Correlation Between AP Møller and Insurance Australia
Can any of the company-specific risk be diversified away by investing in both AP Møller and Insurance Australia 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 AP Møller and Insurance Australia into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between AP Mller and Insurance Australia Group, you can compare the effects of market volatilities on AP Møller and Insurance Australia 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 AP Møller with a short position of Insurance Australia. Check out your portfolio center. Please also check ongoing floating volatility patterns of AP Møller and Insurance Australia.
Diversification Opportunities for AP Møller and Insurance Australia
-0.72 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between DP4B and Insurance is -0.72. Overlapping area represents the amount of risk that can be diversified away by holding AP Mller and Insurance Australia Group in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Insurance Australia and AP Møller 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 AP Mller are associated (or correlated) with Insurance Australia. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Insurance Australia has no effect on the direction of AP Møller i.e., AP Møller and Insurance Australia go up and down completely randomly.
Pair Corralation between AP Møller and Insurance Australia
Assuming the 90 days trading horizon AP Mller is expected to generate 1.07 times more return on investment than Insurance Australia. However, AP Møller is 1.07 times more volatile than Insurance Australia Group. It trades about 0.09 of its potential returns per unit of risk. Insurance Australia Group is currently generating about -0.06 per unit of risk. If you would invest 146,400 in AP Mller on December 30, 2024 and sell it today you would earn a total of 17,750 from holding AP Mller or generate 12.12% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
AP Mller vs. Insurance Australia Group
Performance |
Timeline |
AP Møller |
Insurance Australia |
AP Møller and Insurance Australia Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with AP Møller and Insurance Australia
The main advantage of trading using opposite AP Møller and Insurance Australia positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if AP Møller position performs unexpectedly, Insurance Australia 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 Insurance Australia will offset losses from the drop in Insurance Australia's long position.AP Møller vs. BROADSTNET LEADL 00025 | AP Møller vs. EMPEROR ENT HOTEL | AP Møller vs. MELIA HOTELS | AP Møller vs. Kaufman Broad SA |
Insurance Australia vs. Ross Stores | Insurance Australia vs. MARKET VECTR RETAIL | Insurance Australia vs. MCEWEN MINING INC | Insurance Australia vs. ANGLO ASIAN MINING |
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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