Correlation Between Ford and Hong Tai
Can any of the company-specific risk be diversified away by investing in both Ford and Hong Tai 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 Hong Tai into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ford Motor and Hong Tai Electric, you can compare the effects of market volatilities on Ford and Hong Tai 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 Hong Tai. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ford and Hong Tai.
Diversification Opportunities for Ford and Hong Tai
Significant diversification
The 3 months correlation between Ford and Hong is 0.01. Overlapping area represents the amount of risk that can be diversified away by holding Ford Motor and Hong Tai Electric in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hong Tai Electric 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 Hong Tai. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hong Tai Electric has no effect on the direction of Ford i.e., Ford and Hong Tai go up and down completely randomly.
Pair Corralation between Ford and Hong Tai
Taking into account the 90-day investment horizon Ford Motor is expected to under-perform the Hong Tai. In addition to that, Ford is 1.3 times more volatile than Hong Tai Electric. It trades about -0.01 of its total potential returns per unit of risk. Hong Tai Electric is currently generating about 0.04 per unit of volatility. If you would invest 3,345 in Hong Tai Electric on September 16, 2024 and sell it today you would earn a total of 100.00 from holding Hong Tai Electric or generate 2.99% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 98.46% |
Values | Daily Returns |
Ford Motor vs. Hong Tai Electric
Performance |
Timeline |
Ford Motor |
Hong Tai Electric |
Ford and Hong Tai Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Ford and Hong Tai
The main advantage of trading using opposite Ford and Hong Tai positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ford position performs unexpectedly, Hong Tai 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 Hong Tai will offset losses from the drop in Hong Tai's long position.The idea behind Ford Motor and Hong Tai Electric 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.Hong Tai vs. Ta Ya Electric | Hong Tai vs. Hua Eng Wire | Hong Tai vs. Walsin Lihwa Corp | Hong Tai vs. Sampo Corp |
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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