Correlation Between Capital Engineering and City Steel
Can any of the company-specific risk be diversified away by investing in both Capital Engineering and City Steel 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 Capital Engineering and City Steel into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Capital Engineering Network and City Steel Public, you can compare the effects of market volatilities on Capital Engineering and City Steel 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 Capital Engineering with a short position of City Steel. Check out your portfolio center. Please also check ongoing floating volatility patterns of Capital Engineering and City Steel.
Diversification Opportunities for Capital Engineering and City Steel
0.61 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Capital and City is 0.61. Overlapping area represents the amount of risk that can be diversified away by holding Capital Engineering Network and City Steel Public in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on City Steel Public and Capital Engineering 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 Capital Engineering Network are associated (or correlated) with City Steel. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of City Steel Public has no effect on the direction of Capital Engineering i.e., Capital Engineering and City Steel go up and down completely randomly.
Pair Corralation between Capital Engineering and City Steel
Assuming the 90 days trading horizon Capital Engineering Network is expected to generate 0.19 times more return on investment than City Steel. However, Capital Engineering Network is 5.3 times less risky than City Steel. It trades about 0.0 of its potential returns per unit of risk. City Steel Public is currently generating about -0.2 per unit of risk. If you would invest 200.00 in Capital Engineering Network on September 12, 2024 and sell it today you would earn a total of 0.00 from holding Capital Engineering Network or generate 0.0% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Capital Engineering Network vs. City Steel Public
Performance |
Timeline |
Capital Engineering |
City Steel Public |
Capital Engineering and City Steel Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Capital Engineering and City Steel
The main advantage of trading using opposite Capital Engineering and City Steel positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Capital Engineering position performs unexpectedly, City Steel 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 City Steel will offset losses from the drop in City Steel's long position.Capital Engineering vs. Thantawan Industry Public | Capital Engineering vs. The Erawan Group | Capital Engineering vs. Jay Mart Public | Capital Engineering vs. Airports of Thailand |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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