Correlation Between Jasmine Telecom and Phatra Leasing
Can any of the company-specific risk be diversified away by investing in both Jasmine Telecom and Phatra Leasing 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 Jasmine Telecom and Phatra Leasing into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Jasmine Telecom Systems and Phatra Leasing Public, you can compare the effects of market volatilities on Jasmine Telecom and Phatra Leasing 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 Jasmine Telecom with a short position of Phatra Leasing. Check out your portfolio center. Please also check ongoing floating volatility patterns of Jasmine Telecom and Phatra Leasing.
Diversification Opportunities for Jasmine Telecom and Phatra Leasing
0.86 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Jasmine and Phatra is 0.86. Overlapping area represents the amount of risk that can be diversified away by holding Jasmine Telecom Systems and Phatra Leasing Public in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Phatra Leasing Public and Jasmine Telecom 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 Jasmine Telecom Systems are associated (or correlated) with Phatra Leasing. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Phatra Leasing Public has no effect on the direction of Jasmine Telecom i.e., Jasmine Telecom and Phatra Leasing go up and down completely randomly.
Pair Corralation between Jasmine Telecom and Phatra Leasing
Assuming the 90 days trading horizon Jasmine Telecom Systems is expected to generate 1.99 times more return on investment than Phatra Leasing. However, Jasmine Telecom is 1.99 times more volatile than Phatra Leasing Public. It trades about -0.11 of its potential returns per unit of risk. Phatra Leasing Public is currently generating about -0.35 per unit of risk. If you would invest 6,900 in Jasmine Telecom Systems on October 9, 2024 and sell it today you would lose (425.00) from holding Jasmine Telecom Systems or give up 6.16% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Jasmine Telecom Systems vs. Phatra Leasing Public
Performance |
Timeline |
Jasmine Telecom Systems |
Phatra Leasing Public |
Jasmine Telecom and Phatra Leasing Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Jasmine Telecom and Phatra Leasing
The main advantage of trading using opposite Jasmine Telecom and Phatra Leasing positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Jasmine Telecom position performs unexpectedly, Phatra Leasing 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 Phatra Leasing will offset losses from the drop in Phatra Leasing's long position.Jasmine Telecom vs. Jay Mart Public | Jasmine Telecom vs. Jasmine International Public | Jasmine Telecom vs. KCE Electronics Public | Jasmine Telecom vs. Delta Electronics Public |
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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 Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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