Goldman Sachs Clean Fund Manager Performance Evaluation

Mutual Funds . USA . 
Fund . Goldman Sachs Clean
GCEBX Fund  USD 13.77  0.10  0.73%   
Goldman Sachs's return record is summarized here, from recent weeks to multi-year horizons. The stock's expected return over 3 months is 0.12%, complemented by a 1.13% dividend yield.
Risk-Adjusted Performance
0High
7 · Moderate
Across the last 90 days, the risk-adjusted return profile of Goldman Sachs Clean is weaker than 7% of the funds and fund portfolios reviewed by Macroaxis. This score becomes more informative when compared with downside risk, Sharpe Ratio, and current trend stability. Recent data suggests Goldman Sachs is converting risk into modest positive returns, a constructive signal if sustained. Learn More

Relative Risk vs. Return Landscape

If you had invested $ 1,282 in Goldman Sachs Clean on February 11, 2026 and sold it today, you would have earned $ 95.00 , a return of 7.41% over 90 days. Goldman Sachs Clean is currently producing a 0.1232% return and carries 1.26% volatility of returns over 90 trading days. Stated differently, Goldman Sachs is more volatile than roughly 89% of traded mutual funds, and GCEBX is outperformed by 98% of traded instruments in expected return over the next 90 trading days.
  Expected Return   
       Risk  
This relative risk-return summary evaluates how the instrument behaves against its benchmark. It is intended to show how efficiently risk has translated into return over the selected horizon. Based on a 90-day horizon, GCEBX generates 1.36 times more return on investment than the market. However, GCEBX is 1.36 times more volatile than its market benchmark. Its risk-adjusted efficiency stands at about 0.1% per unit of risk. Dow Jones Industrial is currently generating roughly -0.01% per unit of risk.

Target Price Odds to finish over Current Price

Historical averages are sometimes used as a secondary reference point when assessing Goldman Sachs Mutual Fund price behavior. In practice, valuation gaps may persist longer than expected when market sentiment or liquidity conditions dominate trading activity. Changes in interest rates, capital flows, or geopolitical developments can influence how investors value Goldman Sachs Mutual Fund.
Current PriceHorizonTarget PriceOdds moving above the current price in 90 days
13.77 90 days 13.77
about 5.8 %
Applying a normal distribution to this fund, the odds of Goldman Sachs moving above the current price in 90 days from now are about 5.8 %. Based on past return behavior, the distribution of outcomes has been weighted above current levels over this period. (The probability curve shows the outcome range with the heaviest concentration for Goldman Sachs Mutual Fund over 90 days). A tighter center suggests recent price behavior has been clustering into a narrower range for Goldman Sachs Mutual Fund.
Based on a 90-day horizon, Goldman Sachs Clean has a beta of -0.19. This usually indicates that as returns on the benchmark increase, returns on Goldman Sachs tend to move in the opposite direction, though by a smaller magnitude. During a bear market, however, Goldman Sachs Clean tends to outperform the market. Additionally, Goldman Sachs Clean has an alpha of 0.1459, implying that it can generate a 0.1459 percent excess return over Dow Jones Industrial after adjusting for the inherent market risk (beta).
   Goldman Sachs Price Density   
       Price  

Predictive Modules for Goldman Sachs

For Goldman Sachs Clean, multiple forecasting techniques provide different perspectives on future fund price direction. No method can consistently predict the fund market with certainty, but disciplined forecasting sharpens analysis. Comparing the outputs of diverse models helps set realistic expectations for Goldman Sachs Clean price behavior.
Mean reversion analysis in Goldman Sachs' involves identifying price extremes that diverge materially from the historical norm. High prices relative to historical norms contrast with unusually low prices, where recovery expectations may emerge. Mean reversion in Goldman Sachs is distinct from trend following, which rides momentum rather than betting on reversals.
Sentiment
Range
LowSentimentHigh
12.5113.7715.03
Details
Intrinsic
Valuation
LowIntrinsicHigh
11.2812.5413.80
Details
Naive
Forecast
LowNextHigh
12.6313.9015.16
Details
Bollinger
Band Projection (param)
LowerMiddle BandUpper
13.1313.6014.06
Details
Goldman Sachs's financial and valuation profile is evaluated here relative to direct competitors. Goldman Sachs's multiples and operating metrics gain context when measured against direct competitors. Growth rates, profitability, and capital efficiency relative to peers frame Goldman Sachs' competitive position.

Primary Risk Indicators

The mutual fund market's volatility over the past 10-20 years has tested even experienced investors in Goldman Sachs. Large corrections and rapid recoveries have created challenges for investors in Goldman Sachs Clean. A disciplined approach to monitoring Goldman Sachs' risk indicators supports more effective hedging decisions.
α
Alpha over Dow Jones		0.15
β
Beta against Dow Jones-0.19
σ
Overall volatility		0.49
Ir
Information ratio 0.1

Goldman Sachs Fundamentals Growth

Goldman Sachs' financial fundamentals are the foundation of Goldman Sachs Mutual Fund market pricing and valuation. Metrics like earnings growth, revenue consistency, and margin trends collectively determine market sentiment toward Goldman Sachs Mutual Fund. Goldman Sachs Mutual Fund market pricing reflects the collective assessment of Goldman Sachs's financial fundamentals.
Total Asset TTM349.77 M

Performance Metrics & Calculation Methodology

Return quality for Goldman Sachs measures how stable NAV growth has been across rolling measurement windows. Consistent positive returns across rolling windows support confidence in structural performance patterns.

Goldman Sachs Clean analytics rely on fund disclosures and market reference feeds, with quality checks and normalization applied. Return and risk statistics are calculated from historical price series.

Editorial review and methodology oversight provided by: Vlad Skutelnik, Macroaxis Contributor
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