Correlation Between APG Securities and Thong Nhat
Can any of the company-specific risk be diversified away by investing in both APG Securities and Thong Nhat 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 APG Securities and Thong Nhat into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between APG Securities Joint and Thong Nhat Rubber, you can compare the effects of market volatilities on APG Securities and Thong Nhat 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 APG Securities with a short position of Thong Nhat. Check out your portfolio center. Please also check ongoing floating volatility patterns of APG Securities and Thong Nhat.
Diversification Opportunities for APG Securities and Thong Nhat
0.56 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between APG and Thong is 0.56. Overlapping area represents the amount of risk that can be diversified away by holding APG Securities Joint and Thong Nhat Rubber in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Thong Nhat Rubber and APG Securities 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 APG Securities Joint are associated (or correlated) with Thong Nhat. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Thong Nhat Rubber has no effect on the direction of APG Securities i.e., APG Securities and Thong Nhat go up and down completely randomly.
Pair Corralation between APG Securities and Thong Nhat
Assuming the 90 days trading horizon APG Securities Joint is expected to under-perform the Thong Nhat. But the stock apears to be less risky and, when comparing its historical volatility, APG Securities Joint is 1.23 times less risky than Thong Nhat. The stock trades about -0.32 of its potential returns per unit of risk. The Thong Nhat Rubber is currently generating about -0.09 of returns per unit of risk over similar time horizon. If you would invest 3,500,000 in Thong Nhat Rubber on October 12, 2024 and sell it today you would lose (300,000) from holding Thong Nhat Rubber or give up 8.57% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 76.19% |
| Values | Daily Returns |
APG Securities Joint vs. Thong Nhat Rubber
Performance |
| Timeline |
| APG Securities Joint |
| Thong Nhat Rubber |
APG Securities and Thong Nhat Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with APG Securities and Thong Nhat
The main advantage of trading using opposite APG Securities and Thong Nhat positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if APG Securities position performs unexpectedly, Thong Nhat 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 Thong Nhat will offset losses from the drop in Thong Nhat's long position.| APG Securities vs. Vina2 Investment and | APG Securities vs. Thanh Dat Investment | APG Securities vs. Development Investment Construction | APG Securities vs. Long Giang Investment |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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