Correlation Between Panda Financial and G-bits Network
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By analyzing existing cross correlation between Panda Financial Holding and G bits Network Technology, you can compare the effects of market volatilities on Panda Financial and G-bits Network 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 Panda Financial with a short position of G-bits Network. Check out your portfolio center. Please also check ongoing floating volatility patterns of Panda Financial and G-bits Network.
Diversification Opportunities for Panda Financial and G-bits Network
0.25 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Panda and G-bits is 0.25. Overlapping area represents the amount of risk that can be diversified away by holding Panda Financial Holding and G bits Network Technology in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on G bits Network and Panda Financial 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 Panda Financial Holding are associated (or correlated) with G-bits Network. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of G bits Network has no effect on the direction of Panda Financial i.e., Panda Financial and G-bits Network go up and down completely randomly.
Pair Corralation between Panda Financial and G-bits Network
Assuming the 90 days trading horizon Panda Financial Holding is expected to under-perform the G-bits Network. In addition to that, Panda Financial is 2.28 times more volatile than G bits Network Technology. It trades about -0.35 of its total potential returns per unit of risk. G bits Network Technology is currently generating about -0.02 per unit of volatility. If you would invest 20,728 in G bits Network Technology on November 7, 2024 and sell it today you would lose (78.00) from holding G bits Network Technology or give up 0.38% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Panda Financial Holding vs. G bits Network Technology
Performance |
| Timeline |
| Panda Financial Holding |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
| G bits Network |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
Panda Financial and G-bits Network Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Panda Financial and G-bits Network
The main advantage of trading using opposite Panda Financial and G-bits Network positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Panda Financial position performs unexpectedly, G-bits Network 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 G-bits Network will offset losses from the drop in G-bits Network's long position.The idea behind Panda Financial Holding and G bits Network Technology 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 Price Exposure Probability module to analyze equity upside and downside potential for a given time horizon across multiple markets.
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