Correlation Between Lam Research and Advantest
Can any of the company-specific risk be diversified away by investing in both Lam Research and Advantest 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 Lam Research and Advantest into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Lam Research Corp and Advantest, you can compare the effects of market volatilities on Lam Research and Advantest 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 Lam Research with a short position of Advantest. Check out your portfolio center. Please also check ongoing floating volatility patterns of Lam Research and Advantest.
Diversification Opportunities for Lam Research and Advantest
-0.56 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Lam and Advantest is -0.56. Overlapping area represents the amount of risk that can be diversified away by holding Lam Research Corp and Advantest in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Advantest and Lam Research 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 Lam Research Corp are associated (or correlated) with Advantest. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Advantest has no effect on the direction of Lam Research i.e., Lam Research and Advantest go up and down completely randomly.
Pair Corralation between Lam Research and Advantest
Given the investment horizon of 90 days Lam Research is expected to generate 18.3 times less return on investment than Advantest. But when comparing it to its historical volatility, Lam Research Corp is 1.27 times less risky than Advantest. It trades about 0.02 of its potential returns per unit of risk. Advantest is currently generating about 0.28 of returns per unit of risk over similar time horizon. If you would invest 5,104 in Advantest on August 24, 2024 and sell it today you would earn a total of 1,146 from holding Advantest or generate 22.45% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Lam Research Corp vs. Advantest
Performance |
| Timeline |
| Lam Research Corp |
| Advantest |
Lam Research and Advantest Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Lam Research and Advantest
The main advantage of trading using opposite Lam Research and Advantest positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Lam Research position performs unexpectedly, Advantest 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 Advantest will offset losses from the drop in Advantest's long position.| Lam Research vs. ASML Holding NV | Lam Research vs. KLA Tencor | Lam Research vs. Axcelis Technologies | Lam Research vs. Teradyne |
| Advantest vs. ASML Holding NV | Advantest vs. ASML Holding NV | Advantest vs. Applied Materials | Advantest vs. Lam Research Corp |
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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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