Forex Next Candle Forecast 3D MT5
- Indicators
- Konstantin Chechnev
- Version: 1.0
The Holy Grail failed to compile again. The indicator, however, compiled just fine—and it generates a forecast for the new candle on its first tick, does not repaint the signal, and keeps statistics.
Under the hood, you will not find yet another “secret formula,” but a modular forecasting system: it checks live quotes, distinguishes a price shock from a data error, selects the calculation model best suited to current conditions, and compares the current market state with its stored scenarios.
The result becomes a clear 3D forecast, and once the candle closes, the system records the outcome honestly—because hindsight can make even a coin toss look like the work of a trading guru.
Not just where price ended up, but how it got there
- Deep Flow reads the tick chronology and builds a microstructural fingerprint of the move: buying and selling pressure, momentum persistence, bursts, pauses, reversals, spread behavior, absorption, and concentration of activity.
- Scenario Engine + Context Layer search completed market episodes for a similar formation mechanism and check trend, volatility, and market session. This is why candles that look alike can receive different forecasts.
- Shock Engine compares price jumps, spread, and tick activity against their historical baseline. When an anomaly occurs, the system widens the forecast range instead of pretending to have confidence it no longer has.
- Adaptive memory is updated only after the candle closes and affects future decisions exclusively—the current forecast is never changed retroactively.
- Recording and verification: before the outcome is known, the forecast is stored in an immutable log and CSV file. Scoring Engine evaluates the result, while the 3D panel displays direction, countdown, outcome, and cumulative statistics.
Meet Lumi
Most indicators manage to fit their entire personality into one green and one red arrow. Our complex forecasting system, however, has gained a heroine of its own—Lumi.
Lumi keeps pace with the market: her cozy scene changes with the time of day and season, while her lines reflect the current forecast state. She comments on the action in her own distinctive style, helps you follow the system, and makes the long wait for the next candle noticeably more pleasant.
Every algorithm looks flawless in its description
Run the demo version and evaluate its behavior on historical tick data. In the visual Strategy Tester, select “Every tick based on real ticks”: this mode comes as close as possible to live market conditions, and the indicator uses the same calculation logic as it does on your live chart—it locks in the forecast before the outcome is known and evaluates it after the candle closes.
This allows you to see the system working through a continuous sequence instead of judging it by a few successful examples, so you can decide for yourself whether this tool belongs on your chart.
A forecast is not autopilot
Forex Next Candle Forecast 3D is an indicator, not an Expert Advisor. It generates a forecast, but it does not open, manage, or close trades. Whether to use the forecast, what position size to use, and how much risk to accept remain entirely up to the trader—risk management still has to be switched on manually.
Profit is, of course, not guaranteed: the market never signed off on the specification and is under no obligation to follow the forecast. Quotes, spreads, data quality, and broker-specific conditions can affect the indicator’s results.
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Settings and initial optimization ranges
Optimizers have a peculiar talent: give them enough knobs and they will inevitably discover a perfect past. That is why Forex Next Candle Forecast 3D exposes only eight high-level parameters. They let you test your own market hypothesis without allowing you to disable Shock Engine, data-quality checks, forecast locking, or subsequent scoring.
The defaults already form a neutral configuration: the built-in model retains its full weight, the additional context adjustments do not pull the decision in either direction, and the directional threshold remains balanced. The multilingual help rows in the Inputs window are informational only and do not affect calculations.
Memory and built-in model
- Analog memory controls how much market history is available to the analog memory. Default: 96 bars. Suggested first pass: Start 64, Step 16, Stop 160. A smaller value reacts more quickly to changes in market behavior; a larger one gives the model broader and steadier context.
- Built-in model weight controls the built-in forecasting model's contribution to the final decision. Default: 1.00. Initial grid: 0.50 / 0.25 / 1.50. A value of 0 removes its contribution, 1 preserves the original weight, and 2 doubles it.
Context adjustments
- Short impulse weight controls the response to short-term momentum in live quotes. Default: 0. Initial grid: -1.0 / 0.5 / 1.0. Positive values favor continuation; negative values test a pullback.
- Six-bar trend weight accounts for the direction of the last six completed bars. Default: 0. Initial grid: -1.0 / 0.5 / 1.0. A positive weight favors trend continuation; a negative one tests reversion.
- Range-location weight evaluates where price sits within the observed range. Default: 0. Initial grid: -1.0 / 0.5 / 1.0. Positive values favor a breakout; negative values favor a move back into the range.
- Opening-gap weight controls the response to the gap between the previous close and the new open. Default: 0. Initial grid: -1.0 / 0.5 / 1.0. A positive weight tests gap continuation; a negative one tests gap closure.
Final decision
- UP probability threshold sets the dividing line between an upward and downward forecast after all components are combined. Default: 0.50. Initial grid: 0.40 / 0.05 / 0.60. Lower values produce more UP decisions; higher values make that condition stricter.
- Signal polarity either preserves the model's directions or reverses every forecast. Default: Normal. Test Inverted separately: it is not a “make it more accurate” switch, but a control test for the sign of the relationship you found.
These grids are starting points for an initial test, not ready-made presets. The code permits wider technical limits: memory 24–256, built-in model weight 0–2, context weights from -3 to 3, and directional threshold 0.30–0.70.
Do not optimize every parameter at once. Test the defaults first, then adjust one logical group at a time and verify the result on a later segment of history that was not used for tuning. Otherwise, the Tester may find not a robust configuration, but a remarkably convincing explanation of what has already happened.
