Correlation Between Firan Technology and GOLDMAN SACHS
Can any of the company-specific risk be diversified away by investing in both Firan Technology and GOLDMAN SACHS 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 Firan Technology and GOLDMAN SACHS into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Firan Technology Group and GOLDMAN SACHS CDR, you can compare the effects of market volatilities on Firan Technology and GOLDMAN SACHS 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 Firan Technology with a short position of GOLDMAN SACHS. Check out your portfolio center. Please also check ongoing floating volatility patterns of Firan Technology and GOLDMAN SACHS.
Diversification Opportunities for Firan Technology and GOLDMAN SACHS
0.88 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Firan and GOLDMAN is 0.88. Overlapping area represents the amount of risk that can be diversified away by holding Firan Technology Group and GOLDMAN SACHS CDR in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on GOLDMAN SACHS CDR and Firan Technology 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 Firan Technology Group are associated (or correlated) with GOLDMAN SACHS. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of GOLDMAN SACHS CDR has no effect on the direction of Firan Technology i.e., Firan Technology and GOLDMAN SACHS go up and down completely randomly.
Pair Corralation between Firan Technology and GOLDMAN SACHS
Assuming the 90 days trading horizon Firan Technology is expected to generate 1.11 times less return on investment than GOLDMAN SACHS. But when comparing it to its historical volatility, Firan Technology Group is 1.1 times less risky than GOLDMAN SACHS. It trades about 0.17 of its potential returns per unit of risk. GOLDMAN SACHS CDR is currently generating about 0.17 of returns per unit of risk over similar time horizon. If you would invest 2,442 in GOLDMAN SACHS CDR on September 2, 2024 and sell it today you would earn a total of 609.00 from holding GOLDMAN SACHS CDR or generate 24.94% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Firan Technology Group vs. GOLDMAN SACHS CDR
Performance |
Timeline |
Firan Technology |
GOLDMAN SACHS CDR |
Firan Technology and GOLDMAN SACHS Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Firan Technology and GOLDMAN SACHS
The main advantage of trading using opposite Firan Technology and GOLDMAN SACHS positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Firan Technology position performs unexpectedly, GOLDMAN SACHS 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 GOLDMAN SACHS will offset losses from the drop in GOLDMAN SACHS's long position.Firan Technology vs. Hammond Power Solutions | Firan Technology vs. Questor Technology | Firan Technology vs. Vecima Networks | Firan Technology vs. Magellan Aerospace |
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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 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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