Correlation Between POCC and KARRAT
Can any of the company-specific risk be diversified away by investing in both POCC and KARRAT 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 POCC and KARRAT into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between POCC and KARRAT, you can compare the effects of market volatilities on POCC and KARRAT 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 POCC with a short position of KARRAT. Check out your portfolio center. Please also check ongoing floating volatility patterns of POCC and KARRAT.
Diversification Opportunities for POCC and KARRAT
Weak diversification
The 3 months correlation between POCC and KARRAT is 0.36. Overlapping area represents the amount of risk that can be diversified away by holding POCC and KARRAT in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on KARRAT and POCC 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 POCC are associated (or correlated) with KARRAT. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of KARRAT has no effect on the direction of POCC i.e., POCC and KARRAT go up and down completely randomly.
Pair Corralation between POCC and KARRAT
Assuming the 90 days trading horizon POCC is expected to generate 2.33 times less return on investment than KARRAT. But when comparing it to its historical volatility, POCC is 4.32 times less risky than KARRAT. It trades about 0.18 of its potential returns per unit of risk. KARRAT is currently generating about 0.1 of returns per unit of risk over similar time horizon. If you would invest 31.00 in KARRAT on September 1, 2024 and sell it today you would earn a total of 18.00 from holding KARRAT or generate 58.06% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
POCC vs. KARRAT
Performance |
Timeline |
POCC |
KARRAT |
POCC and KARRAT Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with POCC and KARRAT
The main advantage of trading using opposite POCC and KARRAT positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if POCC position performs unexpectedly, KARRAT 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 KARRAT will offset losses from the drop in KARRAT's long position.The idea behind POCC and KARRAT 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.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 Transaction History module to view history of all your transactions and understand their impact on performance.
Other Complementary Tools
Bonds Directory Find actively traded corporate debentures issued by US companies | |
Fundamentals Comparison Compare fundamentals across multiple equities to find investing opportunities | |
Equity Forecasting Use basic forecasting models to generate price predictions and determine price momentum | |
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 | |
Fundamental Analysis View fundamental data based on most recent published financial statements |