Correlation Between Reward Wool and Feng Tay
Can any of the company-specific risk be diversified away by investing in both Reward Wool and Feng Tay 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 Reward Wool and Feng Tay into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Reward Wool Industry and Feng Tay Enterprises, you can compare the effects of market volatilities on Reward Wool and Feng Tay 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 Reward Wool with a short position of Feng Tay. Check out your portfolio center. Please also check ongoing floating volatility patterns of Reward Wool and Feng Tay.
Diversification Opportunities for Reward Wool and Feng Tay
0.74 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Reward and Feng is 0.74. Overlapping area represents the amount of risk that can be diversified away by holding Reward Wool Industry and Feng Tay Enterprises in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Feng Tay Enterprises and Reward Wool 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 Reward Wool Industry are associated (or correlated) with Feng Tay. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Feng Tay Enterprises has no effect on the direction of Reward Wool i.e., Reward Wool and Feng Tay go up and down completely randomly.
Pair Corralation between Reward Wool and Feng Tay
Assuming the 90 days trading horizon Reward Wool Industry is expected to under-perform the Feng Tay. But the stock apears to be less risky and, when comparing its historical volatility, Reward Wool Industry is 2.02 times less risky than Feng Tay. The stock trades about -0.27 of its potential returns per unit of risk. The Feng Tay Enterprises is currently generating about 0.0 of returns per unit of risk over similar time horizon. If you would invest 14,050 in Feng Tay Enterprises on September 13, 2024 and sell it today you would lose (250.00) from holding Feng Tay Enterprises or give up 1.78% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Reward Wool Industry vs. Feng Tay Enterprises
Performance |
Timeline |
Reward Wool Industry |
Feng Tay Enterprises |
Reward Wool and Feng Tay Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Reward Wool and Feng Tay
The main advantage of trading using opposite Reward Wool and Feng Tay positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Reward Wool position performs unexpectedly, Feng Tay 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 Feng Tay will offset losses from the drop in Feng Tay's long position.Reward Wool vs. Feng Tay Enterprises | Reward Wool vs. Ruentex Development Co | Reward Wool vs. WiseChip Semiconductor | Reward Wool vs. Novatek Microelectronics Corp |
Feng Tay vs. Pou Chen Corp | Feng Tay vs. Eclat Textile Co | Feng Tay vs. Hotai Motor Co | Feng Tay vs. Giant Manufacturing Co |
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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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