Correlation Between NMI Holdings and GUOTAI JUNAN
Can any of the company-specific risk be diversified away by investing in both NMI Holdings and GUOTAI JUNAN 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 NMI Holdings and GUOTAI JUNAN into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NMI Holdings and GUOTAI JUNAN SEC, you can compare the effects of market volatilities on NMI Holdings and GUOTAI JUNAN 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 NMI Holdings with a short position of GUOTAI JUNAN. Check out your portfolio center. Please also check ongoing floating volatility patterns of NMI Holdings and GUOTAI JUNAN.
Diversification Opportunities for NMI Holdings and GUOTAI JUNAN
-0.33 | Correlation Coefficient |
Very good diversification
The 3 months correlation between NMI and GUOTAI is -0.33. Overlapping area represents the amount of risk that can be diversified away by holding NMI Holdings and GUOTAI JUNAN SEC in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on GUOTAI JUNAN SEC and NMI Holdings 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 NMI Holdings are associated (or correlated) with GUOTAI JUNAN. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of GUOTAI JUNAN SEC has no effect on the direction of NMI Holdings i.e., NMI Holdings and GUOTAI JUNAN go up and down completely randomly.
Pair Corralation between NMI Holdings and GUOTAI JUNAN
Assuming the 90 days horizon NMI Holdings is expected to generate 3.08 times less return on investment than GUOTAI JUNAN. But when comparing it to its historical volatility, NMI Holdings is 3.76 times less risky than GUOTAI JUNAN. It trades about 0.1 of its potential returns per unit of risk. GUOTAI JUNAN SEC is currently generating about 0.08 of returns per unit of risk over similar time horizon. If you would invest 24.00 in GUOTAI JUNAN SEC on August 30, 2024 and sell it today you would earn a total of 113.00 from holding GUOTAI JUNAN SEC or generate 470.83% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 99.8% |
| Values | Daily Returns |
NMI Holdings vs. GUOTAI JUNAN SEC
Performance |
| Timeline |
| NMI Holdings |
| GUOTAI JUNAN SEC |
NMI Holdings and GUOTAI JUNAN Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with NMI Holdings and GUOTAI JUNAN
The main advantage of trading using opposite NMI Holdings and GUOTAI JUNAN positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NMI Holdings position performs unexpectedly, GUOTAI JUNAN 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 GUOTAI JUNAN will offset losses from the drop in GUOTAI JUNAN's long position.| NMI Holdings vs. Perseus Mining Limited | NMI Holdings vs. CVW CLEANTECH INC | NMI Holdings vs. Warner Music Group | NMI Holdings vs. Tencent Music Entertainment |
| GUOTAI JUNAN vs. MSCI Inc | GUOTAI JUNAN vs. Superior Plus Corp | GUOTAI JUNAN vs. NMI Holdings | GUOTAI JUNAN vs. SIVERS SEMICONDUCTORS AB |
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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