Correlation Between SoFi Technologies and CBOE Volatility

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

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

Diversification Opportunities for SoFi Technologies and CBOE Volatility

-0.65

Correlation Coefficient

SoFi Technologies  CBOE Volatility

Excellent diversification

The 3 months correlation between SoFi and CBOE is -0.65. Overlapping area represents the amount of risk that can be diversified away by holding SoFi Technologies and CBOE Volatility Index in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CBOE Volatility Index and SoFi Technologies 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 SoFi Technologies are associated (or correlated) with CBOE Volatility. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CBOE Volatility Index has no effect on the direction of SoFi Technologies i.e., SoFi Technologies and CBOE Volatility go up and down completely randomly.

Pair Corralation between SoFi Technologies and CBOE Volatility

Given the investment horizon of 90 days SoFi Technologies is expected to generate 0.52 times more return on investment than CBOE Volatility. However, SoFi Technologies is 1.94 times less risky than CBOE Volatility. It trades about 0.38 of its potential returns per unit of risk. CBOE Volatility Index is currently generating about -0.02 per unit of risk. If you would invest  811.00  in SoFi Technologies on September 18, 2024 and sell it today you would earn a total of  877.00  from holding SoFi Technologies or generate 108.14% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Against
Strength	Weak
Accuracy	98.44%
Values	Daily Returns

SoFi Technologies  vs.  CBOE Volatility Index

Pair Trading with SoFi Technologies and CBOE Volatility

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

The idea behind SoFi Technologies and CBOE Volatility Index 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 Correlation Analysis module to reduce portfolio risk simply by holding instruments which are not perfectly correlated.