Correlation Between Ford and FPT Digital
Can any of the company-specific risk be diversified away by investing in both Ford and FPT Digital 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 FPT Digital into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ford Motor and FPT Digital Retail, you can compare the effects of market volatilities on Ford and FPT Digital 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 FPT Digital. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ford and FPT Digital.
Diversification Opportunities for Ford and FPT Digital
-0.49 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Ford and FPT is -0.49. Overlapping area represents the amount of risk that can be diversified away by holding Ford Motor and FPT Digital Retail in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on FPT Digital Retail 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 FPT Digital. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of FPT Digital Retail has no effect on the direction of Ford i.e., Ford and FPT Digital go up and down completely randomly.
Pair Corralation between Ford and FPT Digital
Taking into account the 90-day investment horizon Ford Motor is expected to under-perform the FPT Digital. In addition to that, Ford is 1.08 times more volatile than FPT Digital Retail. It trades about 0.0 of its total potential returns per unit of risk. FPT Digital Retail is currently generating about 0.41 per unit of volatility. If you would invest 18,600,000 in FPT Digital Retail on November 6, 2024 and sell it today you would earn a total of 2,000,000 from holding FPT Digital Retail or generate 10.75% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 84.21% |
| Values | Daily Returns |
Ford Motor vs. FPT Digital Retail
Performance |
| Timeline |
| Ford Motor |
| FPT Digital Retail |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Solid
Ford and FPT Digital Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Ford and FPT Digital
The main advantage of trading using opposite Ford and FPT Digital positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ford position performs unexpectedly, FPT Digital 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 FPT Digital will offset losses from the drop in FPT Digital's long position.The idea behind Ford Motor and FPT Digital Retail 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.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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