Correlation Between Forum Energy and KLX Energy
Can any of the company-specific risk be diversified away by investing in both Forum Energy and KLX Energy 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 Forum Energy and KLX Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Forum Energy Technologies and KLX Energy Services, you can compare the effects of market volatilities on Forum Energy and KLX Energy 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 Forum Energy with a short position of KLX Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Forum Energy and KLX Energy.
Diversification Opportunities for Forum Energy and KLX Energy
0.67 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Forum and KLX is 0.67. Overlapping area represents the amount of risk that can be diversified away by holding Forum Energy Technologies and KLX Energy Services in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on KLX Energy Services and Forum Energy 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 Forum Energy Technologies are associated (or correlated) with KLX Energy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of KLX Energy Services has no effect on the direction of Forum Energy i.e., Forum Energy and KLX Energy go up and down completely randomly.
Pair Corralation between Forum Energy and KLX Energy
Considering the 90-day investment horizon Forum Energy Technologies is expected to generate 0.88 times more return on investment than KLX Energy. However, Forum Energy Technologies is 1.14 times less risky than KLX Energy. It trades about -0.03 of its potential returns per unit of risk. KLX Energy Services is currently generating about -0.43 per unit of risk. If you would invest 1,516 in Forum Energy Technologies on September 24, 2024 and sell it today you would lose (40.00) from holding Forum Energy Technologies or give up 2.64% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Forum Energy Technologies vs. KLX Energy Services
Performance |
Timeline |
Forum Energy Technologies |
KLX Energy Services |
Forum Energy and KLX Energy Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Forum Energy and KLX Energy
The main advantage of trading using opposite Forum Energy and KLX Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Forum Energy position performs unexpectedly, KLX Energy 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 KLX Energy will offset losses from the drop in KLX Energy's long position.Forum Energy vs. Oceaneering International | Forum Energy vs. Valaris | Forum Energy vs. Geospace Technologies | Forum Energy vs. Liberty Oilfield Services |
KLX Energy vs. Oceaneering International | KLX Energy vs. Valaris | KLX Energy vs. Geospace Technologies | KLX Energy vs. Liberty Oilfield Services |
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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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