Correlation Between Ford and PPB Group
Can any of the company-specific risk be diversified away by investing in both Ford and PPB Group 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 PPB Group into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ford Motor and PPB Group Bhd, you can compare the effects of market volatilities on Ford and PPB Group 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 PPB Group. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ford and PPB Group.
Diversification Opportunities for Ford and PPB Group
Weak diversification
The 3 months correlation between Ford and PPB is 0.37. Overlapping area represents the amount of risk that can be diversified away by holding Ford Motor and PPB Group Bhd in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PPB Group Bhd 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 PPB Group. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PPB Group Bhd has no effect on the direction of Ford i.e., Ford and PPB Group go up and down completely randomly.
Pair Corralation between Ford and PPB Group
Taking into account the 90-day investment horizon Ford Motor is expected to under-perform the PPB Group. In addition to that, Ford is 1.89 times more volatile than PPB Group Bhd. It trades about -0.05 of its total potential returns per unit of risk. PPB Group Bhd is currently generating about -0.09 per unit of volatility. If you would invest 1,430 in PPB Group Bhd on September 27, 2024 and sell it today you would lose (212.00) from holding PPB Group Bhd or give up 14.83% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Ford Motor vs. PPB Group Bhd
Performance |
Timeline |
Ford Motor |
PPB Group Bhd |
Ford and PPB Group Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Ford and PPB Group
The main advantage of trading using opposite Ford and PPB Group positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ford position performs unexpectedly, PPB Group 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 PPB Group will offset losses from the drop in PPB Group's long position.The idea behind Ford Motor and PPB Group Bhd 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.PPB Group vs. Nestle Bhd | PPB Group vs. IOI Bhd | PPB Group vs. FGV Holdings Bhd | PPB Group vs. British American Tobacco |
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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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