Correlation Between Taiwan Shin and Giant Manufacturing
Can any of the company-specific risk be diversified away by investing in both Taiwan Shin and Giant Manufacturing 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 Taiwan Shin and Giant Manufacturing into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Taiwan Shin Kong and Giant Manufacturing Co, you can compare the effects of market volatilities on Taiwan Shin and Giant Manufacturing 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 Taiwan Shin with a short position of Giant Manufacturing. Check out your portfolio center. Please also check ongoing floating volatility patterns of Taiwan Shin and Giant Manufacturing.
Diversification Opportunities for Taiwan Shin and Giant Manufacturing
0.72 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Taiwan and Giant is 0.72. Overlapping area represents the amount of risk that can be diversified away by holding Taiwan Shin Kong and Giant Manufacturing Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Giant Manufacturing and Taiwan Shin 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 Taiwan Shin Kong are associated (or correlated) with Giant Manufacturing. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Giant Manufacturing has no effect on the direction of Taiwan Shin i.e., Taiwan Shin and Giant Manufacturing go up and down completely randomly.
Pair Corralation between Taiwan Shin and Giant Manufacturing
Assuming the 90 days trading horizon Taiwan Shin Kong is expected to generate 0.26 times more return on investment than Giant Manufacturing. However, Taiwan Shin Kong is 3.87 times less risky than Giant Manufacturing. It trades about 0.03 of its potential returns per unit of risk. Giant Manufacturing Co is currently generating about -0.03 per unit of risk. If you would invest 3,809 in Taiwan Shin Kong on October 25, 2024 and sell it today you would earn a total of 286.00 from holding Taiwan Shin Kong or generate 7.51% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 99.79% |
Values | Daily Returns |
Taiwan Shin Kong vs. Giant Manufacturing Co
Performance |
Timeline |
Taiwan Shin Kong |
Giant Manufacturing |
Taiwan Shin and Giant Manufacturing Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Taiwan Shin and Giant Manufacturing
The main advantage of trading using opposite Taiwan Shin and Giant Manufacturing positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Taiwan Shin position performs unexpectedly, Giant Manufacturing 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 Giant Manufacturing will offset losses from the drop in Giant Manufacturing's long position.Taiwan Shin vs. Taiwan Secom Co | Taiwan Shin vs. Yulon Finance Corp | Taiwan Shin vs. CHC Resources Corp | Taiwan Shin vs. Nak Sealing Technologies |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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