Correlation Between Shan Loong and Wistron NeWeb
Can any of the company-specific risk be diversified away by investing in both Shan Loong and Wistron NeWeb 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 Shan Loong and Wistron NeWeb into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Shan Loong Transportation Co and Wistron NeWeb Corp, you can compare the effects of market volatilities on Shan Loong and Wistron NeWeb 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 Shan Loong with a short position of Wistron NeWeb. Check out your portfolio center. Please also check ongoing floating volatility patterns of Shan Loong and Wistron NeWeb.
Diversification Opportunities for Shan Loong and Wistron NeWeb
-0.24 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Shan and Wistron is -0.24. Overlapping area represents the amount of risk that can be diversified away by holding Shan Loong Transportation Co and Wistron NeWeb Corp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Wistron NeWeb Corp and Shan Loong 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 Shan Loong Transportation Co are associated (or correlated) with Wistron NeWeb. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Wistron NeWeb Corp has no effect on the direction of Shan Loong i.e., Shan Loong and Wistron NeWeb go up and down completely randomly.
Pair Corralation between Shan Loong and Wistron NeWeb
Assuming the 90 days trading horizon Shan Loong Transportation Co is expected to under-perform the Wistron NeWeb. But the stock apears to be less risky and, when comparing its historical volatility, Shan Loong Transportation Co is 1.82 times less risky than Wistron NeWeb. The stock trades about -0.57 of its potential returns per unit of risk. The Wistron NeWeb Corp is currently generating about 0.19 of returns per unit of risk over similar time horizon. If you would invest 11,100 in Wistron NeWeb Corp on September 17, 2024 and sell it today you would earn a total of 750.00 from holding Wistron NeWeb Corp or generate 6.76% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Shan Loong Transportation Co vs. Wistron NeWeb Corp
Performance |
Timeline |
Shan Loong Transport |
Wistron NeWeb Corp |
Shan Loong and Wistron NeWeb Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Shan Loong and Wistron NeWeb
The main advantage of trading using opposite Shan Loong and Wistron NeWeb positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Shan Loong position performs unexpectedly, Wistron NeWeb 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 Wistron NeWeb will offset losses from the drop in Wistron NeWeb's long position.Shan Loong vs. Kerry TJ Logistics | Shan Loong vs. China Container Terminal | Shan Loong vs. Eastern Media International | Shan Loong vs. Taiwan Navigation Co |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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