Correlation Between Automatic Data and Monks Investment
Can any of the company-specific risk be diversified away by investing in both Automatic Data and Monks Investment 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 Automatic Data and Monks Investment into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Automatic Data Processing and Monks Investment Trust, you can compare the effects of market volatilities on Automatic Data and Monks Investment 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 Automatic Data with a short position of Monks Investment. Check out your portfolio center. Please also check ongoing floating volatility patterns of Automatic Data and Monks Investment.
Diversification Opportunities for Automatic Data and Monks Investment
0.85 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Automatic and Monks is 0.85. Overlapping area represents the amount of risk that can be diversified away by holding Automatic Data Processing and Monks Investment Trust in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Monks Investment Trust and Automatic 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 Automatic Data Processing are associated (or correlated) with Monks Investment. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Monks Investment Trust has no effect on the direction of Automatic Data i.e., Automatic Data and Monks Investment go up and down completely randomly.
Pair Corralation between Automatic Data and Monks Investment
Assuming the 90 days trading horizon Automatic Data Processing is expected to under-perform the Monks Investment. In addition to that, Automatic Data is 1.12 times more volatile than Monks Investment Trust. It trades about -0.14 of its total potential returns per unit of risk. Monks Investment Trust is currently generating about -0.08 per unit of volatility. If you would invest 128,400 in Monks Investment Trust on September 24, 2024 and sell it today you would lose (2,000) from holding Monks Investment Trust or give up 1.56% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 95.45% |
Values | Daily Returns |
Automatic Data Processing vs. Monks Investment Trust
Performance |
Timeline |
Automatic Data Processing |
Monks Investment Trust |
Automatic Data and Monks Investment Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Automatic Data and Monks Investment
The main advantage of trading using opposite Automatic Data and Monks Investment positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Automatic Data position performs unexpectedly, Monks Investment 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 Monks Investment will offset losses from the drop in Monks Investment's long position.Automatic Data vs. Playtech Plc | Automatic Data vs. Metals Exploration Plc | Automatic Data vs. Trainline Plc | Automatic Data vs. Fulcrum Metals PLC |
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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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