Correlation Between Small-cap Value and Applied Finance
Can any of the company-specific risk be diversified away by investing in both Small-cap Value and Applied Finance 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 Small-cap Value and Applied Finance into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Small Cap Value Fund and Applied Finance Explorer, you can compare the effects of market volatilities on Small-cap Value and Applied Finance 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 Small-cap Value with a short position of Applied Finance. Check out your portfolio center. Please also check ongoing floating volatility patterns of Small-cap Value and Applied Finance.
Diversification Opportunities for Small-cap Value and Applied Finance
0.97 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Small-cap and Applied is 0.97. Overlapping area represents the amount of risk that can be diversified away by holding Small Cap Value Fund and Applied Finance Explorer in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Applied Finance Explorer and Small-cap Value 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 Small Cap Value Fund are associated (or correlated) with Applied Finance. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Applied Finance Explorer has no effect on the direction of Small-cap Value i.e., Small-cap Value and Applied Finance go up and down completely randomly.
Pair Corralation between Small-cap Value and Applied Finance
Assuming the 90 days horizon Small Cap Value Fund is expected to under-perform the Applied Finance. In addition to that, Small-cap Value is 1.29 times more volatile than Applied Finance Explorer. It trades about -0.04 of its total potential returns per unit of risk. Applied Finance Explorer is currently generating about 0.0 per unit of volatility. If you would invest 2,267 in Applied Finance Explorer on October 21, 2024 and sell it today you would lose (12.00) from holding Applied Finance Explorer or give up 0.53% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Small Cap Value Fund vs. Applied Finance Explorer
Performance |
Timeline |
Small Cap Value |
Applied Finance Explorer |
Small-cap Value and Applied Finance Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Small-cap Value and Applied Finance
The main advantage of trading using opposite Small-cap Value and Applied Finance positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Small-cap Value position performs unexpectedly, Applied Finance 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 Applied Finance will offset losses from the drop in Applied Finance's long position.Small-cap Value vs. Franklin Government Money | Small-cap Value vs. Cref Money Market | Small-cap Value vs. Ab Government Exchange | Small-cap Value vs. Schwab Government Money |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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