Correlation Between Bitcoin and Ravencoin
Can any of the company-specific risk be diversified away by investing in both Bitcoin and Ravencoin 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 and Ravencoin into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bitcoin and Ravencoin, you can compare the effects of market volatilities on Bitcoin and Ravencoin 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 with a short position of Ravencoin. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bitcoin and Ravencoin.
Diversification Opportunities for Bitcoin and Ravencoin
Very poor diversification
The 3 months correlation between Bitcoin and Ravencoin is 0.88. Overlapping area represents the amount of risk that can be diversified away by holding Bitcoin and Ravencoin in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ravencoin and Bitcoin 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 are associated (or correlated) with Ravencoin. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ravencoin has no effect on the direction of Bitcoin i.e., Bitcoin and Ravencoin go up and down completely randomly.
Pair Corralation between Bitcoin and Ravencoin
Assuming the 90 days trading horizon Bitcoin is expected to generate 1.04 times less return on investment than Ravencoin. But when comparing it to its historical volatility, Bitcoin is 1.78 times less risky than Ravencoin. It trades about 0.24 of its potential returns per unit of risk. Ravencoin is currently generating about 0.14 of returns per unit of risk over similar time horizon. If you would invest 1.62 in Ravencoin on August 30, 2024 and sell it today you would earn a total of 0.88 from holding Ravencoin or generate 54.32% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Bitcoin vs. Ravencoin
Performance |
Timeline |
Bitcoin |
Ravencoin |
Bitcoin and Ravencoin Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bitcoin and Ravencoin
The main advantage of trading using opposite Bitcoin and Ravencoin positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bitcoin position performs unexpectedly, Ravencoin 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 Ravencoin will offset losses from the drop in Ravencoin's long position.The idea behind Bitcoin and Ravencoin 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 Equity Search module to search for actively traded equities including funds and ETFs from over 30 global markets.
Other Complementary Tools
Alpha Finder Use alpha and beta coefficients to find investment opportunities after accounting for the risk | |
Watchlist Optimization Optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm | |
Portfolio Volatility Check portfolio volatility and analyze historical return density to properly model market risk | |
Portfolio Backtesting Avoid under-diversification and over-optimization by backtesting your portfolios | |
Fundamentals Comparison Compare fundamentals across multiple equities to find investing opportunities |