Correlation Between Apple and LION ONE
Can any of the company-specific risk be diversified away by investing in both Apple and LION ONE 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 Apple and LION ONE into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Apple Inc and LION ONE METALS, you can compare the effects of market volatilities on Apple and LION ONE 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 Apple with a short position of LION ONE. Check out your portfolio center. Please also check ongoing floating volatility patterns of Apple and LION ONE.
Diversification Opportunities for Apple and LION ONE
Very weak diversification
The 3 months correlation between Apple and LION is 0.45. Overlapping area represents the amount of risk that can be diversified away by holding Apple Inc and LION ONE METALS in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on LION ONE METALS and Apple 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 Apple Inc are associated (or correlated) with LION ONE. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of LION ONE METALS has no effect on the direction of Apple i.e., Apple and LION ONE go up and down completely randomly.
Pair Corralation between Apple and LION ONE
Assuming the 90 days trading horizon Apple Inc is expected to generate 0.37 times more return on investment than LION ONE. However, Apple Inc is 2.69 times less risky than LION ONE. It trades about 0.08 of its potential returns per unit of risk. LION ONE METALS is currently generating about -0.03 per unit of risk. If you would invest 13,212 in Apple Inc on August 28, 2024 and sell it today you would earn a total of 8,728 from holding Apple Inc or generate 66.06% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Apple Inc vs. LION ONE METALS
Performance |
| Timeline |
| Apple Inc |
| LION ONE METALS |
Apple and LION ONE Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Apple and LION ONE
The main advantage of trading using opposite Apple and LION ONE positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Apple position performs unexpectedly, LION ONE 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 LION ONE will offset losses from the drop in LION ONE's long position.The idea behind Apple Inc and LION ONE METALS 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.| LION ONE vs. Austevoll Seafood ASA | LION ONE vs. TreeHouse Foods | LION ONE vs. National Retail Properties | LION ONE vs. AIR PRODCHEMICALS |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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