Correlation Between Banco De and Pampa Energia
Can any of the company-specific risk be diversified away by investing in both Banco De and Pampa Energia 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 Banco De and Pampa Energia into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Banco de Valores and Pampa Energia SA, you can compare the effects of market volatilities on Banco De and Pampa Energia 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 Banco De with a short position of Pampa Energia. Check out your portfolio center. Please also check ongoing floating volatility patterns of Banco De and Pampa Energia.
Diversification Opportunities for Banco De and Pampa Energia
0.61 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Banco and Pampa is 0.61. Overlapping area represents the amount of risk that can be diversified away by holding Banco de Valores and Pampa Energia SA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Pampa Energia SA and Banco De 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 Banco de Valores are associated (or correlated) with Pampa Energia. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Pampa Energia SA has no effect on the direction of Banco De i.e., Banco De and Pampa Energia go up and down completely randomly.
Pair Corralation between Banco De and Pampa Energia
Assuming the 90 days trading horizon Banco de Valores is expected to under-perform the Pampa Energia. But the stock apears to be less risky and, when comparing its historical volatility, Banco de Valores is 3.19 times less risky than Pampa Energia. The stock trades about -0.16 of its potential returns per unit of risk. The Pampa Energia SA is currently generating about -0.02 of returns per unit of risk over similar time horizon. If you would invest 438,500 in Pampa Energia SA on November 2, 2024 and sell it today you would lose (10,500) from holding Pampa Energia SA or give up 2.39% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 95.45% |
| Values | Daily Returns |
Banco de Valores vs. Pampa Energia SA
Performance |
| Timeline |
| Banco de Valores |
| Pampa Energia SA |
Banco De and Pampa Energia Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Banco De and Pampa Energia
The main advantage of trading using opposite Banco De and Pampa Energia positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Banco De position performs unexpectedly, Pampa Energia 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 Pampa Energia will offset losses from the drop in Pampa Energia's long position.| Banco De vs. Harmony Gold Mining | Banco De vs. Agrometal SAI | Banco De vs. Transportadora de Gas | Banco De vs. Telecom Argentina |
| Pampa Energia vs. Transportadora de Gas | Pampa Energia vs. Compania de Transporte | Pampa Energia vs. United States Steel | Pampa Energia vs. Harmony Gold Mining |
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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