Correlation Between JAR and DATA

Specify exactly 2 symbols:
Can any of the company-specific risk be diversified away by investing in both JAR and DATA 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 JAR and DATA into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between JAR and DATA, you can compare the effects of market volatilities on JAR and DATA 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 JAR with a short position of DATA. Check out your portfolio center. Please also check ongoing floating volatility patterns of JAR and DATA.

Diversification Opportunities for JAR and DATA

0.02
  Correlation Coefficient

Significant diversification

The 3 months correlation between JAR and DATA is 0.02. Overlapping area represents the amount of risk that can be diversified away by holding JAR and DATA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on DATA and JAR 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 JAR are associated (or correlated) with DATA. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of DATA has no effect on the direction of JAR i.e., JAR and DATA go up and down completely randomly.

Pair Corralation between JAR and DATA

Assuming the 90 days trading horizon JAR is expected to generate 1.15 times more return on investment than DATA. However, JAR is 1.15 times more volatile than DATA. It trades about 0.25 of its potential returns per unit of risk. DATA is currently generating about 0.23 per unit of risk. If you would invest  0.27  in JAR on August 25, 2024 and sell it today you would earn a total of  0.08  from holding JAR or generate 30.0% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthInsignificant
Accuracy100.0%
ValuesDaily Returns

JAR  vs.  DATA

 Performance 
       Timeline  
JAR 

Risk-Adjusted Performance

13 of 100

 
Weak
 
Strong
Good
Compared to the overall equity markets, risk-adjusted returns on investments in JAR are ranked lower than 13 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady basic indicators, JAR exhibited solid returns over the last few months and may actually be approaching a breakup point.
DATA 

Risk-Adjusted Performance

4 of 100

 
Weak
 
Strong
Insignificant
Compared to the overall equity markets, risk-adjusted returns on investments in DATA are ranked lower than 4 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady fundamental indicators, DATA exhibited solid returns over the last few months and may actually be approaching a breakup point.

JAR and DATA Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with JAR and DATA

The main advantage of trading using opposite JAR and DATA positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if JAR position performs unexpectedly, DATA 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 DATA will offset losses from the drop in DATA's long position.
The idea behind JAR and DATA 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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.

Other Complementary Tools

Risk-Return Analysis
View associations between returns expected from investment and the risk you assume
Insider Screener
Find insiders across different sectors to evaluate their impact on performance
Aroon Oscillator
Analyze current equity momentum using Aroon Oscillator and other momentum ratios
Bollinger Bands
Use Bollinger Bands indicator to analyze target price for a given investing horizon
Equity Forecasting
Use basic forecasting models to generate price predictions and determine price momentum