Correlation Between Near and Ethereum
Can any of the company-specific risk be diversified away by investing in both Near and Ethereum 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 Near and Ethereum into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Near and Ethereum, you can compare the effects of market volatilities on Near and Ethereum 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 Near with a short position of Ethereum. Check out your portfolio center. Please also check ongoing floating volatility patterns of Near and Ethereum.
Diversification Opportunities for Near and Ethereum
Poor diversification
The 3 months correlation between Near and Ethereum is 0.74. Overlapping area represents the amount of risk that can be diversified away by holding Near and Ethereum in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ethereum and Near 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 Near are associated (or correlated) with Ethereum. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ethereum has no effect on the direction of Near i.e., Near and Ethereum go up and down completely randomly.
Pair Corralation between Near and Ethereum
Assuming the 90 days trading horizon Near is expected to generate 1.25 times more return on investment than Ethereum. However, Near is 1.25 times more volatile than Ethereum. It trades about 0.35 of its potential returns per unit of risk. Ethereum is currently generating about 0.35 per unit of risk. If you would invest 423.00 in Near on August 26, 2024 and sell it today you would earn a total of 197.00 from holding Near or generate 46.57% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Near vs. Ethereum
Performance |
| Timeline |
| Near |
| Ethereum |
Near and Ethereum Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Near and Ethereum
The main advantage of trading using opposite Near and Ethereum positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Near position performs unexpectedly, Ethereum 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 Ethereum will offset losses from the drop in Ethereum's long position.The idea behind Near and Ethereum 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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
Other Complementary Tools
| AI Portfolio Architect Use AI to generate optimal portfolios and find profitable investment opportunities | |
| My Watchlist Analysis Analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like | |
| Insider Screener Find insiders across different sectors to evaluate their impact on performance | |
| Global Correlations Find global opportunities by holding instruments from different markets | |
| CEOs Directory Screen CEOs from public companies around the world |