Correlation Between SK Telecom and Pure Storage,
Can any of the company-specific risk be diversified away by investing in both SK Telecom and Pure Storage, 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 SK Telecom and Pure Storage, into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between SK Telecom Co, and Pure Storage,, you can compare the effects of market volatilities on SK Telecom and Pure Storage, 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 SK Telecom with a short position of Pure Storage,. Check out your portfolio center. Please also check ongoing floating volatility patterns of SK Telecom and Pure Storage,.
Diversification Opportunities for SK Telecom and Pure Storage,
-0.34 | Correlation Coefficient |
Very good diversification
The 3 months correlation between S1KM34 and Pure is -0.34. Overlapping area represents the amount of risk that can be diversified away by holding SK Telecom Co, and Pure Storage, in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Pure Storage, and SK Telecom 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 SK Telecom Co, are associated (or correlated) with Pure Storage,. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Pure Storage, has no effect on the direction of SK Telecom i.e., SK Telecom and Pure Storage, go up and down completely randomly.
Pair Corralation between SK Telecom and Pure Storage,
Assuming the 90 days trading horizon SK Telecom Co, is expected to under-perform the Pure Storage,. But the stock apears to be less risky and, when comparing its historical volatility, SK Telecom Co, is 2.26 times less risky than Pure Storage,. The stock trades about -0.03 of its potential returns per unit of risk. The Pure Storage, is currently generating about 0.14 of returns per unit of risk over similar time horizon. If you would invest 7,420 in Pure Storage, on November 6, 2024 and sell it today you would earn a total of 2,720 from holding Pure Storage, or generate 36.66% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
SK Telecom Co, vs. Pure Storage,
Performance |
| Timeline |
| SK Telecom Co, |
| Pure Storage, |
SK Telecom and Pure Storage, Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with SK Telecom and Pure Storage,
The main advantage of trading using opposite SK Telecom and Pure Storage, positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SK Telecom position performs unexpectedly, Pure Storage, 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 Pure Storage, will offset losses from the drop in Pure Storage,'s long position.| SK Telecom vs. Taiwan Semiconductor Manufacturing | SK Telecom vs. Apple Inc | SK Telecom vs. Alibaba Group Holding | SK Telecom vs. Microsoft |
| Pure Storage, vs. Taiwan Semiconductor Manufacturing | Pure Storage, vs. Apple Inc | Pure Storage, vs. Alibaba Group Holding | Pure Storage, vs. Microsoft |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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