Correlation Between Ford and NEXON Co
Can any of the company-specific risk be diversified away by investing in both Ford and NEXON Co 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 NEXON Co into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ford Motor and NEXON Co, you can compare the effects of market volatilities on Ford and NEXON Co 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 NEXON Co. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ford and NEXON Co.
Diversification Opportunities for Ford and NEXON Co
Very good diversification
The 3 months correlation between Ford and NEXON is -0.36. Overlapping area represents the amount of risk that can be diversified away by holding Ford Motor and NEXON Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on NEXON Co 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 NEXON Co. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of NEXON Co has no effect on the direction of Ford i.e., Ford and NEXON Co go up and down completely randomly.
Pair Corralation between Ford and NEXON Co
Taking into account the 90-day investment horizon Ford is expected to generate 14.95 times less return on investment than NEXON Co. But when comparing it to its historical volatility, Ford Motor is 2.55 times less risky than NEXON Co. It trades about 0.01 of its potential returns per unit of risk. NEXON Co is currently generating about 0.05 of returns per unit of risk over similar time horizon. If you would invest 919.00 in NEXON Co on August 25, 2024 and sell it today you would earn a total of 421.00 from holding NEXON Co or generate 45.81% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 98.28% |
| Values | Daily Returns |
Ford Motor vs. NEXON Co
Performance |
| Timeline |
| Ford Motor |
| NEXON Co |
Ford and NEXON Co Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Ford and NEXON Co
The main advantage of trading using opposite Ford and NEXON Co positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ford position performs unexpectedly, NEXON Co 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 NEXON Co will offset losses from the drop in NEXON Co's long position.The idea behind Ford Motor and NEXON Co 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.| NEXON Co vs. Darden Restaurants | NEXON Co vs. Selective Insurance Group | NEXON Co vs. Goosehead Insurance | NEXON Co vs. GREENX METALS LTD |
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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