Correlation Between Snowflake and ServiceNow

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

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

Diversification Opportunities for Snowflake and ServiceNow

0.51

Correlation Coefficient

Snowflake  ServiceNow

Very weak diversification

The 3 months correlation between Snowflake and ServiceNow is 0.51. Overlapping area represents the amount of risk that can be diversified away by holding Snowflake and ServiceNow in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on ServiceNow and Snowflake 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 Snowflake are associated (or correlated) with ServiceNow. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of ServiceNow has no effect on the direction of Snowflake i.e., Snowflake and ServiceNow go up and down completely randomly.

Pair Corralation between Snowflake and ServiceNow

Given the investment horizon of 90 days Snowflake is expected to generate 1.15 times more return on investment than ServiceNow. However, Snowflake is 1.15 times more volatile than ServiceNow. It trades about -0.02 of its potential returns per unit of risk. ServiceNow is currently generating about -0.14 per unit of risk. If you would invest  16,052  in Snowflake on January 30, 2024 and sell it today you would lose (239.00) from holding Snowflake or give up 1.49% of portfolio value over 90 days.

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

Snowflake  vs.  ServiceNow

Snowflake

Risk-Adjusted Performance

0 of 100

Very Weak

Over the last 90 days Snowflake has generated negative risk-adjusted returns adding no value to investors with long positions. In spite of inconsistent performance in the last few months, the Stock's basic indicators remain fairly stable which may send shares a bit higher in May 2024. The latest fuss may also be a sign of long-term up-swing for the venture sophisticated investors.

ServiceNow

Risk-Adjusted Performance

0 of 100

Very Weak

Over the last 90 days ServiceNow has generated negative risk-adjusted returns adding no value to investors with long positions. In spite of latest conflicting performance, the Stock's basic indicators remain stable and the latest fuss on Wall Street may also be a sign of long-term gains for the venture sophisticated investors.

Pair Trading with Snowflake and ServiceNow

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

The idea behind Snowflake and ServiceNow 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.