Correlation Between DATA and Ontology
Can any of the company-specific risk be diversified away by investing in both DATA and Ontology 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 DATA and Ontology into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between DATA and Ontology, you can compare the effects of market volatilities on DATA and Ontology 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 DATA with a short position of Ontology. Check out your portfolio center. Please also check ongoing floating volatility patterns of DATA and Ontology.
Diversification Opportunities for DATA and Ontology
Very poor diversification
The 3 months correlation between DATA and Ontology is 0.81. Overlapping area represents the amount of risk that can be diversified away by holding DATA and Ontology in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ontology and DATA 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 DATA are associated (or correlated) with Ontology. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ontology has no effect on the direction of DATA i.e., DATA and Ontology go up and down completely randomly.
Pair Corralation between DATA and Ontology
Assuming the 90 days trading horizon DATA is expected to generate 1.27 times less return on investment than Ontology. In addition to that, DATA is 1.25 times more volatile than Ontology. It trades about 0.01 of its total potential returns per unit of risk. Ontology is currently generating about 0.02 per unit of volatility. If you would invest 27.00 in Ontology on November 10, 2024 and sell it today you would lose (8.00) from holding Ontology or give up 29.63% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
DATA vs. Ontology
Performance |
| Timeline |
| DATA |
| Ontology |
DATA and Ontology Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with DATA and Ontology
The main advantage of trading using opposite DATA and Ontology positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if DATA position performs unexpectedly, Ontology 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 Ontology will offset losses from the drop in Ontology's long position.The idea behind DATA and Ontology 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 Fundamentals Comparison module to compare fundamentals across multiple equities to find investing opportunities.
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