Correlation Between BITM and MLN

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

Diversification Opportunities for BITM and MLN

-0.23
  Correlation Coefficient

Very good diversification

The 3 months correlation between BITM and MLN is -0.23. Overlapping area represents the amount of risk that can be diversified away by holding BITM and MLN in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on MLN and BITM 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 BITM are associated (or correlated) with MLN. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of MLN has no effect on the direction of BITM i.e., BITM and MLN go up and down completely randomly.

Pair Corralation between BITM and MLN

If you would invest  0.00  in BITM on September 1, 2024 and sell it today you would earn a total of  0.00  from holding BITM or generate 0.0% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Against 
StrengthInsignificant
Accuracy0.76%
ValuesDaily Returns

BITM  vs.  MLN

 Performance 
       Timeline  
BITM 

Risk-Adjusted Performance

0 of 100

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

Risk-Adjusted Performance

8 of 100

 
Weak
 
Strong
OK
Compared to the overall equity markets, risk-adjusted returns on investments in MLN are ranked lower than 8 (%) of all global equities and portfolios over the last 90 days. In spite of rather unsteady basic indicators, MLN exhibited solid returns over the last few months and may actually be approaching a breakup point.

BITM and MLN Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with BITM and MLN

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

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