Correlation Between DAX Index and PennyMac Financial

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

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

Diversification Opportunities for DAX Index and PennyMac Financial

0.37

Correlation Coefficient

DAX Index  PennyMac Financial

Weak diversification

The 3 months correlation between DAX and PennyMac is 0.37. Overlapping area represents the amount of risk that can be diversified away by holding DAX Index and PennyMac Financial Services in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PennyMac Financial and DAX Index 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 DAX Index are associated (or correlated) with PennyMac Financial. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PennyMac Financial has no effect on the direction of DAX Index i.e., DAX Index and PennyMac Financial go up and down completely randomly.

Pair Corralation between DAX Index and PennyMac Financial

Assuming the 90 days trading horizon DAX Index is expected to generate 0.39 times more return on investment than PennyMac Financial. However, DAX Index is 2.57 times less risky than PennyMac Financial. It trades about 0.09 of its potential returns per unit of risk. PennyMac Financial Services is currently generating about 0.02 per unit of risk. If you would invest  1,910,410  in DAX Index on October 7, 2024 and sell it today you would earn a total of  80,198  from holding DAX Index or generate 4.2% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Very Weak
Accuracy	100.0%
Values	Daily Returns

DAX Index  vs.  PennyMac Financial Services

Pair Trading with DAX Index and PennyMac Financial

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

The idea behind DAX Index and PennyMac Financial Services 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.