Correlation Between GAMESTOP and ULTRA CLEAN
Can any of the company-specific risk be diversified away by investing in both GAMESTOP and ULTRA CLEAN 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 GAMESTOP and ULTRA CLEAN into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between GAMESTOP and ULTRA CLEAN HLDGS, you can compare the effects of market volatilities on GAMESTOP and ULTRA CLEAN 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 GAMESTOP with a short position of ULTRA CLEAN. Check out your portfolio center. Please also check ongoing floating volatility patterns of GAMESTOP and ULTRA CLEAN.
Diversification Opportunities for GAMESTOP and ULTRA CLEAN
0.33 | Correlation Coefficient |
Weak diversification
The 3 months correlation between GAMESTOP and ULTRA is 0.33. Overlapping area represents the amount of risk that can be diversified away by holding GAMESTOP and ULTRA CLEAN HLDGS in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on ULTRA CLEAN HLDGS and GAMESTOP 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 GAMESTOP are associated (or correlated) with ULTRA CLEAN. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of ULTRA CLEAN HLDGS has no effect on the direction of GAMESTOP i.e., GAMESTOP and ULTRA CLEAN go up and down completely randomly.
Pair Corralation between GAMESTOP and ULTRA CLEAN
Assuming the 90 days trading horizon GAMESTOP is expected to generate 1.54 times more return on investment than ULTRA CLEAN. However, GAMESTOP is 1.54 times more volatile than ULTRA CLEAN HLDGS. It trades about 0.35 of its potential returns per unit of risk. ULTRA CLEAN HLDGS is currently generating about 0.31 per unit of risk. If you would invest 2,028 in GAMESTOP on September 1, 2024 and sell it today you would earn a total of 674.00 from holding GAMESTOP or generate 33.23% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
GAMESTOP vs. ULTRA CLEAN HLDGS
Performance |
| Timeline |
| GAMESTOP |
| ULTRA CLEAN HLDGS |
GAMESTOP and ULTRA CLEAN Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with GAMESTOP and ULTRA CLEAN
The main advantage of trading using opposite GAMESTOP and ULTRA CLEAN positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GAMESTOP position performs unexpectedly, ULTRA CLEAN 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 ULTRA CLEAN will offset losses from the drop in ULTRA CLEAN's long position.| GAMESTOP vs. SIVERS SEMICONDUCTORS AB | GAMESTOP vs. Darden Restaurants | GAMESTOP vs. Reliance Steel Aluminum | GAMESTOP vs. Q2M Managementberatung AG |
| ULTRA CLEAN vs. DEVRY EDUCATION GRP | ULTRA CLEAN vs. WILLIS LEASE FIN | ULTRA CLEAN vs. G8 EDUCATION | ULTRA CLEAN vs. Grand Canyon Education |
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 Idea Breakdown module to analyze constituents of all Macroaxis ideas. Macroaxis investment ideas are predefined, sector-focused investing themes.
Other Complementary Tools
| Portfolio Volatility Check portfolio volatility and analyze historical return density to properly model market risk | |
| Price Transformation Use Price Transformation models to analyze the depth of different equity instruments across global markets | |
| Stock Tickers Use high-impact, comprehensive, and customizable stock tickers that can be easily integrated to any websites | |
| Pair Correlation Compare performance and examine fundamental relationship between any two equity instruments | |
| Watchlist Optimization Optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm |