Correlation Between Integral and BitFuFu
Can any of the company-specific risk be diversified away by investing in both Integral and BitFuFu 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 Integral and BitFuFu into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Integral Ad Science and BitFuFu Class A, you can compare the effects of market volatilities on Integral and BitFuFu 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 Integral with a short position of BitFuFu. Check out your portfolio center. Please also check ongoing floating volatility patterns of Integral and BitFuFu.
Diversification Opportunities for Integral and BitFuFu
Significant diversification
The 3 months correlation between Integral and BitFuFu is 0.05. Overlapping area represents the amount of risk that can be diversified away by holding Integral Ad Science and BitFuFu Class A in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BitFuFu Class A and Integral 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 Integral Ad Science are associated (or correlated) with BitFuFu. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of BitFuFu Class A has no effect on the direction of Integral i.e., Integral and BitFuFu go up and down completely randomly.
Pair Corralation between Integral and BitFuFu
Considering the 90-day investment horizon Integral is expected to generate 1.68 times less return on investment than BitFuFu. But when comparing it to its historical volatility, Integral Ad Science is 2.23 times less risky than BitFuFu. It trades about 0.02 of its potential returns per unit of risk. BitFuFu Class A is currently generating about 0.02 of returns per unit of risk over similar time horizon. If you would invest 1,017 in BitFuFu Class A on October 11, 2024 and sell it today you would lose (479.00) from holding BitFuFu Class A or give up 47.1% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Integral Ad Science vs. BitFuFu Class A
Performance |
Timeline |
Integral Ad Science |
BitFuFu Class A |
Integral and BitFuFu Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Integral and BitFuFu
The main advantage of trading using opposite Integral and BitFuFu positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Integral position performs unexpectedly, BitFuFu 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 BitFuFu will offset losses from the drop in BitFuFu's long position.The idea behind Integral Ad Science and BitFuFu Class A 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.BitFuFu vs. Harmony Gold Mining | BitFuFu vs. Dave Busters Entertainment | BitFuFu vs. Integral Ad Science | BitFuFu vs. Arrow Electronics |
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 Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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