Correlation Between Maple Leaf and GelStat Corp
Can any of the company-specific risk be diversified away by investing in both Maple Leaf and GelStat Corp 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 Maple Leaf and GelStat Corp into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Maple Leaf Green and GelStat Corp, you can compare the effects of market volatilities on Maple Leaf and GelStat Corp 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 Maple Leaf with a short position of GelStat Corp. Check out your portfolio center. Please also check ongoing floating volatility patterns of Maple Leaf and GelStat Corp.
Diversification Opportunities for Maple Leaf and GelStat Corp
0.1 | Correlation Coefficient |
Average diversification
The 3 months correlation between Maple and GelStat is 0.1. Overlapping area represents the amount of risk that can be diversified away by holding Maple Leaf Green and GelStat Corp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on GelStat Corp and Maple Leaf 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 Maple Leaf Green are associated (or correlated) with GelStat Corp. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of GelStat Corp has no effect on the direction of Maple Leaf i.e., Maple Leaf and GelStat Corp go up and down completely randomly.
Pair Corralation between Maple Leaf and GelStat Corp
Assuming the 90 days horizon Maple Leaf Green is expected to generate 1.04 times more return on investment than GelStat Corp. However, Maple Leaf is 1.04 times more volatile than GelStat Corp. It trades about 0.07 of its potential returns per unit of risk. GelStat Corp is currently generating about 0.07 per unit of risk. If you would invest 4.10 in Maple Leaf Green on November 19, 2024 and sell it today you would lose (1.40) from holding Maple Leaf Green or give up 34.15% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 99.6% |
Values | Daily Returns |
Maple Leaf Green vs. GelStat Corp
Performance |
Timeline |
Maple Leaf Green |
GelStat Corp |
Maple Leaf and GelStat Corp Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Maple Leaf and GelStat Corp
The main advantage of trading using opposite Maple Leaf and GelStat Corp positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Maple Leaf position performs unexpectedly, GelStat Corp 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 GelStat Corp will offset losses from the drop in GelStat Corp's long position.Maple Leaf vs. Greater Cannabis | Maple Leaf vs. Global Hemp Group | Maple Leaf vs. Cannabis Suisse Corp | Maple Leaf vs. Mc Endvrs |
GelStat Corp vs. Rimrock Gold Corp | GelStat Corp vs. Emergent Health Corp | GelStat Corp vs. Galexxy Holdings | GelStat Corp vs. Cann American Corp |
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 Money Flow Index module to determine momentum by analyzing Money Flow Index and other technical indicators.
Other Complementary Tools
Pattern Recognition Use different Pattern Recognition models to time the market across multiple global exchanges | |
Watchlist Optimization Optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm | |
Performance Analysis Check effects of mean-variance optimization against your current asset allocation | |
Volatility Analysis Get historical volatility and risk analysis based on latest market data | |
Portfolio Volatility Check portfolio volatility and analyze historical return density to properly model market risk |