Correlation Between Modine Manufacturing and NET Power
Can any of the company-specific risk be diversified away by investing in both Modine Manufacturing and NET Power 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 Modine Manufacturing and NET Power into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Modine Manufacturing and NET Power, you can compare the effects of market volatilities on Modine Manufacturing and NET Power 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 Modine Manufacturing with a short position of NET Power. Check out your portfolio center. Please also check ongoing floating volatility patterns of Modine Manufacturing and NET Power.
Diversification Opportunities for Modine Manufacturing and NET Power
0.31 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Modine and NET is 0.31. Overlapping area represents the amount of risk that can be diversified away by holding Modine Manufacturing and NET Power in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on NET Power and Modine Manufacturing 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 Modine Manufacturing are associated (or correlated) with NET Power. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of NET Power has no effect on the direction of Modine Manufacturing i.e., Modine Manufacturing and NET Power go up and down completely randomly.
Pair Corralation between Modine Manufacturing and NET Power
Considering the 90-day investment horizon Modine Manufacturing is expected to generate 0.9 times more return on investment than NET Power. However, Modine Manufacturing is 1.11 times less risky than NET Power. It trades about 0.03 of its potential returns per unit of risk. NET Power is currently generating about -0.23 per unit of risk. If you would invest 12,729 in Modine Manufacturing on September 14, 2024 and sell it today you would earn a total of 93.00 from holding Modine Manufacturing or generate 0.73% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Modine Manufacturing vs. NET Power
Performance |
| Timeline |
| Modine Manufacturing |
| NET Power |
Modine Manufacturing and NET Power Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Modine Manufacturing and NET Power
The main advantage of trading using opposite Modine Manufacturing and NET Power positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Modine Manufacturing position performs unexpectedly, NET Power 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 NET Power will offset losses from the drop in NET Power's long position.| Modine Manufacturing vs. Ford Motor | Modine Manufacturing vs. General Motors | Modine Manufacturing vs. Goodyear Tire Rubber | Modine Manufacturing vs. Li Auto |
| NET Power vs. Summit Materials | NET Power vs. Modine Manufacturing | NET Power vs. Getty Copper | NET Power vs. Li Auto |
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 Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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