Correlation Between Transport and FPT Digital
Can any of the company-specific risk be diversified away by investing in both Transport and FPT Digital 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 Transport and FPT Digital into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Transport and Industry and FPT Digital Retail, you can compare the effects of market volatilities on Transport and FPT Digital 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 Transport with a short position of FPT Digital. Check out your portfolio center. Please also check ongoing floating volatility patterns of Transport and FPT Digital.
Diversification Opportunities for Transport and FPT Digital
0.33 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Transport and FPT is 0.33. Overlapping area represents the amount of risk that can be diversified away by holding Transport and Industry and FPT Digital Retail in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on FPT Digital Retail and Transport 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 Transport and Industry are associated (or correlated) with FPT Digital. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of FPT Digital Retail has no effect on the direction of Transport i.e., Transport and FPT Digital go up and down completely randomly.
Pair Corralation between Transport and FPT Digital
Assuming the 90 days trading horizon Transport and Industry is expected to under-perform the FPT Digital. In addition to that, Transport is 2.02 times more volatile than FPT Digital Retail. It trades about -0.2 of its total potential returns per unit of risk. FPT Digital Retail is currently generating about 0.05 per unit of volatility. If you would invest 17,700,000 in FPT Digital Retail on September 16, 2024 and sell it today you would earn a total of 490,000 from holding FPT Digital Retail or generate 2.77% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Transport and Industry vs. FPT Digital Retail
Performance |
Timeline |
Transport and Industry |
FPT Digital Retail |
Transport and FPT Digital Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Transport and FPT Digital
The main advantage of trading using opposite Transport and FPT Digital positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Transport position performs unexpectedly, FPT Digital 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 FPT Digital will offset losses from the drop in FPT Digital's long position.Transport vs. Saigon Telecommunication Technologies | Transport vs. VTC Telecommunications JSC | Transport vs. Petrolimex Insurance Corp | Transport vs. PVI Reinsurance Corp |
FPT Digital vs. Fecon Mining JSC | FPT Digital vs. Innovative Technology Development | FPT Digital vs. Saigon Viendong Technology | FPT Digital vs. Transport and Industry |
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 Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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