Correlation Between Feng Tay and Everest Textile
Can any of the company-specific risk be diversified away by investing in both Feng Tay and Everest Textile 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 Feng Tay and Everest Textile into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Feng Tay Enterprises and Everest Textile Co, you can compare the effects of market volatilities on Feng Tay and Everest Textile 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 Feng Tay with a short position of Everest Textile. Check out your portfolio center. Please also check ongoing floating volatility patterns of Feng Tay and Everest Textile.
Diversification Opportunities for Feng Tay and Everest Textile
0.43 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Feng and Everest is 0.43. Overlapping area represents the amount of risk that can be diversified away by holding Feng Tay Enterprises and Everest Textile Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Everest Textile and Feng Tay 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 Feng Tay Enterprises are associated (or correlated) with Everest Textile. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Everest Textile has no effect on the direction of Feng Tay i.e., Feng Tay and Everest Textile go up and down completely randomly.
Pair Corralation between Feng Tay and Everest Textile
Assuming the 90 days trading horizon Feng Tay Enterprises is expected to under-perform the Everest Textile. In addition to that, Feng Tay is 2.77 times more volatile than Everest Textile Co. It trades about -0.01 of its total potential returns per unit of risk. Everest Textile Co is currently generating about -0.04 per unit of volatility. If you would invest 716.00 in Everest Textile Co on September 17, 2024 and sell it today you would lose (13.00) from holding Everest Textile Co or give up 1.82% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Feng Tay Enterprises vs. Everest Textile Co
Performance |
Timeline |
Feng Tay Enterprises |
Everest Textile |
Feng Tay and Everest Textile Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Feng Tay and Everest Textile
The main advantage of trading using opposite Feng Tay and Everest Textile positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Feng Tay position performs unexpectedly, Everest Textile 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 Everest Textile will offset losses from the drop in Everest Textile's long position.Feng Tay vs. Pou Chen Corp | Feng Tay vs. Eclat Textile Co | Feng Tay vs. Hotai Motor Co | Feng Tay vs. Giant Manufacturing Co |
Everest Textile vs. Feng Tay Enterprises | Everest Textile vs. Ruentex Development Co | Everest Textile vs. WiseChip Semiconductor | Everest Textile vs. Novatek Microelectronics 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 Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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