Correlation Between Shopify and Where Food

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

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

Diversification Opportunities for Shopify and Where Food

0.33

Correlation Coefficient

Shopify  Where Food

Weak diversification

The 3 months correlation between Shopify and Where is 0.33. Overlapping area represents the amount of risk that can be diversified away by holding Shopify and Where Food Comes in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Where Food Comes and Shopify 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 Shopify are associated (or correlated) with Where Food. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Where Food Comes has no effect on the direction of Shopify i.e., Shopify and Where Food go up and down completely randomly.

Pair Corralation between Shopify and Where Food

Given the investment horizon of 90 days Shopify is expected to generate 1.26 times more return on investment than Where Food. However, Shopify is 1.26 times more volatile than Where Food Comes. It trades about -0.03 of its potential returns per unit of risk. Where Food Comes is currently generating about -0.05 per unit of risk. If you would invest  10,669  in Shopify on December 29, 2024 and sell it today you would lose (1,001) from holding Shopify or give up 9.38% of portfolio value over 90 days.

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

Shopify  vs.  Where Food Comes

Shopify

Risk-Adjusted Performance

Very Weak

Over the last 90 days Shopify has generated negative risk-adjusted returns adding no value to investors with long positions. Even with latest unfluctuating performance, the Stock's basic indicators remain invariable and the latest agitation on Wall Street may also be a sign of long-running gains for the enterprise retail investors.

Where Food Comes

Risk-Adjusted Performance

Very Weak

Over the last 90 days Where Food Comes has generated negative risk-adjusted returns adding no value to investors with long positions. Despite latest weak performance, the Stock's fundamental indicators remain stable and the current disturbance on Wall Street may also be a sign of long-run gains for the company stockholders.

Pair Trading with Shopify and Where Food

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

The idea behind Shopify and Where Food Comes 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 Price Exposure Probability module to analyze equity upside and downside potential for a given time horizon across multiple markets.