Correlation Between Franklin FTSE and KraneShares CSI
Can any of the company-specific risk be diversified away by investing in both Franklin FTSE 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 Franklin FTSE and KraneShares CSI into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Franklin FTSE Hong and KraneShares CSI China, you can compare the effects of market volatilities on Franklin FTSE 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 Franklin FTSE with a short position of KraneShares CSI. Check out your portfolio center. Please also check ongoing floating volatility patterns of Franklin FTSE and KraneShares CSI.
Diversification Opportunities for Franklin FTSE and KraneShares CSI
0.5 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Franklin and KraneShares is 0.5. Overlapping area represents the amount of risk that can be diversified away by holding Franklin FTSE Hong 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 Franklin FTSE 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 Franklin FTSE Hong 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 Franklin FTSE i.e., Franklin FTSE and KraneShares CSI go up and down completely randomly.
Pair Corralation between Franklin FTSE and KraneShares CSI
Given the investment horizon of 90 days Franklin FTSE is expected to generate 3.66 times less return on investment than KraneShares CSI. But when comparing it to its historical volatility, Franklin FTSE Hong is 2.12 times less risky than KraneShares CSI. It trades about 0.06 of its potential returns per unit of risk. KraneShares CSI China is currently generating about 0.1 of returns per unit of risk over similar time horizon. If you would invest 2,962 in KraneShares CSI China on December 4, 2024 and sell it today you would earn a total of 427.00 from holding KraneShares CSI China or generate 14.42% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 98.33% |
Values | Daily Returns |
Franklin FTSE Hong vs. KraneShares CSI China
Performance |
Timeline |
Franklin FTSE Hong |
KraneShares CSI China |
Franklin FTSE and KraneShares CSI Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Franklin FTSE and KraneShares CSI
The main advantage of trading using opposite Franklin FTSE and KraneShares CSI positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Franklin FTSE 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.Franklin FTSE vs. Franklin FTSE China | Franklin FTSE vs. Franklin FTSE Taiwan | Franklin FTSE vs. Franklin FTSE Japan | Franklin FTSE vs. Franklin FTSE Germany |
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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 Suggestion module to get suggestions outside of your existing asset allocation including your own model portfolios.
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