Correlation Between FRONT and BTT

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

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

Diversification Opportunities for FRONT and BTT

0.0

Correlation Coefficient

FRONT  BTT

Pay attention - limited upside

The 3 months correlation between FRONT and BTT is 0.0. Overlapping area represents the amount of risk that can be diversified away by holding FRONT and BTT in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BTT and FRONT 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 FRONT are associated (or correlated) with BTT. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of BTT has no effect on the direction of FRONT i.e., FRONT and BTT go up and down completely randomly.

Pair Corralation between FRONT and BTT

If you would invest  73.00  in FRONT on September 1, 2024 and sell it today you would lose (6.00) from holding FRONT or give up 8.22% of portfolio value over 90 days.

Time Period	3 Months [change]
Direction	Flat
Strength	Insignificant
Accuracy	100.0%
Values	Daily Returns

FRONT  vs.  BTT

FRONT

Risk-Adjusted Performance

6 of 100

Modest

Compared to the overall equity markets, risk-adjusted returns on investments in FRONT are ranked lower than 6 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady fundamental indicators, FRONT exhibited solid returns over the last few months and may actually be approaching a breakup point.

BTT

Risk-Adjusted Performance

0 of 100

Very Weak

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

Pair Trading with FRONT and BTT

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

The idea behind FRONT and BTT 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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.