Correlation Between Fukuyama Transporting and PG E
Can any of the company-specific risk be diversified away by investing in both Fukuyama Transporting and PG E 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 Fukuyama Transporting and PG E into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Fukuyama Transporting Co and PG E P6, you can compare the effects of market volatilities on Fukuyama Transporting and PG E 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 Fukuyama Transporting with a short position of PG E. Check out your portfolio center. Please also check ongoing floating volatility patterns of Fukuyama Transporting and PG E.
Diversification Opportunities for Fukuyama Transporting and PG E
-0.6 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Fukuyama and PCG6 is -0.6. Overlapping area represents the amount of risk that can be diversified away by holding Fukuyama Transporting Co and PG E P6 in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PG E P6 and Fukuyama Transporting 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 Fukuyama Transporting Co are associated (or correlated) with PG E. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PG E P6 has no effect on the direction of Fukuyama Transporting i.e., Fukuyama Transporting and PG E go up and down completely randomly.
Pair Corralation between Fukuyama Transporting and PG E
Assuming the 90 days horizon Fukuyama Transporting Co is expected to generate 1.35 times more return on investment than PG E. However, Fukuyama Transporting is 1.35 times more volatile than PG E P6. It trades about 0.04 of its potential returns per unit of risk. PG E P6 is currently generating about 0.05 per unit of risk. If you would invest 1,612 in Fukuyama Transporting Co on September 14, 2024 and sell it today you would earn a total of 688.00 from holding Fukuyama Transporting Co or generate 42.68% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Fukuyama Transporting Co vs. PG E P6
Performance |
| Timeline |
| Fukuyama Transporting |
| PG E P6 |
Fukuyama Transporting and PG E Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Fukuyama Transporting and PG E
The main advantage of trading using opposite Fukuyama Transporting and PG E positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Fukuyama Transporting position performs unexpectedly, PG E 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 PG E will offset losses from the drop in PG E's long position.| Fukuyama Transporting vs. SCHNEIDER NATLINC CLB | Fukuyama Transporting vs. Superior Plus Corp | Fukuyama Transporting vs. SIVERS SEMICONDUCTORS AB | Fukuyama Transporting vs. NorAm Drilling AS |
| PG E vs. Entravision Communications | PG E vs. Fukuyama Transporting Co | PG E vs. Transport International Holdings | PG E vs. Spirent Communications plc |
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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