Correlation Between AcadeMedia and Thor Mining
Can any of the company-specific risk be diversified away by investing in both AcadeMedia and Thor Mining 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 AcadeMedia and Thor Mining into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between AcadeMedia AB and Thor Mining PLC, you can compare the effects of market volatilities on AcadeMedia and Thor Mining 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 AcadeMedia with a short position of Thor Mining. Check out your portfolio center. Please also check ongoing floating volatility patterns of AcadeMedia and Thor Mining.
Diversification Opportunities for AcadeMedia and Thor Mining
-0.65 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between AcadeMedia and Thor is -0.65. Overlapping area represents the amount of risk that can be diversified away by holding AcadeMedia AB and Thor Mining PLC in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Thor Mining PLC and AcadeMedia 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 AcadeMedia AB are associated (or correlated) with Thor Mining. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Thor Mining PLC has no effect on the direction of AcadeMedia i.e., AcadeMedia and Thor Mining go up and down completely randomly.
Pair Corralation between AcadeMedia and Thor Mining
Assuming the 90 days trading horizon AcadeMedia is expected to generate 4.76 times less return on investment than Thor Mining. But when comparing it to its historical volatility, AcadeMedia AB is 3.01 times less risky than Thor Mining. It trades about 0.03 of its potential returns per unit of risk. Thor Mining PLC is currently generating about 0.05 of returns per unit of risk over similar time horizon. If you would invest 70.00 in Thor Mining PLC on November 7, 2024 and sell it today you would earn a total of 2.00 from holding Thor Mining PLC or generate 2.86% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
AcadeMedia AB vs. Thor Mining PLC
Performance |
| Timeline |
| AcadeMedia AB |
| Thor Mining PLC |
AcadeMedia and Thor Mining Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with AcadeMedia and Thor Mining
The main advantage of trading using opposite AcadeMedia and Thor Mining positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if AcadeMedia position performs unexpectedly, Thor Mining 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 Thor Mining will offset losses from the drop in Thor Mining's long position.| AcadeMedia vs. Pentair PLC | AcadeMedia vs. GoldMining | AcadeMedia vs. Empire Metals Limited | AcadeMedia vs. Systemair AB |
| Thor Mining vs. Capital Metals PLC | Thor Mining vs. European Metals Holdings | Thor Mining vs. Polar Capital Technology | Thor Mining vs. Europa Metals |
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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