Correlation Between UBS AG and ARCA Institutional

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

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

Diversification Opportunities for UBS AG and ARCA Institutional

0.85

Correlation Coefficient

UBS AG  ARCA Institutional

Very poor diversification

The 3 months correlation between UBS and ARCA is 0.85. Overlapping area represents the amount of risk that can be diversified away by holding UBS AG London and ARCA Institutional in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on ARCA Institutional and UBS AG 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 UBS AG London are associated (or correlated) with ARCA Institutional. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of ARCA Institutional has no effect on the direction of UBS AG i.e., UBS AG and ARCA Institutional go up and down completely randomly.

Pair Corralation between UBS AG and ARCA Institutional

Given the investment horizon of 90 days UBS AG London is expected to under-perform the ARCA Institutional. But the etf apears to be less risky and, when comparing its historical volatility, UBS AG London is 1.18 times less risky than ARCA Institutional. The etf trades about -0.01 of its potential returns per unit of risk. The ARCA Institutional is currently generating about 0.21 of returns per unit of risk over similar time horizon. If you would invest  300,683  in ARCA Institutional on September 26, 2024 and sell it today you would earn a total of  12,571  from holding ARCA Institutional or generate 4.18% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Strong
Accuracy	66.67%
Values	Daily Returns

UBS AG London  vs.  ARCA Institutional

Pair Trading with UBS AG and ARCA Institutional

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

The idea behind UBS AG London and ARCA Institutional 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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.