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Ornstein Uhlenbeck Reverter [forexobroker]

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Ornstein-Uhlenbeck Reverter fits the continuous-time mean-reverting OU process dX = theta * (mu - X) * dt + sigma * dW to recent closes. Parameters theta (mean-reversion speed) and mu (long-run mean) are estimated by OLS. Half-life of reversion = ln(2) / theta. Signals fade overshoots beyond k * sigma — a statistically grounded mean-reversion entry.

🔶 ALGORITHM

1. Linear regression: r[t] = a + b * close[t-1] + e, where r = close[t-1] - close[t] (the negative one-step return).
2. theta_hat = -b (assuming dt = 1); mu_hat = a / theta_hat.
3. Half-life = ln(2) / theta. Sigma = stdev of OLS residuals.
4. Overshoot = (close - mu) / sigma.
5. Long fade: overshoot was below -k AND now turning back up. Short fade: above +k AND turning down.

🔶 SIGNAL LOGIC

- Buy: long fade trigger AND not already long AND cooldown elapsed AND barstate.isconfirmed.
- Sell: short fade trigger.
- Position-lock state machine.

🔶 INPUTS

- Fit Window (default 60)
- Overshoot k x sigma (default 1.5)
- Cooldown Bars (default 4)
- Visual: dashboard, glow, equilibrium hline, buy / sell colors

🔶 ALERTS

OUR Buy, OUR Sell, OUR Any Signal, OUR Underext, OUR Overext, OUR Extreme, OUR Fast Revert, OUR Drift Mode, OUR Webhook JSON.

🔶 LIMITATIONS

- OU assumes constant mu over the fit window; trending markets violate this and produce theta near zero (drift mode).
- OLS is sensitive to outliers; robust alternatives (MAD-based) may help on spike-heavy assets.
- The fit re-runs every bar; transitional periods produce unstable mu estimates.
- Mean-reversion strategies underperform during persistent trends; pair with a regime gate (e.g., Hurst < 0.5).

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