Correlation Between Citi Trends and Where Food
Can any of the company-specific risk be diversified away by investing in both Citi Trends and Where Food 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 Citi Trends and Where Food into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Citi Trends and Where Food Comes, you can compare the effects of market volatilities on Citi Trends and Where Food 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 Citi Trends with a short position of Where Food. Check out your portfolio center. Please also check ongoing floating volatility patterns of Citi Trends and Where Food.
Diversification Opportunities for Citi Trends and Where Food
0.84 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Citi and Where is 0.84. Overlapping area represents the amount of risk that can be diversified away by holding Citi Trends and Where Food Comes in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Where Food Comes and Citi Trends 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 Citi Trends are associated (or correlated) with Where Food. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Where Food Comes has no effect on the direction of Citi Trends i.e., Citi Trends and Where Food go up and down completely randomly.
Pair Corralation between Citi Trends and Where Food
Given the investment horizon of 90 days Citi Trends is expected to generate 1.23 times more return on investment than Where Food. However, Citi Trends is 1.23 times more volatile than Where Food Comes. It trades about 0.03 of its potential returns per unit of risk. Where Food Comes is currently generating about 0.01 per unit of risk. If you would invest 2,367 in Citi Trends on October 5, 2024 and sell it today you would earn a total of 282.00 from holding Citi Trends or generate 11.91% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Citi Trends vs. Where Food Comes
Performance |
Timeline |
Citi Trends |
Where Food Comes |
Citi Trends and Where Food Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Citi Trends and Where Food
The main advantage of trading using opposite Citi Trends and Where Food positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Citi Trends position performs unexpectedly, Where Food 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 Where Food will offset losses from the drop in Where Food's long position.Citi Trends vs. JJill Inc | Citi Trends vs. Zumiez Inc | Citi Trends vs. Tillys Inc | Citi Trends vs. Duluth Holdings |
Where Food vs. Issuer Direct Corp | Where Food vs. Smith Midland Corp | Where Food vs. Bm Technologies | Where Food vs. 1StdibsCom |
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 Crypto Correlations module to use cryptocurrency correlation module to diversify your cryptocurrency portfolio across multiple coins.
Other Complementary Tools
Options Analysis Analyze and evaluate options and option chains as a potential hedge for your portfolios | |
ETF Categories List of ETF categories grouped based on various criteria, such as the investment strategy or type of investments | |
My Watchlist Analysis Analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like | |
Theme Ratings Determine theme ratings based on digital equity recommendations. Macroaxis theme ratings are based on combination of fundamental analysis and risk-adjusted market performance | |
Price Exposure Probability Analyze equity upside and downside potential for a given time horizon across multiple markets |