Great Wall Motor Pink Sheet Performance
| GWLLY Pink Sheet | USD 16.24 1.14 7.55% |
Risk-Adjusted Performance
0High
0 · Weak
Performance efficiency for Great Wall Motor has been negative over the last 90 trading days, reflecting weak return quality. The score is most useful when evaluated together with trend stability and downside risk metrics. Great Wall is delivering weak return efficiency relative to its risk profile, with recent data suggesting continued pressure on shareholder returns. Learn More
Relative Risk vs. Return Landscape
If you had invested $ 1,673 in Great Wall Motor on February 11, 2026 and sold it today, you would have lost $ 49.00 , a decline of 2.93% over 90 days. Great Wall Motor is currently producing a 0.0283% return and carries 3.94% volatility of returns over 90 trading days. Stated differently, Great Wall is more volatile than roughly 65% of traded pink sheets, and GWLLY is outperformed by 99% of traded instruments in expected return over the next 90 trading days. Expected Return |
| Risk |
Target Price Odds to finish over Current Price
Changes in sentiment, liquidity, and macro conditions can cause Great Wall Pink Sheet to trade above or below historical valuation norms for extended periods. In some cases, prices remain disconnected from underlying fundamentals until broader market conditions shift. Market pricing may also incorporate forward-looking expectations that differ from historical trading behavior. Forecasting models that incorporate valuation, volatility, and momentum together may provide a more realistic assessment of future price behavior.
| Current Price | Horizon | Target Price | Odds moving above the current price in 90 days |
| 16.24 | 90 days | 16.24 | about 64.15 % |
Our distribution model estimates the likelihood of Great Wall moving above the current price in 90 days from now at about 64.15 %. Past return patterns over this horizon reflect a distribution that has favored above-current-price scenarios. (This Great Wall Motor distribution emphasizes the price range most consistent with recent behavior in Great Wall Pink Sheet over a 90-day period).
Great Wall Price Density |
| Price |
Predictive Modules for Great Wall
Investors apply quantitative and fundamental models to forecast Great Wall Motor within the pink sheet market. Combining results from different methods frames the confidence level warranted by Great Wall Motor predictions. Evaluating multiple forecasts helps separate persistent signals from short-term noise in Great Wall Motor price data. For Great Wall Motor, the combination of techniques matters more than the precision of any individual forecast.Statistical evidence for mean reversion in Great Wall's appears through its tendency to revert after extreme valuations. Under mean reversion theory, Great Wall's price extremes are viewed as temporary dislocations that may self-correct. Mean reversion in Great Wall's is often observed around historical valuation multiples. Historical data for Great Wall shows that extreme valuations have tended to normalize over multi-year periods.
Primary Risk Indicators
Significant market corrections and rallies over the last two decades have made the pink sheet market challenging for Great Wall investors. Dramatic market moves have periodically reshaped the risk landscape for holders of Great Wall Motor. Watching for changes in Great Wall's volatility and market elasticity is one way to limit portfolio losses. A data-driven view of Great Wall risk supports more disciplined portfolio management decisions.α | Alpha over Dow Jones | -0.0341 | |
β | Beta against Dow Jones | 0.93 | |
σ | Overall volatility | 0.80 | |
Ir | Information ratio | -0.009 |
Investor Alerts and Insights
Tracking Great Wall through automated alerts focuses attention on the most impactful stock developments. Reviewing Great Wall Motor notifications is an efficient way to stay current on technical patterns and fundamental changes. Systematic monitoring of Great Wall through automated alerts reduces the risk of missing critical developments. Automated alert systems provide consistency that manual monitoring of Great Wall cannot match.| Great Wall Motor had very high historical volatility over the last 90 days |
Great Wall Fundamentals Growth
Market participants price Great Wall Pink Sheet based on their assessment of Great Wall's financial trajectory. Revenue and earnings growth, profitability metrics, and debt levels form the core fundamentals driving Great Wall Pink Sheet. Revenue growth, earnings performance, and balance sheet health are critical fundamentals shaping Great Wall Pink Sheet. Long-term performance of Great Wall Pink Sheet depends on Great Wall's ability to maintain strong fundamental execution.
| Return On Equity TTM | 0.12 | |||
| Return On Asset TTM | 0.0154 | |||
| Profit Margin TTM | 0.0603 | |||
| Operating Margin TTM | 0.0583 | |||
| Current Valuation | 29.49 B | |||
| Shares Outstanding | 867.9 M | |||
| Price To Earnings TTM | 9.84 X | |||
| Price To Book TTM | 1.21 X | |||
| Price To Sales TTM | 0.22 X | |||
| Revenue TTM | 136.4 B | |||
| EBITDA TTM | 13.46 B | |||
| Cash And Equivalents TTM | 41.88 B | |||
| Cash Per Share TTM | 45.80 X | |||
| Total Debt TTM | 12.13 B | |||
| Debt To Equity TTM | 0.43 % | |||
| Book Value Per Share TTM | 77.96 X | |||
| Cash Flow From Operations TTM | 35.32 B | |||
| Earnings Per Share | 1.51 X | |||
| Total Asset TTM | 175.41 B | |||
| Retained Earnings TTM | 33.41 B | |||
| Current Asset TTM | 41.79 B | |||
| Current Liabilities TTM | 30.27 B | |||
Performance Metrics & Calculation Methodology
Return quality for Great Wall evaluates how consistent and repeatable performance has been across periods. The asset's responsiveness to economic cycles appears relatively balanced. Great Wall shows ROE of 12.39%, ROA of 1.54% (TTM).
Great Wall Motor data is compiled from periodic company reporting and market reference feeds and standardized for comparability. Return and risk statistics are calculated from historical price series.
Editorial review and methodology oversight provided by: Gabriel Shpitalnik, Member of Macroaxis Editorial Board