Correlation Between Algorand and Ethereum Classic

Specify exactly 2 symbols:
Can any of the company-specific risk be diversified away by investing in both Algorand and Ethereum Classic 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 Algorand and Ethereum Classic into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Algorand and Ethereum Classic, you can compare the effects of market volatilities on Algorand and Ethereum Classic 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 Algorand with a short position of Ethereum Classic. Check out your portfolio center. Please also check ongoing floating volatility patterns of Algorand and Ethereum Classic.

Diversification Opportunities for Algorand and Ethereum Classic

0.78
  Correlation Coefficient

Poor diversification

The 1 month correlation between Algorand and Ethereum is 0.78. Overlapping area represents the amount of risk that can be diversified away by holding Algorand and Ethereum Classic in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ethereum Classic and Algorand 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 Algorand are associated (or correlated) with Ethereum Classic. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ethereum Classic has no effect on the direction of Algorand i.e., Algorand and Ethereum Classic go up and down completely randomly.

Pair Corralation between Algorand and Ethereum Classic

Assuming the 90 days trading horizon Algorand is expected to under-perform the Ethereum Classic. In addition to that, Algorand is 1.14 times more volatile than Ethereum Classic. It trades about -0.21 of its total potential returns per unit of risk. Ethereum Classic is currently generating about -0.09 per unit of volatility. If you would invest  3,030  in Ethereum Classic on January 20, 2024 and sell it today you would lose (401.00) from holding Ethereum Classic or give up 13.23% of portfolio value over 90 days.
Time Period1 Month [change]
DirectionMoves Together 
StrengthSignificant
Accuracy100.0%
ValuesDaily Returns

Algorand  vs.  Ethereum Classic

 Performance 
       Timeline  
Algorand 

Risk-Adjusted Performance

0 of 100

 
Weak
 
Strong
Insignificant
Over the last 90 days Algorand has generated negative risk-adjusted returns adding no value to investors with long positions. In spite of unsteady performance in the last few months, the Crypto's basic indicators remain rather sound which may send shares a bit higher in May 2024. The latest tumult may also be a sign of longer-term up-swing for Algorand shareholders.
Ethereum Classic 

Risk-Adjusted Performance

0 of 100

 
Weak
 
Strong
Modest
Over the last 90 days Ethereum Classic has generated negative risk-adjusted returns adding no value to investors with long positions. In spite of unsteady performance in the last few months, the Crypto's fundamental indicators remain rather sound which may send shares a bit higher in May 2024. The latest tumult may also be a sign of longer-term up-swing for Ethereum Classic shareholders.

Algorand and Ethereum Classic Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with Algorand and Ethereum Classic

The main advantage of trading using opposite Algorand and Ethereum Classic positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Algorand position performs unexpectedly, Ethereum Classic 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 Classic will offset losses from the drop in Ethereum Classic's long position.
The idea behind Algorand and Ethereum Classic 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 Latest Portfolios module to quick portfolio dashboard that showcases your latest portfolios.

Other Complementary Tools

Earnings Calls
Check upcoming earnings announcements updated hourly across public exchanges
Commodity Channel
Use Commodity Channel Index to analyze current equity momentum
Idea Breakdown
Analyze constituents of all Macroaxis ideas. Macroaxis investment ideas are predefined, sector-focused investing themes
Aroon Oscillator
Analyze current equity momentum using Aroon Oscillator and other momentum ratios
Odds Of Bankruptcy
Get analysis of equity chance of financial distress in the next 2 years
Equity Analysis
Research over 250,000 global equities including funds, stocks and ETFs to find investment opportunities
Portfolio Suggestion
Get suggestions outside of your existing asset allocation including your own model portfolios
CEOs Directory
Screen CEOs from public companies around the world
Premium Stories
Follow Macroaxis premium stories from verified contributors across different equity types, categories and coverage scope
Fundamentals Comparison
Compare fundamentals across multiple equities to find investing opportunities
Watchlist Optimization
Optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm