Correlation Between Team Internet and Aurora Investment
Can any of the company-specific risk be diversified away by investing in both Team Internet and Aurora Investment 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 Team Internet and Aurora Investment into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Team Internet Group and Aurora Investment Trust, you can compare the effects of market volatilities on Team Internet and Aurora Investment 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 Team Internet with a short position of Aurora Investment. Check out your portfolio center. Please also check ongoing floating volatility patterns of Team Internet and Aurora Investment.
Diversification Opportunities for Team Internet and Aurora Investment
0.66 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Team and Aurora is 0.66. Overlapping area represents the amount of risk that can be diversified away by holding Team Internet Group and Aurora Investment Trust in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Aurora Investment Trust and Team Internet 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 Team Internet Group are associated (or correlated) with Aurora Investment. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Aurora Investment Trust has no effect on the direction of Team Internet i.e., Team Internet and Aurora Investment go up and down completely randomly.
Pair Corralation between Team Internet and Aurora Investment
Assuming the 90 days trading horizon Team Internet Group is expected to generate 2.83 times more return on investment than Aurora Investment. However, Team Internet is 2.83 times more volatile than Aurora Investment Trust. It trades about 0.13 of its potential returns per unit of risk. Aurora Investment Trust is currently generating about 0.11 per unit of risk. If you would invest 5,290 in Team Internet Group on April 23, 2025 and sell it today you would earn a total of 1,200 from holding Team Internet Group or generate 22.68% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Team Internet Group vs. Aurora Investment Trust
Performance |
Timeline |
Team Internet Group |
Aurora Investment Trust |
Team Internet and Aurora Investment Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Team Internet and Aurora Investment
The main advantage of trading using opposite Team Internet and Aurora Investment positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Team Internet position performs unexpectedly, Aurora Investment 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 Aurora Investment will offset losses from the drop in Aurora Investment's long position.Team Internet vs. Samsung Electronics Co | Team Internet vs. Samsung Electronics Co | Team Internet vs. State Bank of | Team Internet vs. Reliance Industries Limited |
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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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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