Correlation Between PING and LAMB

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

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

Diversification Opportunities for PING and LAMB

-0.57

Correlation Coefficient

PING  LAMB

Excellent diversification

The 3 months correlation between PING and LAMB is -0.57. Overlapping area represents the amount of risk that can be diversified away by holding PING and LAMB in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on LAMB and PING 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 PING are associated (or correlated) with LAMB. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of LAMB has no effect on the direction of PING i.e., PING and LAMB go up and down completely randomly.

Pair Corralation between PING and LAMB

If you would invest  0.19  in LAMB on August 30, 2024 and sell it today you would earn a total of  0.02  from holding LAMB or generate 11.05% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Against
Strength	Very Weak
Accuracy	1.56%
Values	Daily Returns

PING  vs.  LAMB

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.

LAMB

Risk-Adjusted Performance

4 of 100

Insignificant

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

Pair Trading with PING and LAMB

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

The idea behind PING and LAMB 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.