How accurate are hedgewing.ai's machine-learning stock predictions?

hedgewing.ai publishes live ensemble accuracy per horizon on the Accuracy dashboard. Ensemble 1-day directional accuracy averages in the high 50s on large-cap US equities across full market cycles. Every prediction ships with a calibrated confidence interval. We do not hide underperformance.

What deep-learning architectures power hedgewing.ai's stock predictions?

hedgewing.ai uses a four-model neural ensemble: LSTM with attention, GRU with skip connections, Temporal CNN in WaveNet style, and a Transformer encoder. Each model is trained on 45 engineered features spanning price, volume, volatility, and macro regime factors. Model weights are versioned, audited, and walk-forward backtested before promotion.

How often are the ML models retrained?

Per-ticker fine-tuning runs nightly on the most recent rolling window. Full architecture retraining with hyperparameter search runs weekly. Every retrain is benchmarked against the prior weights on a held-out walk-forward set before promotion to production.

How much does hedgewing.ai cost?

hedgewing.ai is free to start with 5 full AI analyses per day. Pro is $19.99/month (or $199.99/year) with unlimited analyses, ML predictions, backtesting, and risk analytics. Workspace is $49.99/month for teams and includes API access. Every plan includes a 7-day Pro trial with no credit card required.

Is hedgewing.ai investment advice?

No. hedgewing.ai is a research and analytics platform for informational and educational purposes only. We do not provide personalized investment advice. Please consult a licensed advisor before making investment decisions.

Does hedgewing.ai offer an API?

Yes. API access and webhook exports are included on the Workspace tier. Endpoints cover predictions, quantitative metrics, and daily intelligence briefs. Rate limits are generous for research workflows.

How is hedgewing.ai different from Bloomberg Terminal or QuantConnect?

Bloomberg Terminal costs around $24,000 per year and targets institutional desks. Quant data vendors run $5,000 to $15,000 per year. hedgewing.ai delivers a production deep-learning ensemble plus institutional risk analytics for $19.99 per month — roughly 99% cheaper than Bloomberg with modern UX and out-of-the-box ML.

What is walk-forward backtesting?

Walk-forward backtesting evaluates a model by training on a rolling historical window, predicting the next out-of-sample period, then sliding the window forward. It prevents look-ahead bias and is the institutional standard for ML model validation. hedgewing.ai walk-forward backtests every model nightly.

Can I cancel my hedgewing.ai subscription at any time?

Yes. Cancellations take effect at the end of the current billing period. You retain full access until then and we never charge surprise fees.

How does Hedgewing predict stocks?

Hedgewing runs a four-model deep-learning ensemble — LSTM, GRU, TCN, and Transformer — combined by a stacking meta-learner over 45 engineered features. It scores 229 US equities daily across 1-, 5-, 10-, and 20-day horizons, each with a calibrated confidence band, and walk-forward backtests every model nightly before any prediction ships.

How accurate is Hedgewing?

Ensemble 1-day directional accuracy averages in the high 50s percent on large-cap US equities across full market cycles, with a calibrated confidence interval on every prediction. Hedgewing publishes live accuracy per horizon and does not hide underperformance.

What is walk-forward backtesting?

Walk-forward backtesting trains on a rolling historical window, predicts the next out-of-sample period, then slides the window forward. It prevents look-ahead bias and is the institutional standard for validating an ML trading model.

How Hedgewing predicts stocks

Q: Where does hedgewing.ai source its market data?

hedgewing.ai aggregates data from multiple licensed providers including Yahoo Finance fundamentals, Polygon equities, and curated news feeds. Real-time quotes stream through our edge broadcast hub.

Hedgewing forecasts the direction of US equities over 1-, 5-, 10-, and 20-day horizons, each with a calibrated confidence band. A four-model deep-learning ensemble — LSTM, GRU, Temporal CNN, and Transformer, combined by a stacking meta-learner — reads 45 engineered features per ticker and is walk-forward backtested nightly before a single prediction ships.

Ensemble 1-day directional accuracy averages in the high 50s percent on large-cap US equities across full market cycles. Every prediction ships with a calibrated confidence interval, and live accuracy is published per horizon.

Licensed market data

Hedgewing aggregates data from multiple licensed providers — Yahoo Finance fundamentals, Polygon equities, and curated news feeds — computed point-in-time so no future information leaks into a backtest.

45 engineered features

Each ticker is described by 45 features spanning price, volume, volatility, momentum, mean reversion, and macro-regime factors.

Four deep-learning architectures

LSTM with attention, GRU, a dilated-causal Temporal CNN, and a Transformer encoder each learn complementary patterns; a stacking meta-learner weights them by recent skill so idiosyncratic errors cancel.

Calibrated confidence and walk-forward validation

Scores are calibrated to true probability on held-out data, and every model is validated on rolling out-of-sample windows before promotion. Per-ticker fine-tuning runs nightly; full retraining runs weekly.

Honest limitations

Markets are noisy and largely efficient; no model predicts prices exactly, and a sustained edge above the low 60s percent is rare. Hedgewing is US-equities research tooling, not a full data terminal or a broker. Backtested and past performance do not guarantee future results, and nothing here is personalized investment advice — see our disclosures.