Correlation Between Tensor and Bitcoin Cash
Can any of the company-specific risk be diversified away by investing in both Tensor and Bitcoin Cash 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 Tensor and Bitcoin Cash into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Tensor and Bitcoin Cash, you can compare the effects of market volatilities on Tensor and Bitcoin Cash 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 Tensor with a short position of Bitcoin Cash. Check out your portfolio center. Please also check ongoing floating volatility patterns of Tensor and Bitcoin Cash.
Diversification Opportunities for Tensor and Bitcoin Cash
0.39 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Tensor and Bitcoin is 0.39. Overlapping area represents the amount of risk that can be diversified away by holding Tensor and Bitcoin Cash in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bitcoin Cash and Tensor 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 Tensor are associated (or correlated) with Bitcoin Cash. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bitcoin Cash has no effect on the direction of Tensor i.e., Tensor and Bitcoin Cash go up and down completely randomly.
Pair Corralation between Tensor and Bitcoin Cash
Assuming the 90 days trading horizon Tensor is expected to under-perform the Bitcoin Cash. In addition to that, Tensor is 1.55 times more volatile than Bitcoin Cash. It trades about -0.14 of its total potential returns per unit of risk. Bitcoin Cash is currently generating about -0.08 per unit of volatility. If you would invest 43,367 in Bitcoin Cash on December 30, 2024 and sell it today you would lose (13,132) from holding Bitcoin Cash or give up 30.28% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Tensor vs. Bitcoin Cash
Performance |
Timeline |
Tensor |
Bitcoin Cash |
Tensor and Bitcoin Cash Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Tensor and Bitcoin Cash
The main advantage of trading using opposite Tensor and Bitcoin Cash positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Tensor position performs unexpectedly, Bitcoin Cash 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 Bitcoin Cash will offset losses from the drop in Bitcoin Cash's long position.The idea behind Tensor and Bitcoin Cash 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.Bitcoin Cash vs. Bitcoin Gold | Bitcoin Cash vs. Bitcoin SV | Bitcoin Cash vs. Staked Ether | Bitcoin Cash vs. Phala Network |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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