Correlation Between Aeon Credit and Datasonic Group
Can any of the company-specific risk be diversified away by investing in both Aeon Credit and Datasonic Group 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 Aeon Credit and Datasonic Group into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Aeon Credit Service and Datasonic Group Bhd, you can compare the effects of market volatilities on Aeon Credit and Datasonic Group 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 Aeon Credit with a short position of Datasonic Group. Check out your portfolio center. Please also check ongoing floating volatility patterns of Aeon Credit and Datasonic Group.
Diversification Opportunities for Aeon Credit and Datasonic Group
0.39 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Aeon and Datasonic is 0.39. Overlapping area represents the amount of risk that can be diversified away by holding Aeon Credit Service and Datasonic Group Bhd in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Datasonic Group Bhd and Aeon Credit 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 Aeon Credit Service are associated (or correlated) with Datasonic Group. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Datasonic Group Bhd has no effect on the direction of Aeon Credit i.e., Aeon Credit and Datasonic Group go up and down completely randomly.
Pair Corralation between Aeon Credit and Datasonic Group
Assuming the 90 days trading horizon Aeon Credit Service is expected to under-perform the Datasonic Group. But the stock apears to be less risky and, when comparing its historical volatility, Aeon Credit Service is 2.35 times less risky than Datasonic Group. The stock trades about -0.42 of its potential returns per unit of risk. The Datasonic Group Bhd is currently generating about 0.14 of returns per unit of risk over similar time horizon. If you would invest 40.00 in Datasonic Group Bhd on September 13, 2024 and sell it today you would earn a total of 3.00 from holding Datasonic Group Bhd or generate 7.5% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 95.65% |
Values | Daily Returns |
Aeon Credit Service vs. Datasonic Group Bhd
Performance |
Timeline |
Aeon Credit Service |
Datasonic Group Bhd |
Aeon Credit and Datasonic Group Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Aeon Credit and Datasonic Group
The main advantage of trading using opposite Aeon Credit and Datasonic Group positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Aeon Credit position performs unexpectedly, Datasonic Group 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 Datasonic Group will offset losses from the drop in Datasonic Group's long position.Aeon Credit vs. Alliance Financial Group | Aeon Credit vs. Al Aqar Healthcare | Aeon Credit vs. PMB Technology Bhd | Aeon Credit vs. Digistar Bhd |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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