Correlation Between GLCN and KraneShares CSI
Can any of the company-specific risk be diversified away by investing in both GLCN and KraneShares CSI 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 GLCN and KraneShares CSI into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between GLCN and KraneShares CSI China, you can compare the effects of market volatilities on GLCN and KraneShares CSI 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 GLCN with a short position of KraneShares CSI. Check out your portfolio center. Please also check ongoing floating volatility patterns of GLCN and KraneShares CSI.
Diversification Opportunities for GLCN and KraneShares CSI
-0.28 | Correlation Coefficient |
Very good diversification
The 3 months correlation between GLCN and KraneShares is -0.28. Overlapping area represents the amount of risk that can be diversified away by holding GLCN and KraneShares CSI China in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on KraneShares CSI China and GLCN 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 GLCN are associated (or correlated) with KraneShares CSI. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of KraneShares CSI China has no effect on the direction of GLCN i.e., GLCN and KraneShares CSI go up and down completely randomly.
Pair Corralation between GLCN and KraneShares CSI
Given the investment horizon of 90 days GLCN is expected to under-perform the KraneShares CSI. But the etf apears to be less risky and, when comparing its historical volatility, GLCN is 2.0 times less risky than KraneShares CSI. The etf trades about -0.05 of its potential returns per unit of risk. The KraneShares CSI China is currently generating about 0.01 of returns per unit of risk over similar time horizon. If you would invest 3,090 in KraneShares CSI China on September 14, 2024 and sell it today you would earn a total of 79.00 from holding KraneShares CSI China or generate 2.56% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 28.89% |
| Values | Daily Returns |
GLCN vs. KraneShares CSI China
Performance |
| Timeline |
| GLCN |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
| KraneShares CSI China |
GLCN and KraneShares CSI Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with GLCN and KraneShares CSI
The main advantage of trading using opposite GLCN and KraneShares CSI positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GLCN position performs unexpectedly, KraneShares CSI 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 KraneShares CSI will offset losses from the drop in KraneShares CSI's long position.| GLCN vs. KraneShares CSI China | GLCN vs. Invesco China Technology | GLCN vs. iShares MSCI India | GLCN vs. Xtrackers Harvest CSI |
| KraneShares CSI vs. iShares MSCI China | KraneShares CSI vs. Invesco China Technology | KraneShares CSI vs. Xtrackers Harvest CSI | KraneShares CSI vs. iShares China Large Cap |
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 Valuation module to check real value of public entities based on technical and fundamental data.
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