Correlation Between Sharing Economy and Looking Glass
Can any of the company-specific risk be diversified away by investing in both Sharing Economy and Looking Glass 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 Sharing Economy and Looking Glass into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Sharing Economy International and Looking Glass Labs, you can compare the effects of market volatilities on Sharing Economy and Looking Glass 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 Sharing Economy with a short position of Looking Glass. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sharing Economy and Looking Glass.
Diversification Opportunities for Sharing Economy and Looking Glass
0.2 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Sharing and Looking is 0.2. Overlapping area represents the amount of risk that can be diversified away by holding Sharing Economy International and Looking Glass Labs in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Looking Glass Labs and Sharing Economy 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 Sharing Economy International are associated (or correlated) with Looking Glass. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Looking Glass Labs has no effect on the direction of Sharing Economy i.e., Sharing Economy and Looking Glass go up and down completely randomly.
Pair Corralation between Sharing Economy and Looking Glass
If you would invest 2.19 in Looking Glass Labs on September 15, 2024 and sell it today you would earn a total of 0.00 from holding Looking Glass Labs or generate 0.0% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Sharing Economy International vs. Looking Glass Labs
Performance |
Timeline |
Sharing Economy Inte |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
Looking Glass Labs |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
Sharing Economy and Looking Glass Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Sharing Economy and Looking Glass
The main advantage of trading using opposite Sharing Economy and Looking Glass positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sharing Economy position performs unexpectedly, Looking Glass 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 Looking Glass will offset losses from the drop in Looking Glass' long position.Sharing Economy vs. Fuse Science | Sharing Economy vs. Data443 Risk Mitigation | Sharing Economy vs. Smartmetric | Sharing Economy vs. Taoping |
Looking Glass vs. Fuse Science | Looking Glass vs. Data Call Technologi | Looking Glass vs. Rightscorp | Looking Glass vs. Alarum Technologies |
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 Idea Optimizer module to use advanced portfolio builder with pre-computed micro ideas to build optimal portfolio .
Other Complementary Tools
Equity Forecasting Use basic forecasting models to generate price predictions and determine price momentum | |
Portfolio Volatility Check portfolio volatility and analyze historical return density to properly model market risk | |
Watchlist Optimization Optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm | |
Portfolio Rebalancing Analyze risk-adjusted returns against different time horizons to find asset-allocation targets | |
Investing Opportunities Build portfolios using our predefined set of ideas and optimize them against your investing preferences |