Correlation Between Dow Jones and KUAISHOU TECHNOLOGY
Can any of the company-specific risk be diversified away by investing in both Dow Jones and KUAISHOU TECHNOLOGY 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 Dow Jones and KUAISHOU TECHNOLOGY into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Dow Jones Industrial and KUAISHOU TECHNOLOGY CLB, you can compare the effects of market volatilities on Dow Jones and KUAISHOU TECHNOLOGY 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 Dow Jones with a short position of KUAISHOU TECHNOLOGY. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dow Jones and KUAISHOU TECHNOLOGY.
Diversification Opportunities for Dow Jones and KUAISHOU TECHNOLOGY
0.5 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Dow and KUAISHOU is 0.5. Overlapping area represents the amount of risk that can be diversified away by holding Dow Jones Industrial and KUAISHOU TECHNOLOGY CLB in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on KUAISHOU TECHNOLOGY CLB and Dow Jones 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 Dow Jones Industrial are associated (or correlated) with KUAISHOU TECHNOLOGY. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of KUAISHOU TECHNOLOGY CLB has no effect on the direction of Dow Jones i.e., Dow Jones and KUAISHOU TECHNOLOGY go up and down completely randomly.
Pair Corralation between Dow Jones and KUAISHOU TECHNOLOGY
Assuming the 90 days trading horizon Dow Jones Industrial is expected to generate 0.35 times more return on investment than KUAISHOU TECHNOLOGY. However, Dow Jones Industrial is 2.84 times less risky than KUAISHOU TECHNOLOGY. It trades about 0.17 of its potential returns per unit of risk. KUAISHOU TECHNOLOGY CLB is currently generating about -0.21 per unit of risk. If you would invest 4,234,224 in Dow Jones Industrial on October 20, 2024 and sell it today you would earn a total of 114,559 from holding Dow Jones Industrial or generate 2.71% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 80.95% |
Values | Daily Returns |
Dow Jones Industrial vs. KUAISHOU TECHNOLOGY CLB
Performance |
Timeline |
Dow Jones and KUAISHOU TECHNOLOGY Volatility Contrast
Predicted Return Density |
Returns |
Dow Jones Industrial
Pair trading matchups for Dow Jones
KUAISHOU TECHNOLOGY CLB
Pair trading matchups for KUAISHOU TECHNOLOGY
Pair Trading with Dow Jones and KUAISHOU TECHNOLOGY
The main advantage of trading using opposite Dow Jones and KUAISHOU TECHNOLOGY positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dow Jones position performs unexpectedly, KUAISHOU TECHNOLOGY 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 KUAISHOU TECHNOLOGY will offset losses from the drop in KUAISHOU TECHNOLOGY's long position.Dow Jones vs. SkyWest | Dow Jones vs. Air Transport Services | Dow Jones vs. LATAM Airlines Group | Dow Jones vs. Emerson Radio |
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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 Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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