Correlation Between BaoMinh Insurance and Tin Nghia
Can any of the company-specific risk be diversified away by investing in both BaoMinh Insurance and Tin Nghia 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 BaoMinh Insurance and Tin Nghia into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between BaoMinh Insurance Corp and Tin Nghia Industrial, you can compare the effects of market volatilities on BaoMinh Insurance and Tin Nghia 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 BaoMinh Insurance with a short position of Tin Nghia. Check out your portfolio center. Please also check ongoing floating volatility patterns of BaoMinh Insurance and Tin Nghia.
Diversification Opportunities for BaoMinh Insurance and Tin Nghia
0.65 | Correlation Coefficient |
Poor diversification
The 3 months correlation between BaoMinh and Tin is 0.65. Overlapping area represents the amount of risk that can be diversified away by holding BaoMinh Insurance Corp and Tin Nghia Industrial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Tin Nghia Industrial and BaoMinh Insurance 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 BaoMinh Insurance Corp are associated (or correlated) with Tin Nghia. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Tin Nghia Industrial has no effect on the direction of BaoMinh Insurance i.e., BaoMinh Insurance and Tin Nghia go up and down completely randomly.
Pair Corralation between BaoMinh Insurance and Tin Nghia
Assuming the 90 days trading horizon BaoMinh Insurance Corp is expected to under-perform the Tin Nghia. In addition to that, BaoMinh Insurance is 1.5 times more volatile than Tin Nghia Industrial. It trades about -0.05 of its total potential returns per unit of risk. Tin Nghia Industrial is currently generating about -0.01 per unit of volatility. If you would invest 2,310,000 in Tin Nghia Industrial on September 16, 2024 and sell it today you would lose (25,000) from holding Tin Nghia Industrial or give up 1.08% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
BaoMinh Insurance Corp vs. Tin Nghia Industrial
Performance |
Timeline |
BaoMinh Insurance Corp |
Tin Nghia Industrial |
BaoMinh Insurance and Tin Nghia Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with BaoMinh Insurance and Tin Nghia
The main advantage of trading using opposite BaoMinh Insurance and Tin Nghia positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if BaoMinh Insurance position performs unexpectedly, Tin Nghia 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 Tin Nghia will offset losses from the drop in Tin Nghia's long position.BaoMinh Insurance vs. VTC Telecommunications JSC | BaoMinh Insurance vs. MST Investment JSC | BaoMinh Insurance vs. Nam Kim Steel | BaoMinh Insurance vs. HUD1 Investment and |
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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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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