Correlation Between Insurance Australia and DALATA HOTEL
Can any of the company-specific risk be diversified away by investing in both Insurance Australia and DALATA HOTEL 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 Insurance Australia and DALATA HOTEL into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Insurance Australia Group and DALATA HOTEL, you can compare the effects of market volatilities on Insurance Australia and DALATA HOTEL 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 Insurance Australia with a short position of DALATA HOTEL. Check out your portfolio center. Please also check ongoing floating volatility patterns of Insurance Australia and DALATA HOTEL.
Diversification Opportunities for Insurance Australia and DALATA HOTEL
0.81 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Insurance and DALATA is 0.81. Overlapping area represents the amount of risk that can be diversified away by holding Insurance Australia Group and DALATA HOTEL in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on DALATA HOTEL and Insurance Australia 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 Insurance Australia Group are associated (or correlated) with DALATA HOTEL. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of DALATA HOTEL has no effect on the direction of Insurance Australia i.e., Insurance Australia and DALATA HOTEL go up and down completely randomly.
Pair Corralation between Insurance Australia and DALATA HOTEL
Assuming the 90 days horizon Insurance Australia Group is expected to generate 3.76 times more return on investment than DALATA HOTEL. However, Insurance Australia is 3.76 times more volatile than DALATA HOTEL. It trades about 0.03 of its potential returns per unit of risk. DALATA HOTEL is currently generating about 0.0 per unit of risk. If you would invest 492.00 in Insurance Australia Group on September 22, 2024 and sell it today you would earn a total of 4.00 from holding Insurance Australia Group or generate 0.81% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Insurance Australia Group vs. DALATA HOTEL
Performance |
Timeline |
Insurance Australia |
DALATA HOTEL |
Insurance Australia and DALATA HOTEL Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Insurance Australia and DALATA HOTEL
The main advantage of trading using opposite Insurance Australia and DALATA HOTEL positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Insurance Australia position performs unexpectedly, DALATA HOTEL 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 DALATA HOTEL will offset losses from the drop in DALATA HOTEL's long position.Insurance Australia vs. The Progressive | Insurance Australia vs. The Allstate | Insurance Australia vs. PICC Property and | Insurance Australia vs. Cincinnati Financial |
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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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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