Correlation Between Xiaomi and Sony Group
Can any of the company-specific risk be diversified away by investing in both Xiaomi and Sony Group 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 Xiaomi and Sony Group into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Xiaomi and Sony Group Corp, you can compare the effects of market volatilities on Xiaomi and Sony Group 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 Xiaomi with a short position of Sony Group. Check out your portfolio center. Please also check ongoing floating volatility patterns of Xiaomi and Sony Group.
Diversification Opportunities for Xiaomi and Sony Group
-0.45 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Xiaomi and Sony is -0.45. Overlapping area represents the amount of risk that can be diversified away by holding Xiaomi and Sony Group Corp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Sony Group Corp and Xiaomi 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 Xiaomi are associated (or correlated) with Sony Group. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Sony Group Corp has no effect on the direction of Xiaomi i.e., Xiaomi and Sony Group go up and down completely randomly.
Pair Corralation between Xiaomi and Sony Group
Assuming the 90 days horizon Xiaomi is expected to generate 1.18 times more return on investment than Sony Group. However, Xiaomi is 1.18 times more volatile than Sony Group Corp. It trades about 0.05 of its potential returns per unit of risk. Sony Group Corp is currently generating about -0.02 per unit of risk. If you would invest 572.00 in Xiaomi on May 7, 2025 and sell it today you would earn a total of 31.00 from holding Xiaomi or generate 5.42% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Xiaomi vs. Sony Group Corp
Performance |
Timeline |
Xiaomi |
Sony Group Corp |
Xiaomi and Sony Group Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Xiaomi and Sony Group
The main advantage of trading using opposite Xiaomi and Sony Group positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Xiaomi position performs unexpectedly, Sony Group 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 Sony Group will offset losses from the drop in Sony Group's long position.The idea behind Xiaomi and Sony Group Corp 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.Sony Group vs. SBM OFFSHORE | Sony Group vs. GOLDGROUP MINING INC | Sony Group vs. Ringmetall SE | Sony Group vs. Stag Industrial |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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