Correlation Between Bitcoin Cash and Aelf

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

Diversification Opportunities for Bitcoin Cash and Aelf

0.03
  Correlation Coefficient

Significant diversification

The 3 months correlation between Bitcoin and Aelf is 0.03. Overlapping area represents the amount of risk that can be diversified away by holding Bitcoin Cash and aelf in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on aelf and Bitcoin Cash 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 Bitcoin Cash are associated (or correlated) with Aelf. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of aelf has no effect on the direction of Bitcoin Cash i.e., Bitcoin Cash and Aelf go up and down completely randomly.

Pair Corralation between Bitcoin Cash and Aelf

Assuming the 90 days trading horizon Bitcoin Cash is expected to under-perform the Aelf. In addition to that, Bitcoin Cash is 1.05 times more volatile than aelf. It trades about -0.34 of its total potential returns per unit of risk. aelf is currently generating about -0.04 per unit of volatility. If you would invest  59.00  in aelf on February 4, 2024 and sell it today you would lose (4.00) from holding aelf or give up 6.78% of portfolio value over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthInsignificant
Accuracy100.0%
ValuesDaily Returns

Bitcoin Cash  vs.  aelf

 Performance 
       Timeline  
Bitcoin Cash 

Risk-Adjusted Performance

10 of 100

 
Weak
 
Strong
OK
Compared to the overall equity markets, risk-adjusted returns on investments in Bitcoin Cash are ranked lower than 10 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady technical indicators, Bitcoin Cash exhibited solid returns over the last few months and may actually be approaching a breakup point.
aelf 

Risk-Adjusted Performance

0 of 100

 
Weak
 
Strong
Very Weak
Over the last 90 days aelf has generated negative risk-adjusted returns adding no value to investors with long positions. In spite of rather sound technical and fundamental indicators, Aelf is not utilizing all of its potentials. The latest stock price tumult, may contribute to shorter-term losses for the shareholders.

Bitcoin Cash and Aelf Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with Bitcoin Cash and Aelf

The main advantage of trading using opposite Bitcoin Cash and Aelf positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bitcoin Cash position performs unexpectedly, Aelf 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 Aelf will offset losses from the drop in Aelf's long position.
The idea behind Bitcoin Cash and aelf 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 Comparator module to compare the composition, asset allocations and performance of any two portfolios in your account.

Other Complementary Tools

Portfolio Rebalancing
Analyze risk-adjusted returns against different time horizons to find asset-allocation targets
Bonds Directory
Find actively traded corporate debentures issued by US companies
Alpha Finder
Use alpha and beta coefficients to find investment opportunities after accounting for the risk
Idea Analyzer
Analyze all characteristics, volatility and risk-adjusted return of Macroaxis ideas
Portfolio Holdings
Check your current holdings and cash postion to detemine if your portfolio needs rebalancing
Price Transformation
Use Price Transformation models to analyze the depth of different equity instruments across global markets
Investing Opportunities
Build portfolios using our predefined set of ideas and optimize them against your investing preferences
Odds Of Bankruptcy
Get analysis of equity chance of financial distress in the next 2 years
Piotroski F Score
Get Piotroski F Score based on the binary analysis strategy of nine different fundamentals
Instant Ratings
Determine any equity ratings based on digital recommendations. Macroaxis instant equity ratings are based on combination of fundamental analysis and risk-adjusted market performance
Idea Breakdown
Analyze constituents of all Macroaxis ideas. Macroaxis investment ideas are predefined, sector-focused investing themes
Headlines Timeline
Stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity