Correlation Between Deutsche Boerse and Hong Kong
Can any of the company-specific risk be diversified away by investing in both Deutsche Boerse and Hong Kong 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 Deutsche Boerse and Hong Kong into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Deutsche Boerse AG and Hong Kong Exchanges, you can compare the effects of market volatilities on Deutsche Boerse and Hong Kong 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 Deutsche Boerse with a short position of Hong Kong. Check out your portfolio center. Please also check ongoing floating volatility patterns of Deutsche Boerse and Hong Kong.
Diversification Opportunities for Deutsche Boerse and Hong Kong
0.1 | Correlation Coefficient |
Average diversification
The 3 months correlation between Deutsche and Hong is 0.1. Overlapping area represents the amount of risk that can be diversified away by holding Deutsche Boerse AG and Hong Kong Exchanges in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hong Kong Exchanges and Deutsche Boerse 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 Deutsche Boerse AG are associated (or correlated) with Hong Kong. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hong Kong Exchanges has no effect on the direction of Deutsche Boerse i.e., Deutsche Boerse and Hong Kong go up and down completely randomly.
Pair Corralation between Deutsche Boerse and Hong Kong
Assuming the 90 days horizon Deutsche Boerse AG is expected to generate 0.23 times more return on investment than Hong Kong. However, Deutsche Boerse AG is 4.28 times less risky than Hong Kong. It trades about -0.02 of its potential returns per unit of risk. Hong Kong Exchanges is currently generating about -0.02 per unit of risk. If you would invest 2,323 in Deutsche Boerse AG on October 9, 2024 and sell it today you would lose (41.00) from holding Deutsche Boerse AG or give up 1.76% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Deutsche Boerse AG vs. Hong Kong Exchanges
Performance |
Timeline |
Deutsche Boerse AG |
Hong Kong Exchanges |
Deutsche Boerse and Hong Kong Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Deutsche Boerse and Hong Kong
The main advantage of trading using opposite Deutsche Boerse and Hong Kong positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Deutsche Boerse position performs unexpectedly, Hong Kong 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 Hong Kong will offset losses from the drop in Hong Kong's long position.Deutsche Boerse vs. London Stock Exchange | Deutsche Boerse vs. Hong Kong Exchanges | Deutsche Boerse vs. Deutsche Brse AG | Deutsche Boerse vs. Singapore Exchange Limited |
Hong Kong vs. Singapore Exchange Limited | Hong Kong vs. London Stock Exchange | Hong Kong vs. MSCI Inc | Hong Kong vs. London Stock Exchange |
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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