Correlation Between Catalyst Metals and Hansen Technologies
Can any of the company-specific risk be diversified away by investing in both Catalyst Metals and Hansen Technologies 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 Catalyst Metals and Hansen Technologies into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Catalyst Metals and Hansen Technologies, you can compare the effects of market volatilities on Catalyst Metals and Hansen Technologies 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 Catalyst Metals with a short position of Hansen Technologies. Check out your portfolio center. Please also check ongoing floating volatility patterns of Catalyst Metals and Hansen Technologies.
Diversification Opportunities for Catalyst Metals and Hansen Technologies
-0.21 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Catalyst and Hansen is -0.21. Overlapping area represents the amount of risk that can be diversified away by holding Catalyst Metals and Hansen Technologies in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hansen Technologies and Catalyst Metals 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 Catalyst Metals are associated (or correlated) with Hansen Technologies. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hansen Technologies has no effect on the direction of Catalyst Metals i.e., Catalyst Metals and Hansen Technologies go up and down completely randomly.
Pair Corralation between Catalyst Metals and Hansen Technologies
Assuming the 90 days trading horizon Catalyst Metals is expected to generate 2.76 times more return on investment than Hansen Technologies. However, Catalyst Metals is 2.76 times more volatile than Hansen Technologies. It trades about 0.06 of its potential returns per unit of risk. Hansen Technologies is currently generating about 0.02 per unit of risk. If you would invest 115.00 in Catalyst Metals on September 19, 2024 and sell it today you would earn a total of 155.00 from holding Catalyst Metals or generate 134.78% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 99.8% |
Values | Daily Returns |
Catalyst Metals vs. Hansen Technologies
Performance |
Timeline |
Catalyst Metals |
Hansen Technologies |
Catalyst Metals and Hansen Technologies Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Catalyst Metals and Hansen Technologies
The main advantage of trading using opposite Catalyst Metals and Hansen Technologies positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Catalyst Metals position performs unexpectedly, Hansen Technologies 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 Hansen Technologies will offset losses from the drop in Hansen Technologies' long position.Catalyst Metals vs. Northern Star Resources | Catalyst Metals vs. Bluescope Steel | Catalyst Metals vs. Sandfire Resources NL | Catalyst Metals vs. De Grey Mining |
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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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