Correlation Between MWAT and Flare

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

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

Diversification Opportunities for MWAT and Flare

0.33

Correlation Coefficient

MWAT  Flare

Weak diversification

The 3 months correlation between MWAT and Flare is 0.33. Overlapping area represents the amount of risk that can be diversified away by holding MWAT and Flare in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Flare and MWAT 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 MWAT are associated (or correlated) with Flare. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Flare has no effect on the direction of MWAT i.e., MWAT and Flare go up and down completely randomly.

Pair Corralation between MWAT and Flare

If you would invest  1.52  in Flare on September 1, 2024 and sell it today you would earn a total of  1.23  from holding Flare or generate 80.92% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Very Weak
Accuracy	1.54%
Values	Daily Returns

MWAT  vs.  Flare

MWAT

Risk-Adjusted Performance

0 of 100

Very Weak

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

Flare

Risk-Adjusted Performance

13 of 100

Good

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

Pair Trading with MWAT and Flare

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

The idea behind MWAT and Flare 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 Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.