Correlation Between Goodtech and XXL ASA
Can any of the company-specific risk be diversified away by investing in both Goodtech and XXL ASA 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 Goodtech and XXL ASA into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Goodtech and XXL ASA, you can compare the effects of market volatilities on Goodtech and XXL ASA 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 Goodtech with a short position of XXL ASA. Check out your portfolio center. Please also check ongoing floating volatility patterns of Goodtech and XXL ASA.
Diversification Opportunities for Goodtech and XXL ASA
Very poor diversification
The 3 months correlation between Goodtech and XXL is 0.87. Overlapping area represents the amount of risk that can be diversified away by holding Goodtech and XXL ASA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on XXL ASA and Goodtech 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 Goodtech are associated (or correlated) with XXL ASA. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of XXL ASA has no effect on the direction of Goodtech i.e., Goodtech and XXL ASA go up and down completely randomly.
Pair Corralation between Goodtech and XXL ASA
Assuming the 90 days trading horizon Goodtech is expected to generate 0.11 times more return on investment than XXL ASA. However, Goodtech is 9.23 times less risky than XXL ASA. It trades about -0.16 of its potential returns per unit of risk. XXL ASA is currently generating about -0.36 per unit of risk. If you would invest 990.00 in Goodtech on September 1, 2024 and sell it today you would lose (64.00) from holding Goodtech or give up 6.46% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Goodtech vs. XXL ASA
Performance |
Timeline |
Goodtech |
XXL ASA |
Goodtech and XXL ASA Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Goodtech and XXL ASA
The main advantage of trading using opposite Goodtech and XXL ASA positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Goodtech position performs unexpectedly, XXL ASA 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 XXL ASA will offset losses from the drop in XXL ASA's long position.Goodtech vs. Eidesvik Offshore ASA | Goodtech vs. Borgestad A | Goodtech vs. Kitron ASA | Goodtech vs. Havila Shipping ASA |
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 Stock Screener module to find equities using a custom stock filter or screen asymmetry in trading patterns, price, volume, or investment outlook..
Other Complementary Tools
Commodity Channel Use Commodity Channel Index to analyze current equity momentum | |
Bollinger Bands Use Bollinger Bands indicator to analyze target price for a given investing horizon | |
Transaction History View history of all your transactions and understand their impact on performance | |
Pattern Recognition Use different Pattern Recognition models to time the market across multiple global exchanges | |
Insider Screener Find insiders across different sectors to evaluate their impact on performance |