Correlation Between Kaltura and GMS
Can any of the company-specific risk be diversified away by investing in both Kaltura and GMS 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 Kaltura and GMS into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Kaltura and GMS Inc, you can compare the effects of market volatilities on Kaltura and GMS 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 Kaltura with a short position of GMS. Check out your portfolio center. Please also check ongoing floating volatility patterns of Kaltura and GMS.
Diversification Opportunities for Kaltura and GMS
Very poor diversification
The 3 months correlation between Kaltura and GMS is 0.89. Overlapping area represents the amount of risk that can be diversified away by holding Kaltura and GMS Inc in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on GMS Inc and Kaltura 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 Kaltura are associated (or correlated) with GMS. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of GMS Inc has no effect on the direction of Kaltura i.e., Kaltura and GMS go up and down completely randomly.
Pair Corralation between Kaltura and GMS
Given the investment horizon of 90 days Kaltura is expected to generate 2.3 times more return on investment than GMS. However, Kaltura is 2.3 times more volatile than GMS Inc. It trades about 0.04 of its potential returns per unit of risk. GMS Inc is currently generating about 0.09 per unit of risk. If you would invest 179.00 in Kaltura on September 2, 2024 and sell it today you would earn a total of 43.00 from holding Kaltura or generate 24.02% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Kaltura vs. GMS Inc
Performance |
Timeline |
Kaltura |
GMS Inc |
Kaltura and GMS Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Kaltura and GMS
The main advantage of trading using opposite Kaltura and GMS positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Kaltura position performs unexpectedly, GMS 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 GMS will offset losses from the drop in GMS's long position.Kaltura vs. Evertec | Kaltura vs. Consensus Cloud Solutions | Kaltura vs. Global Blue Group | Kaltura vs. Lesaka Technologies |
GMS vs. Quanex Building Products | GMS vs. Apogee Enterprises | GMS vs. Azek Company | GMS vs. Beacon Roofing Supply |
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 Equity Analysis module to research over 250,000 global equities including funds, stocks and ETFs to find investment opportunities.
Other Complementary Tools
Odds Of Bankruptcy Get analysis of equity chance of financial distress in the next 2 years | |
Bonds Directory Find actively traded corporate debentures issued by US companies | |
Volatility Analysis Get historical volatility and risk analysis based on latest market data | |
Idea Optimizer Use advanced portfolio builder with pre-computed micro ideas to build optimal portfolio | |
Equity Valuation Check real value of public entities based on technical and fundamental data |