Correlation Between KARRAT and PING

Can any of the company-specific risk be diversified away by investing in both KARRAT and PING 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 KARRAT and PING into the same portfolio, which is an essential part of the fundamental portfolio management process.

By analyzing existing cross correlation between KARRAT and PING, you can compare the effects of market volatilities on KARRAT and PING 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 KARRAT with a short position of PING. Check out your portfolio center. Please also check ongoing floating volatility patterns of KARRAT and PING.

Diversification Opportunities for KARRAT and PING

-0.14

Correlation Coefficient

KARRAT  PING

Good diversification

The 3 months correlation between KARRAT and PING is -0.14. Overlapping area represents the amount of risk that can be diversified away by holding KARRAT and PING in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PING and KARRAT 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 KARRAT are associated (or correlated) with PING. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PING has no effect on the direction of KARRAT i.e., KARRAT and PING go up and down completely randomly.

Pair Corralation between KARRAT and PING

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 Against
Strength	Insignificant
Accuracy	1.54%
Values	Daily Returns

KARRAT  vs.  PING

KARRAT

Risk-Adjusted Performance

7 of 100

OK

Compared to the overall equity markets, risk-adjusted returns on investments in KARRAT are ranked lower than 7 (%) of all global equities and portfolios over the last 90 days. Despite somewhat unsteady basic indicators, KARRAT sustained solid returns over the last few months and may actually be approaching a breakup point.

PING

Risk-Adjusted Performance

0 of 100

Very Weak

Over the last 90 days PING has generated negative risk-adjusted returns adding no value to investors with long positions. In spite of rather sound fundamental indicators, PING is not utilizing all of its potentials. The latest stock price tumult, may contribute to shorter-term losses for the shareholders.

Pair Trading with KARRAT and PING

The main advantage of trading using opposite KARRAT and PING positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if KARRAT position performs unexpectedly, PING 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 PING will offset losses from the drop in PING's long position.

The idea behind KARRAT and PING 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.

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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.