Correlation Between Charoen Pokphand and Motorcar Parts
Can any of the company-specific risk be diversified away by investing in both Charoen Pokphand and Motorcar Parts 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 Charoen Pokphand and Motorcar Parts into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Charoen Pokphand Foods and Motorcar Parts of, you can compare the effects of market volatilities on Charoen Pokphand and Motorcar Parts 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 Charoen Pokphand with a short position of Motorcar Parts. Check out your portfolio center. Please also check ongoing floating volatility patterns of Charoen Pokphand and Motorcar Parts.
Diversification Opportunities for Charoen Pokphand and Motorcar Parts
-0.23 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Charoen and Motorcar is -0.23. Overlapping area represents the amount of risk that can be diversified away by holding Charoen Pokphand Foods and Motorcar Parts of in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Motorcar Parts and Charoen Pokphand 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 Charoen Pokphand Foods are associated (or correlated) with Motorcar Parts. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Motorcar Parts has no effect on the direction of Charoen Pokphand i.e., Charoen Pokphand and Motorcar Parts go up and down completely randomly.
Pair Corralation between Charoen Pokphand and Motorcar Parts
Assuming the 90 days trading horizon Charoen Pokphand Foods is expected to generate 0.67 times more return on investment than Motorcar Parts. However, Charoen Pokphand Foods is 1.49 times less risky than Motorcar Parts. It trades about 0.02 of its potential returns per unit of risk. Motorcar Parts of is currently generating about 0.01 per unit of risk. If you would invest 64.00 in Charoen Pokphand Foods on September 14, 2024 and sell it today you would earn a total of 2.00 from holding Charoen Pokphand Foods or generate 3.13% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Charoen Pokphand Foods vs. Motorcar Parts of
Performance |
| Timeline |
| Charoen Pokphand Foods |
| Motorcar Parts |
Charoen Pokphand and Motorcar Parts Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Charoen Pokphand and Motorcar Parts
The main advantage of trading using opposite Charoen Pokphand and Motorcar Parts positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Charoen Pokphand position performs unexpectedly, Motorcar Parts 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 Motorcar Parts will offset losses from the drop in Motorcar Parts' long position.| Charoen Pokphand vs. Alaska Air Group | Charoen Pokphand vs. Westinghouse Air Brake | Charoen Pokphand vs. Wizz Air Holdings | Charoen Pokphand vs. NORWEGIAN AIR SHUT |
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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