Correlation Between Shinkong Synthetic and Nan Yang
Can any of the company-specific risk be diversified away by investing in both Shinkong Synthetic and Nan Yang 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 Shinkong Synthetic and Nan Yang into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Shinkong Synthetic Fiber and Nan Yang Dyeing, you can compare the effects of market volatilities on Shinkong Synthetic and Nan Yang 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 Shinkong Synthetic with a short position of Nan Yang. Check out your portfolio center. Please also check ongoing floating volatility patterns of Shinkong Synthetic and Nan Yang.
Diversification Opportunities for Shinkong Synthetic and Nan Yang
0.38 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Shinkong and Nan is 0.38. Overlapping area represents the amount of risk that can be diversified away by holding Shinkong Synthetic Fiber and Nan Yang Dyeing in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Nan Yang Dyeing and Shinkong Synthetic 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 Shinkong Synthetic Fiber are associated (or correlated) with Nan Yang. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Nan Yang Dyeing has no effect on the direction of Shinkong Synthetic i.e., Shinkong Synthetic and Nan Yang go up and down completely randomly.
Pair Corralation between Shinkong Synthetic and Nan Yang
Assuming the 90 days trading horizon Shinkong Synthetic Fiber is expected to under-perform the Nan Yang. In addition to that, Shinkong Synthetic is 1.23 times more volatile than Nan Yang Dyeing. It trades about -0.58 of its total potential returns per unit of risk. Nan Yang Dyeing is currently generating about -0.29 per unit of volatility. If you would invest 3,680 in Nan Yang Dyeing on October 6, 2024 and sell it today you would lose (130.00) from holding Nan Yang Dyeing or give up 3.53% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Shinkong Synthetic Fiber vs. Nan Yang Dyeing
Performance |
Timeline |
Shinkong Synthetic Fiber |
Nan Yang Dyeing |
Shinkong Synthetic and Nan Yang Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Shinkong Synthetic and Nan Yang
The main advantage of trading using opposite Shinkong Synthetic and Nan Yang positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Shinkong Synthetic position performs unexpectedly, Nan Yang 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 Nan Yang will offset losses from the drop in Nan Yang's long position.Shinkong Synthetic vs. Tainan Spinning Co | Shinkong Synthetic vs. Lealea Enterprise Co | Shinkong Synthetic vs. China Petrochemical Development | Shinkong Synthetic vs. Taiwan Styrene Monomer |
Nan Yang vs. Hung Chou Fiber | Nan Yang vs. Shinkong Synthetic Fiber | Nan Yang vs. Carnival Industrial Corp | Nan Yang vs. Tung Ho Textile |
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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