You already weigh discounted‑cash‑flow models and price charts, but both leave blind spots. DCF anchors long‑term worth yet lags real‑time news, while technical patterns often ignore economics altogether. Our AI Valuation Engine closes that gap bylearning the relationship between a company’s latest fundamentals and its next six‑to‑twelve‑month price delta. Instead of guessing the absolute “true” price, the model focuses on the change—the incremental rerating that should logically follow a shift in revenue, margins, leverage, or capital intensity. You can therefore act onwhere the stock is likely heading, not just where it “ought” to settle someday
Pillar | Details |
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Coverage | Approximately 10 000 listed equities across North America, Europe, and Japan since 2005 |
Raw Inputs | Quarterly and annual filings, segment disclosures, share‑based‑comp adjustments, intraday price/volume, and macro factors such as CPI and the 10‑year yield |
Engineered Signals | Growth rates, trend‑adjusted margins, rolling ROIC, leverage ratios, working‑capital turn, buy‑back intensity, proprietary “moat” quality metrics, and over 300 additional features |
Label | Risk‑adjusted excess return versus the MSCI ACWI over the next 6–12 months |
Lagged variables (one to eight quarters), rolling z‑scores, calendar seasonality buckets, and peer‑ranked percentiles help the network “see” both longitudinal trends and cross‑sectional context.
Regime | Excess IRR vs S&P 500 | Hit Rate | Max Draw‑Down | Context |
---|---|---|---|---|
2006 – 2020 Out‑of‑Sample | robust +5.4 pp/yr | 63 % | −21 % | Before transaction costs |
2021 – Q1 2023 Paper Trade | solid +4.9 pp/yr | 60 % | −19 % | Stress‑tested in a volatile macro window |
Q2 2023 – Today Live | encouraging +3.3 pp/yr | 58 % | −17 % | Includes real execution slippage |
Past results do not guarantee future returns, yet the consistency underscores statistical validity. Metrics are market‑neutral.
Field | Meaning | Typical Range |
---|---|---|
AI Target Δ% | Model‑implied price change over the next 6–12 months | −40 % to +80 % |
AI Rating | Five‑bucket signal from Strong Sell to Strong Buy | Discrete |
Confidence | Posterior probability that the direction of Δ% is correct | 50 % to 85 % |
Driver Tags | Top SHAP factors (e.g., “FCF ↑”, “Debt/EBITDA ↓”) | 3 per stock |
Risk | Implication | Mitigation |
---|---|---|
Data Quality | Restated filings or erroneous inputs can distort forecasts. | Automatic anomaly detection flags outliers for manual review. |
Regime Shifts | Structural changes may weaken learned relationships. | Quarterly retrains incorporate new economic regimes quickly. |
Crowding | Alpha can compress if many adopt similar signals. | Continual feature R&D and ensembling maintain edge. |
Black‑Box Perception | Limited transparency can deter discretionary managers. | SHAP driver tags and factor downloads enhance clarity. |
Execution Slippage | Real trades may fill away from theoretical mid‑quotes. | Live metrics already incorporate typical bid‑ask spreads. |
The InvestorsCraft AI Valuation Engine turns raw, time‑stamped fundamentals intostatistically significant, forward‑looking price deltas you can act on today. Use its signals to sharpen your watch‑list, time entries and exits, and cross‑check qualitative narratives—always in concert with disciplined risk management and complementary research.