Correlation Between Golem Network and Stacks
Can any of the company-specific risk be diversified away by investing in both Golem Network and Stacks 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 Golem Network and Stacks into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Golem Network Token and Stacks, you can compare the effects of market volatilities on Golem Network and Stacks 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 Golem Network with a short position of Stacks. Check out your portfolio center. Please also check ongoing floating volatility patterns of Golem Network and Stacks.
Diversification Opportunities for Golem Network and Stacks
0.76 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Golem and Stacks is 0.76. Overlapping area represents the amount of risk that can be diversified away by holding Golem Network Token and Stacks in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Stacks and Golem Network 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 Golem Network Token are associated (or correlated) with Stacks. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Stacks has no effect on the direction of Golem Network i.e., Golem Network and Stacks go up and down completely randomly.
Pair Corralation between Golem Network and Stacks
Assuming the 90 days trading horizon Golem Network Token is expected to generate 0.96 times more return on investment than Stacks. However, Golem Network Token is 1.04 times less risky than Stacks. It trades about -0.08 of its potential returns per unit of risk. Stacks is currently generating about -0.21 per unit of risk. If you would invest 37.00 in Golem Network Token on December 29, 2024 and sell it today you would lose (12.00) from holding Golem Network Token or give up 32.43% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Golem Network Token vs. Stacks
Performance |
Timeline |
Golem Network Token |
Stacks |
Golem Network and Stacks Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Golem Network and Stacks
The main advantage of trading using opposite Golem Network and Stacks positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Golem Network position performs unexpectedly, Stacks 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 Stacks will offset losses from the drop in Stacks' long position.The idea behind Golem Network Token and Stacks pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.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 Bollinger Bands module to use Bollinger Bands indicator to analyze target price for a given investing horizon.
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