Correlation Between NYSE Composite and Oxford Lane
Can any of the company-specific risk be diversified away by investing in both NYSE Composite and Oxford Lane 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 NYSE Composite and Oxford Lane into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NYSE Composite and Oxford Lane Capital, you can compare the effects of market volatilities on NYSE Composite and Oxford Lane 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 NYSE Composite with a short position of Oxford Lane. Check out your portfolio center. Please also check ongoing floating volatility patterns of NYSE Composite and Oxford Lane.
Diversification Opportunities for NYSE Composite and Oxford Lane
0.37 | Correlation Coefficient |
Weak diversification
The 3 months correlation between NYSE and Oxford is 0.37. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and Oxford Lane Capital in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Oxford Lane Capital and NYSE Composite 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 NYSE Composite are associated (or correlated) with Oxford Lane. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Oxford Lane Capital has no effect on the direction of NYSE Composite i.e., NYSE Composite and Oxford Lane go up and down completely randomly.
Pair Corralation between NYSE Composite and Oxford Lane
Assuming the 90 days trading horizon NYSE Composite is expected to under-perform the Oxford Lane. In addition to that, NYSE Composite is 3.43 times more volatile than Oxford Lane Capital. It trades about -0.24 of its total potential returns per unit of risk. Oxford Lane Capital is currently generating about 0.28 per unit of volatility. If you would invest 2,341 in Oxford Lane Capital on September 19, 2024 and sell it today you would earn a total of 30.50 from holding Oxford Lane Capital or generate 1.3% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
NYSE Composite vs. Oxford Lane Capital
Performance |
Timeline |
NYSE Composite and Oxford Lane Volatility Contrast
Predicted Return Density |
Returns |
NYSE Composite
Pair trading matchups for NYSE Composite
Oxford Lane Capital
Pair trading matchups for Oxford Lane
Pair Trading with NYSE Composite and Oxford Lane
The main advantage of trading using opposite NYSE Composite and Oxford Lane positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NYSE Composite position performs unexpectedly, Oxford Lane 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 Oxford Lane will offset losses from the drop in Oxford Lane's long position.NYSE Composite vs. Relx PLC ADR | NYSE Composite vs. Century Aluminum | NYSE Composite vs. Udemy Inc | NYSE Composite vs. Blue Moon Metals |
Oxford Lane vs. Oxford Lane Capital | Oxford Lane vs. Oxford Lane Capital | Oxford Lane vs. Eagle Point Credit | Oxford Lane vs. Eagle Point Credit |
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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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