Correlation Between Microsoft and KIM KINDEX
Can any of the company-specific risk be diversified away by investing in both Microsoft and KIM KINDEX 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 Microsoft and KIM KINDEX into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Microsoft and KIM KINDEX Japan, you can compare the effects of market volatilities on Microsoft and KIM KINDEX 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 Microsoft with a short position of KIM KINDEX. Check out your portfolio center. Please also check ongoing floating volatility patterns of Microsoft and KIM KINDEX.
Diversification Opportunities for Microsoft and KIM KINDEX
0.32 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Microsoft and KIM is 0.32. Overlapping area represents the amount of risk that can be diversified away by holding Microsoft and KIM KINDEX Japan in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on KIM KINDEX Japan and Microsoft 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 Microsoft are associated (or correlated) with KIM KINDEX. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of KIM KINDEX Japan has no effect on the direction of Microsoft i.e., Microsoft and KIM KINDEX go up and down completely randomly.
Pair Corralation between Microsoft and KIM KINDEX
Given the investment horizon of 90 days Microsoft is expected to under-perform the KIM KINDEX. In addition to that, Microsoft is 1.07 times more volatile than KIM KINDEX Japan. It trades about -0.29 of its total potential returns per unit of risk. KIM KINDEX Japan is currently generating about -0.07 per unit of volatility. If you would invest 2,827,000 in KIM KINDEX Japan on October 13, 2024 and sell it today you would lose (42,000) from holding KIM KINDEX Japan or give up 1.49% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 95.0% |
Values | Daily Returns |
Microsoft vs. KIM KINDEX Japan
Performance |
Timeline |
Microsoft |
KIM KINDEX Japan |
Microsoft and KIM KINDEX Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Microsoft and KIM KINDEX
The main advantage of trading using opposite Microsoft and KIM KINDEX positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Microsoft position performs unexpectedly, KIM KINDEX 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 KIM KINDEX will offset losses from the drop in KIM KINDEX's long position.Microsoft vs. Palo Alto Networks | Microsoft vs. Uipath Inc | Microsoft vs. Block Inc | Microsoft vs. Adobe Systems Incorporated |
KIM KINDEX vs. KIM KINDEX Treasury | KIM KINDEX vs. KIM KINDEX 200 | KIM KINDEX vs. KIM KINDEX KOSPI | KIM KINDEX vs. KIM KINDEX Vietnam |
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 Comparator module to compare the composition, asset allocations and performance of any two portfolios in your account.
Other Complementary Tools
ETF Categories List of ETF categories grouped based on various criteria, such as the investment strategy or type of investments | |
Pattern Recognition Use different Pattern Recognition models to time the market across multiple global exchanges | |
Alpha Finder Use alpha and beta coefficients to find investment opportunities after accounting for the risk | |
My Watchlist Analysis Analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like | |
Crypto Correlations Use cryptocurrency correlation module to diversify your cryptocurrency portfolio across multiple coins |