Correlation Between KLA Tencor and Teradyne
Can any of the company-specific risk be diversified away by investing in both KLA Tencor and Teradyne 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 KLA Tencor and Teradyne into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between KLA Tencor and Teradyne, you can compare the effects of market volatilities on KLA Tencor and Teradyne 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 KLA Tencor with a short position of Teradyne. Check out your portfolio center. Please also check ongoing floating volatility patterns of KLA Tencor and Teradyne.
Diversification Opportunities for KLA Tencor and Teradyne
0.88 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between KLA and Teradyne is 0.88. Overlapping area represents the amount of risk that can be diversified away by holding KLA Tencor and Teradyne in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Teradyne and KLA Tencor 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 KLA Tencor are associated (or correlated) with Teradyne. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Teradyne has no effect on the direction of KLA Tencor i.e., KLA Tencor and Teradyne go up and down completely randomly.
Pair Corralation between KLA Tencor and Teradyne
Given the investment horizon of 90 days KLA Tencor is expected to under-perform the Teradyne. In addition to that, KLA Tencor is 1.01 times more volatile than Teradyne. It trades about -0.11 of its total potential returns per unit of risk. Teradyne is currently generating about -0.06 per unit of volatility. If you would invest 11,133 in Teradyne on August 27, 2024 and sell it today you would lose (312.00) from holding Teradyne or give up 2.8% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
KLA Tencor vs. Teradyne
Performance |
| Timeline |
| KLA Tencor |
| Teradyne |
KLA Tencor and Teradyne Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with KLA Tencor and Teradyne
The main advantage of trading using opposite KLA Tencor and Teradyne positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if KLA Tencor position performs unexpectedly, Teradyne 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 Teradyne will offset losses from the drop in Teradyne's long position.The idea behind KLA Tencor and Teradyne 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.| Teradyne vs. IPG Photonics | Teradyne vs. Ultra Clean Holdings | Teradyne vs. Onto Innovation | Teradyne vs. Cohu Inc |
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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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