Correlation Between Bank of New York and Asure Software
Can any of the company-specific risk be diversified away by investing in both Bank of New York and Asure Software 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 Bank of New York and Asure Software into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bank of New and Asure Software, you can compare the effects of market volatilities on Bank of New York and Asure Software 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 Bank of New York with a short position of Asure Software. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of New York and Asure Software.
Diversification Opportunities for Bank of New York and Asure Software
0.4 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Bank and Asure is 0.4. Overlapping area represents the amount of risk that can be diversified away by holding Bank of New and Asure Software in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Asure Software and Bank of New York 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 Bank of New are associated (or correlated) with Asure Software. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Asure Software has no effect on the direction of Bank of New York i.e., Bank of New York and Asure Software go up and down completely randomly.
Pair Corralation between Bank of New York and Asure Software
Allowing for the 90-day total investment horizon Bank of New is expected to generate 0.39 times more return on investment than Asure Software. However, Bank of New is 2.56 times less risky than Asure Software. It trades about 0.2 of its potential returns per unit of risk. Asure Software is currently generating about 0.05 per unit of risk. If you would invest 4,815 in Bank of New on September 4, 2024 and sell it today you would earn a total of 3,296 from holding Bank of New or generate 68.45% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Bank of New vs. Asure Software
Performance |
| Timeline |
| Bank of New York |
| Asure Software |
Bank of New York and Asure Software Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bank of New York and Asure Software
The main advantage of trading using opposite Bank of New York and Asure Software positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of New York position performs unexpectedly, Asure Software 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 Asure Software will offset losses from the drop in Asure Software's long position.| Bank of New York vs. Northern Trust | Bank of New York vs. Invesco Plc | Bank of New York vs. Franklin Resources | Bank of New York vs. T Rowe Price |
| Asure Software vs. Alkami Technology | Asure Software vs. Blackbaud | Asure Software vs. Enfusion | Asure Software vs. Clearwater Analytics Holdings |
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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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