Correlation Between Hyster-Yale Materials and SIVERS SEMICONDUCTORS

Specify exactly 2 symbols:
Can any of the company-specific risk be diversified away by investing in both Hyster-Yale Materials and SIVERS SEMICONDUCTORS 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 Hyster-Yale Materials and SIVERS SEMICONDUCTORS into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Hyster Yale Materials Handling and SIVERS SEMICONDUCTORS AB, you can compare the effects of market volatilities on Hyster-Yale Materials and SIVERS SEMICONDUCTORS 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 Hyster-Yale Materials with a short position of SIVERS SEMICONDUCTORS. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hyster-Yale Materials and SIVERS SEMICONDUCTORS.

Diversification Opportunities for Hyster-Yale Materials and SIVERS SEMICONDUCTORS

0.31
  Correlation Coefficient

Weak diversification

The 3 months correlation between Hyster-Yale and SIVERS is 0.31. Overlapping area represents the amount of risk that can be diversified away by holding Hyster Yale Materials Handling and SIVERS SEMICONDUCTORS AB in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SIVERS SEMICONDUCTORS and Hyster-Yale Materials 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 Hyster Yale Materials Handling are associated (or correlated) with SIVERS SEMICONDUCTORS. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SIVERS SEMICONDUCTORS has no effect on the direction of Hyster-Yale Materials i.e., Hyster-Yale Materials and SIVERS SEMICONDUCTORS go up and down completely randomly.

Pair Corralation between Hyster-Yale Materials and SIVERS SEMICONDUCTORS

Assuming the 90 days trading horizon Hyster Yale Materials Handling is expected to generate 0.38 times more return on investment than SIVERS SEMICONDUCTORS. However, Hyster Yale Materials Handling is 2.66 times less risky than SIVERS SEMICONDUCTORS. It trades about -0.03 of its potential returns per unit of risk. SIVERS SEMICONDUCTORS AB is currently generating about -0.11 per unit of risk. If you would invest  5,762  in Hyster Yale Materials Handling on September 2, 2024 and sell it today you would lose (512.00) from holding Hyster Yale Materials Handling or give up 8.89% of portfolio value over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthVery Weak
Accuracy100.0%
ValuesDaily Returns

Hyster Yale Materials Handling  vs.  SIVERS SEMICONDUCTORS AB

 Performance 
       Timeline  
Hyster Yale Materials 

Risk-Adjusted Performance

0 of 100

 
Weak
 
Strong
Very Weak
Over the last 90 days Hyster Yale Materials Handling has generated negative risk-adjusted returns adding no value to investors with long positions. Despite nearly stable technical and fundamental indicators, Hyster-Yale Materials is not utilizing all of its potentials. The newest stock price disturbance, may contribute to mid-run losses for the stockholders.
SIVERS SEMICONDUCTORS 

Risk-Adjusted Performance

0 of 100

 
Weak
 
Strong
Very Weak
Over the last 90 days SIVERS SEMICONDUCTORS AB has generated negative risk-adjusted returns adding no value to investors with long positions. Despite fragile performance in the last few months, the Stock's basic indicators remain nearly stable which may send shares a bit higher in January 2025. The current disturbance may also be a sign of long-run up-swing for the company stockholders.

Hyster-Yale Materials and SIVERS SEMICONDUCTORS Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with Hyster-Yale Materials and SIVERS SEMICONDUCTORS

The main advantage of trading using opposite Hyster-Yale Materials and SIVERS SEMICONDUCTORS positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hyster-Yale Materials position performs unexpectedly, SIVERS SEMICONDUCTORS 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 SIVERS SEMICONDUCTORS will offset losses from the drop in SIVERS SEMICONDUCTORS's long position.
The idea behind Hyster Yale Materials Handling and SIVERS SEMICONDUCTORS AB 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.
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 Analyzer module to portfolio analysis module that provides access to portfolio diagnostics and optimization engine.

Other Complementary Tools

FinTech Suite
Use AI to screen and filter profitable investment opportunities
Premium Stories
Follow Macroaxis premium stories from verified contributors across different equity types, categories and coverage scope
Bollinger Bands
Use Bollinger Bands indicator to analyze target price for a given investing horizon
Volatility Analysis
Get historical volatility and risk analysis based on latest market data
Portfolio Rebalancing
Analyze risk-adjusted returns against different time horizons to find asset-allocation targets