Correlation Between Financials Ultrasector and Ing Senior
Can any of the company-specific risk be diversified away by investing in both Financials Ultrasector and Ing Senior 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 Financials Ultrasector and Ing Senior into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Financials Ultrasector Profund and Ing Senior Incm, you can compare the effects of market volatilities on Financials Ultrasector and Ing Senior 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 Financials Ultrasector with a short position of Ing Senior. Check out your portfolio center. Please also check ongoing floating volatility patterns of Financials Ultrasector and Ing Senior.
Diversification Opportunities for Financials Ultrasector and Ing Senior
0.62 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Financials and Ing is 0.62. Overlapping area represents the amount of risk that can be diversified away by holding Financials Ultrasector Profund and Ing Senior Incm in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ing Senior Incm and Financials Ultrasector 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 Financials Ultrasector Profund are associated (or correlated) with Ing Senior. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ing Senior Incm has no effect on the direction of Financials Ultrasector i.e., Financials Ultrasector and Ing Senior go up and down completely randomly.
Pair Corralation between Financials Ultrasector and Ing Senior
Assuming the 90 days horizon Financials Ultrasector Profund is expected to under-perform the Ing Senior. In addition to that, Financials Ultrasector is 11.63 times more volatile than Ing Senior Incm. It trades about -0.16 of its total potential returns per unit of risk. Ing Senior Incm is currently generating about -0.37 per unit of volatility. If you would invest 969.00 in Ing Senior Incm on October 15, 2024 and sell it today you would lose (9.00) from holding Ing Senior Incm or give up 0.93% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Financials Ultrasector Profund vs. Ing Senior Incm
Performance |
Timeline |
Financials Ultrasector |
Ing Senior Incm |
Financials Ultrasector and Ing Senior Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Financials Ultrasector and Ing Senior
The main advantage of trading using opposite Financials Ultrasector and Ing Senior positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Financials Ultrasector position performs unexpectedly, Ing Senior 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 Ing Senior will offset losses from the drop in Ing Senior's long position.Financials Ultrasector vs. Tiaa Cref Inflation Link | Financials Ultrasector vs. Atac Inflation Rotation | Financials Ultrasector vs. Ab Bond Inflation | Financials Ultrasector vs. Short Duration Inflation |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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