Correlation Between Financial and Olympia Financial
Can any of the company-specific risk be diversified away by investing in both Financial and Olympia Financial 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 Financial and Olympia Financial into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Financial 15 Split and Olympia Financial Group, you can compare the effects of market volatilities on Financial and Olympia Financial 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 Financial with a short position of Olympia Financial. Check out your portfolio center. Please also check ongoing floating volatility patterns of Financial and Olympia Financial.
Diversification Opportunities for Financial and Olympia Financial
0.74 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Financial and Olympia is 0.74. Overlapping area represents the amount of risk that can be diversified away by holding Financial 15 Split and Olympia Financial Group in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Olympia Financial and Financial 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 Financial 15 Split are associated (or correlated) with Olympia Financial. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Olympia Financial has no effect on the direction of Financial i.e., Financial and Olympia Financial go up and down completely randomly.
Pair Corralation between Financial and Olympia Financial
Assuming the 90 days trading horizon Financial is expected to generate 1.66 times less return on investment than Olympia Financial. But when comparing it to its historical volatility, Financial 15 Split is 4.71 times less risky than Olympia Financial. It trades about 0.29 of its potential returns per unit of risk. Olympia Financial Group is currently generating about 0.1 of returns per unit of risk over similar time horizon. If you would invest 9,828 in Olympia Financial Group on September 21, 2024 and sell it today you would earn a total of 772.00 from holding Olympia Financial Group or generate 7.86% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Financial 15 Split vs. Olympia Financial Group
Performance |
Timeline |
Financial 15 Split |
Olympia Financial |
Financial and Olympia Financial Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Financial and Olympia Financial
The main advantage of trading using opposite Financial and Olympia Financial positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Financial position performs unexpectedly, Olympia Financial 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 Olympia Financial will offset losses from the drop in Olympia Financial's long position.Financial vs. GOLDMAN SACHS CDR | Financial vs. Galaxy Digital Holdings | Financial vs. Hut 8 Mining | Financial vs. Bitfarms |
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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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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