Correlation Between Snowflake and FactSet Research

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

By analyzing existing cross correlation between Snowflake and FactSet Research Systems, you can compare the effects of market volatilities on Snowflake and FactSet Research 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 FactSet Research. Check out your portfolio center. Please also check ongoing floating volatility patterns of Snowflake and FactSet Research.

Diversification Opportunities for Snowflake and FactSet Research

-0.54

Correlation Coefficient

Snowflake  FactSet Research

Excellent diversification

The 3 months correlation between Snowflake and FactSet is -0.54. Overlapping area represents the amount of risk that can be diversified away by holding Snowflake and FactSet Research Systems in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on FactSet Research Systems 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 FactSet Research. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of FactSet Research Systems has no effect on the direction of Snowflake i.e., Snowflake and FactSet Research go up and down completely randomly.

Pair Corralation between Snowflake and FactSet Research

Given the investment horizon of 90 days Snowflake is expected to generate 1.75 times more return on investment than FactSet Research. However, Snowflake is 1.75 times more volatile than FactSet Research Systems. It trades about 0.09 of its potential returns per unit of risk. FactSet Research Systems is currently generating about -0.32 per unit of risk. If you would invest  21,194  in Snowflake on July 16, 2025 and sell it today you would earn a total of  3,533  from holding Snowflake or generate 16.67% return on investment over 90 days.

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

Snowflake  vs.  FactSet Research Systems

Snowflake

Risk-Adjusted Performance

Mild

Compared to the overall equity markets, risk-adjusted returns on investments in Snowflake are ranked lower than 6 (%) of all global equities and portfolios over the last 90 days. In spite of fairly inconsistent basic indicators, Snowflake showed solid returns over the last few months and may actually be approaching a breakup point.

FactSet Research Systems

Risk-Adjusted Performance

Weakest

Over the last 90 days FactSet Research Systems has generated negative risk-adjusted returns adding no value to investors with long positions. In spite of weak performance in the last few months, the Stock's fundamental indicators remain comparatively stable which may send shares a bit higher in November 2025. The newest uproar may also be a sign of mid-term up-swing for the firm private investors.

Pair Trading with Snowflake and FactSet Research

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

The idea behind Snowflake and FactSet Research Systems 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.