Correlation Between Ford and Scynexis
Can any of the company-specific risk be diversified away by investing in both Ford and Scynexis 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 Ford and Scynexis into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ford Motor and Scynexis, you can compare the effects of market volatilities on Ford and Scynexis 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 Ford with a short position of Scynexis. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ford and Scynexis.
Diversification Opportunities for Ford and Scynexis
Very good diversification
The 3 months correlation between Ford and Scynexis is -0.26. Overlapping area represents the amount of risk that can be diversified away by holding Ford Motor and Scynexis in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Scynexis and Ford 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 Ford Motor are associated (or correlated) with Scynexis. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Scynexis has no effect on the direction of Ford i.e., Ford and Scynexis go up and down completely randomly.
Pair Corralation between Ford and Scynexis
Taking into account the 90-day investment horizon Ford Motor is expected to generate 0.59 times more return on investment than Scynexis. However, Ford Motor is 1.7 times less risky than Scynexis. It trades about 0.02 of its potential returns per unit of risk. Scynexis is currently generating about 0.0 per unit of risk. If you would invest 1,063 in Ford Motor on September 5, 2024 and sell it today you would earn a total of 19.00 from holding Ford Motor or generate 1.79% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Ford Motor vs. Scynexis
Performance |
Timeline |
Ford Motor |
Scynexis |
Ford and Scynexis Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Ford and Scynexis
The main advantage of trading using opposite Ford and Scynexis positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ford position performs unexpectedly, Scynexis 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 Scynexis will offset losses from the drop in Scynexis' long position.The idea behind Ford Motor and Scynexis pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.Scynexis vs. Crinetics Pharmaceuticals | Scynexis vs. Enanta Pharmaceuticals | Scynexis vs. Amicus Therapeutics | Scynexis vs. Connect Biopharma 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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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