Correlation Between Ford and Dong Ah
Can any of the company-specific risk be diversified away by investing in both Ford and Dong Ah 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 Dong Ah into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ford Motor and Dong Ah Tire, you can compare the effects of market volatilities on Ford and Dong Ah 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 Dong Ah. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ford and Dong Ah.
Diversification Opportunities for Ford and Dong Ah
Very good diversification
The 3 months correlation between Ford and Dong is -0.37. Overlapping area represents the amount of risk that can be diversified away by holding Ford Motor and Dong Ah Tire in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dong Ah Tire 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 Dong Ah. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dong Ah Tire has no effect on the direction of Ford i.e., Ford and Dong Ah go up and down completely randomly.
Pair Corralation between Ford and Dong Ah
Taking into account the 90-day investment horizon Ford Motor is expected to under-perform the Dong Ah. But the stock apears to be less risky and, when comparing its historical volatility, Ford Motor is 1.64 times less risky than Dong Ah. The stock trades about -0.32 of its potential returns per unit of risk. The Dong Ah Tire is currently generating about 0.04 of returns per unit of risk over similar time horizon. If you would invest 1,830,000 in Dong Ah Tire on September 27, 2024 and sell it today you would earn a total of 30,000 from holding Dong Ah Tire or generate 1.64% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 95.65% |
Values | Daily Returns |
Ford Motor vs. Dong Ah Tire
Performance |
Timeline |
Ford Motor |
Dong Ah Tire |
Ford and Dong Ah Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Ford and Dong Ah
The main advantage of trading using opposite Ford and Dong Ah positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ford position performs unexpectedly, Dong Ah 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 Dong Ah will offset losses from the drop in Dong Ah's long position.The idea behind Ford Motor and Dong Ah Tire 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.Dong Ah vs. Samsung Electronics Co | Dong Ah vs. Samsung Electronics Co | Dong Ah vs. LG Energy Solution | Dong Ah vs. SK Hynix |
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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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