Correlation Between Cars and LB Foster
Can any of the company-specific risk be diversified away by investing in both Cars and LB Foster 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 Cars and LB Foster into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Cars Inc and LB Foster, you can compare the effects of market volatilities on Cars and LB Foster 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 Cars with a short position of LB Foster. Check out your portfolio center. Please also check ongoing floating volatility patterns of Cars and LB Foster.
Diversification Opportunities for Cars and LB Foster
Very poor diversification
The 3 months correlation between Cars and FSTR is 0.86. Overlapping area represents the amount of risk that can be diversified away by holding Cars Inc and LB Foster in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on LB Foster and Cars 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 Cars Inc are associated (or correlated) with LB Foster. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of LB Foster has no effect on the direction of Cars i.e., Cars and LB Foster go up and down completely randomly.
Pair Corralation between Cars and LB Foster
Given the investment horizon of 90 days Cars Inc is expected to under-perform the LB Foster. But the stock apears to be less risky and, when comparing its historical volatility, Cars Inc is 1.43 times less risky than LB Foster. The stock trades about 0.0 of its potential returns per unit of risk. The LB Foster is currently generating about 0.04 of returns per unit of risk over similar time horizon. If you would invest 2,199 in LB Foster on September 24, 2024 and sell it today you would earn a total of 440.00 from holding LB Foster or generate 20.01% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Cars Inc vs. LB Foster
Performance |
Timeline |
Cars Inc |
LB Foster |
Cars and LB Foster Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Cars and LB Foster
The main advantage of trading using opposite Cars and LB Foster positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Cars position performs unexpectedly, LB Foster 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 LB Foster will offset losses from the drop in LB Foster's long position.The idea behind Cars Inc and LB Foster pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.LB Foster vs. Steel Partners Holdings | LB Foster vs. Brookfield Business Partners | LB Foster vs. Griffon | LB Foster vs. Tejon Ranch Co |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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