Correlation Between FS Energy and Bank of New York
Can any of the company-specific risk be diversified away by investing in both FS Energy and Bank of New York 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 FS Energy and Bank of New York into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between FS Energy and and Bank of New, you can compare the effects of market volatilities on FS Energy and Bank of New York 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 FS Energy with a short position of Bank of New York. Check out your portfolio center. Please also check ongoing floating volatility patterns of FS Energy and Bank of New York.
Diversification Opportunities for FS Energy and Bank of New York
0.48 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between FSEN and Bank is 0.48. Overlapping area represents the amount of risk that can be diversified away by holding FS Energy and and Bank of New in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bank of New York and FS Energy 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 FS Energy and are associated (or correlated) with Bank of New York. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bank of New York has no effect on the direction of FS Energy i.e., FS Energy and Bank of New York go up and down completely randomly.
Pair Corralation between FS Energy and Bank of New York
Given the investment horizon of 90 days FS Energy is expected to generate 1.19 times less return on investment than Bank of New York. In addition to that, FS Energy is 4.2 times more volatile than Bank of New. It trades about 0.03 of its total potential returns per unit of risk. Bank of New is currently generating about 0.16 per unit of volatility. If you would invest 4,179 in Bank of New on August 31, 2024 and sell it today you would earn a total of 4,008 from holding Bank of New or generate 95.91% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 99.73% |
Values | Daily Returns |
FS Energy and vs. Bank of New
Performance |
Timeline |
FS Energy |
Bank of New York |
FS Energy and Bank of New York Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with FS Energy and Bank of New York
The main advantage of trading using opposite FS Energy and Bank of New York positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if FS Energy position performs unexpectedly, Bank of New York 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 Bank of New York will offset losses from the drop in Bank of New York's long position.FS Energy vs. Business Development Corp | FS Energy vs. Inpex Corp ADR | FS Energy vs. Daikin IndustriesLtd |
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 |
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 Comparator module to compare the composition, asset allocations and performance of any two portfolios in your account.
Other Complementary Tools
Crypto Correlations Use cryptocurrency correlation module to diversify your cryptocurrency portfolio across multiple coins | |
Piotroski F Score Get Piotroski F Score based on the binary analysis strategy of nine different fundamentals | |
Portfolio Backtesting Avoid under-diversification and over-optimization by backtesting your portfolios | |
Volatility Analysis Get historical volatility and risk analysis based on latest market data | |
Sectors List of equity sectors categorizing publicly traded companies based on their primary business activities |