Aqua Metals positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ford position performs unexpectedly, Aqua Metals 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 Aqua Metals will offset losses from the drop in Aqua Metals' long position.The idea behind Ford Motor and Aqua Metals 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.| Aqua Metals vs. LanzaTech Global | Aqua Metals vs. Waste Management | Aqua Metals vs. Clean Harbors | Aqua Metals vs. Casella Waste Systems |
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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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