Correlation Between Basic Materials and Budapest

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

Diversification Opportunities for Basic Materials and Budapest

0.44
  Correlation Coefficient

Very weak diversification

The 3 months correlation between Basic and Budapest is 0.44. Overlapping area represents the amount of risk that can be diversified away by holding Basic Materials and Budapest SE in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Budapest SE and Basic Materials 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 Basic Materials are associated (or correlated) with Budapest. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Budapest SE has no effect on the direction of Basic Materials i.e., Basic Materials and Budapest go up and down completely randomly.
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Pair Corralation between Basic Materials and Budapest

Assuming the 90 days trading horizon Basic Materials is expected to generate 5.85 times less return on investment than Budapest. In addition to that, Basic Materials is 1.27 times more volatile than Budapest SE. It trades about 0.01 of its total potential returns per unit of risk. Budapest SE is currently generating about 0.1 per unit of volatility. If you would invest  4,092,935  in Budapest SE on January 31, 2024 and sell it today you would earn a total of  2,695,657  from holding Budapest SE or generate 65.86% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthWeak
Accuracy98.99%
ValuesDaily Returns

Basic Materials  vs.  Budapest SE

 Performance 
       Timeline  

Basic Materials and Budapest Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with Basic Materials and Budapest

The main advantage of trading using opposite Basic Materials and Budapest positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Basic Materials position performs unexpectedly, Budapest 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 Budapest will offset losses from the drop in Budapest's long position.
The idea behind Basic Materials and Budapest SE 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 Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.

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