SoFi Technologies Stock Performance

SOFI Stock  USD 16.03  0.01  0.06%   
SoFi Technologies's return record is summarized here, from recent weeks to multi-year horizons. Over the last 3 months, the expected return is -0.25%.
Risk-Adjusted Performance
Weak
0
0100
SoFi Technologies posted below-breakeven returns over the last 90 days, with return quality lagging for investors with long positions. Weak return efficiency can persist even when isolated price moves briefly appear constructive. Over the measured horizon, SoFi Technologies has produced deeply negative returns relative to the volatility absorbed. Learn More

Relative Risk vs. Return Landscape

If you had invested $ 1,946 in SoFi Technologies on February 5, 2026 and sold it today, you would have lost $ 343.00 , a decline of 17.63% over 90 days. SoFi Technologies does not currently generate positive expected returns and carries 3.4% risk (volatility on return distribution) over a 90-day horizon. In relative terms, SoFi Technologies exhibits above-average volatility, exceeding roughly 70% of comparable stocks, and SOFI has trailed 99% of traded instruments in return over the 90-day horizon.
  Expected Return   
       Risk  
This comparison focuses on expected return, realized volatility, and risk efficiency versus the market. It is informative when expected return is read together with volatility rather than in isolation. Given a 90-day horizon, SOFI has been underperforming the market. Compounding this underperformance, SOFI is 3.51 times more volatile than its market benchmark. It converts risk into return at a rate of about -0.07%. Dow Jones Industrial is currently generating roughly 0.02% per unit of volatility.

Target Price Odds to finish over Current Price

Mean reversion in SoFi Stock pricing reflects the documented tendency for stocks to gravitate toward equilibrium. While this pattern holds broadly, certain stocks can remain mispriced for extended periods before correction.
Current PriceHorizonTarget PriceOdds moving above the current price in 90 days
16.03 90 days 16.03
about 89.41 %
Using a normal distribution model, the likelihood of SoFi Technologies moving above the current price in 90 days from now is about 89.41 %. Past return patterns over this horizon reflect a distribution that has favored above-current-price scenarios. (The curve shows where outcomes have been clustering for SoFi Stock over the next 90 days). The curve width gives a practical read on how much uncertainty surrounds SoFi Stock over this horizon.
Given a 90-day horizon, the stock has the beta coefficient of 1.99 . This usually implies when the benchmark rises, SOFI tends to outperform it on average. However, when benchmark returns turn negative, SoFi Technologies tends to underperform. Additionally, SoFi Technologies has a negative alpha, implying that risk has not been adequately compensated by returns. SOFI is significantly underperforming the Dow Jones Industrial.
   SoFi Technologies Price Density   
       Price  

Predictive Modules for SoFi Technologies

Forecasting SoFi Technologies requires combining quantitative signals with evolving sentiment and fundamental trends. Each approach has strengths and limitations, making diversified forecasting strategies especially important for SoFi Technologies.
Mean reversion is the tendency of SoFi Technologies' price to return to its historical average after periods of extreme deviation. Some analysts monitor this tendency by comparing SoFi Technologies' price extremes to fundamental value.
Sentiment
Range
LowSentimentHigh
12.6916.0919.49
Details
Intrinsic
Valuation
LowIntrinsicHigh
11.5214.9218.32
Details
Naive
Forecast
LowNextHigh
9.4012.8016.20
Details
Bollinger
Band Projection (param)
LowerMiddle BandUpper
14.6917.3820.06
Details
SoFi Technologies is positioned within its peer group by benchmarking margins, returns, and multiples. This peer-relative view identifies where SoFi Technologies leads, trails, or tracks its competitive set.

Primary Risk Indicators

Over the past two decades, the stock market has experienced significant volatility affecting SoFi Technologies. SoFi Technologies has seen dramatic price moves that have reshaped risk profiles for its holders.
α
Alpha over Dow Jones
-0.3345
β
Beta against Dow Jones1.99
σ
Overall volatility
1.57
Ir
Information ratio -0.0995

Investor Alerts and Insights

Targeted alerts for SoFi Technologies provide the responsiveness needed to evaluate market conditions and assess potential outcomes. These notifications for SoFi Technologies help investors make timely decisions in response to significant stock events.
SoFi Technologies generated a negative expected return over the last 90 days
SoFi Technologies has high historical volatility and very poor performance
SoFi Technologies currently holds about $935.16 million in cash as of latest reporting with -$3.74 billion of positive cash flow from operations. This results in cash-per-share (CPS) ratio of 1.01.
Latest headline from thelincolnianonline.com: Disposition of 4919 shares by Jennifer Piepszak of JPMorgan Chase at 309.4201 subject to Rule 16 b-3

Price Density Drivers

Price movements in SoFi Technologies are influenced by the balance of buyer and seller positioning dynamics. Monitoring key indicators provides context for understanding when price movements are fundamental versus tactical.
Common Stock Shares Outstanding1.25 billion
Cash And Short Term Investments4.93 billion

SoFi Technologies Fundamentals Growth

The market price of SoFi Stock is shaped by investors' expectations for SoFi Technologies' financial performance. Revenue and earnings trends, operating margins, and capital structure decisions all play a role in SoFi Stock pricing.

Performance Metrics & Calculation Methodology

SoFi Technologies risk-adjusted performance measures whether returns compensate for the volatility borne by holders. Sharpe and Sortino ratios frame return efficiency relative to total and downside risk. SoFi Technologies shows ROE of 6.6%, ROA of 1.26% (TTM).

SoFi Technologies inputs come from periodic company reporting and market reference feeds and are mapped into a consistent reporting framework. Return and risk statistics are calculated from historical price series.

Editorial review and methodology oversight provided by: Rifka Kats, Member of Macroaxis Editorial Board