Correlation Between Gold Ent and New Generation
Can any of the company-specific risk be diversified away by investing in both Gold Ent and New Generation 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 Gold Ent and New Generation into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Gold Ent Group and New Generation Consumer, you can compare the effects of market volatilities on Gold Ent and New Generation 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 Gold Ent with a short position of New Generation. Check out your portfolio center. Please also check ongoing floating volatility patterns of Gold Ent and New Generation.
Diversification Opportunities for Gold Ent and New Generation
0.18 | Correlation Coefficient |
Average diversification
The 3 months correlation between Gold and New is 0.18. Overlapping area represents the amount of risk that can be diversified away by holding Gold Ent Group and New Generation Consumer in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on New Generation Consumer and Gold Ent 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 Gold Ent Group are associated (or correlated) with New Generation. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of New Generation Consumer has no effect on the direction of Gold Ent i.e., Gold Ent and New Generation go up and down completely randomly.
Pair Corralation between Gold Ent and New Generation
Given the investment horizon of 90 days Gold Ent Group is expected to generate 2.53 times more return on investment than New Generation. However, Gold Ent is 2.53 times more volatile than New Generation Consumer. It trades about 0.18 of its potential returns per unit of risk. New Generation Consumer is currently generating about 0.04 per unit of risk. If you would invest 0.01 in Gold Ent Group on September 17, 2024 and sell it today you would earn a total of 0.01 from holding Gold Ent Group or generate 100.0% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 98.46% |
Values | Daily Returns |
Gold Ent Group vs. New Generation Consumer
Performance |
Timeline |
Gold Ent Group |
New Generation Consumer |
Gold Ent and New Generation Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Gold Ent and New Generation
The main advantage of trading using opposite Gold Ent and New Generation positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Gold Ent position performs unexpectedly, New Generation 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 New Generation will offset losses from the drop in New Generation's long position.Gold Ent vs. Green Planet Bio | Gold Ent vs. Azure Holding Group | Gold Ent vs. Four Leaf Acquisition | Gold Ent vs. Opus Magnum Ameris |
New Generation vs. Xtra Energy Corp | New Generation vs. Arsenal Digital Holdings | New Generation vs. UHF Logistics Group | New Generation vs. XCana Petroleum |
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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