Correlation Between K2 Asset and Argo Investments
Can any of the company-specific risk be diversified away by investing in both K2 Asset and Argo Investments 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 K2 Asset and Argo Investments into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between K2 Asset Management and Argo Investments, you can compare the effects of market volatilities on K2 Asset and Argo Investments 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 K2 Asset with a short position of Argo Investments. Check out your portfolio center. Please also check ongoing floating volatility patterns of K2 Asset and Argo Investments.
Diversification Opportunities for K2 Asset and Argo Investments
0.86 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between KAM and Argo is 0.86. Overlapping area represents the amount of risk that can be diversified away by holding K2 Asset Management and Argo Investments in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Argo Investments and K2 Asset 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 K2 Asset Management are associated (or correlated) with Argo Investments. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Argo Investments has no effect on the direction of K2 Asset i.e., K2 Asset and Argo Investments go up and down completely randomly.
Pair Corralation between K2 Asset and Argo Investments
Assuming the 90 days trading horizon K2 Asset Management is expected to generate 11.4 times more return on investment than Argo Investments. However, K2 Asset is 11.4 times more volatile than Argo Investments. It trades about 0.08 of its potential returns per unit of risk. Argo Investments is currently generating about 0.1 per unit of risk. If you would invest 4.70 in K2 Asset Management on September 2, 2024 and sell it today you would earn a total of 2.30 from holding K2 Asset Management or generate 48.94% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
K2 Asset Management vs. Argo Investments
Performance |
| Timeline |
| K2 Asset Management |
| Argo Investments |
K2 Asset and Argo Investments Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with K2 Asset and Argo Investments
The main advantage of trading using opposite K2 Asset and Argo Investments positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if K2 Asset position performs unexpectedly, Argo Investments 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 Argo Investments will offset losses from the drop in Argo Investments' long position.| K2 Asset vs. WA1 Resources | K2 Asset vs. Predictive Discovery | K2 Asset vs. Cooper Metals | K2 Asset vs. OD6 Metals |
| Argo Investments vs. WA1 Resources | Argo Investments vs. Predictive Discovery | Argo Investments vs. Cooper Metals | Argo Investments vs. OD6 Metals |
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 Correlation Analysis module to reduce portfolio risk simply by holding instruments which are not perfectly correlated.
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