47a5ef338b
- Replaced standard library signal modules with custom implementations to allow for named patterns and improved voting. - Added new input parameters for module weights, allowing for optimization of individual signal contributions. - Enhanced the management of trades with new options for breakeven and management cut. - Introduced a mechanism for dynamic ranking of signal weights based on historical performance. - Improved initialization logic to ensure proper registration of filters and handling of trading conditions. - Added detailed logging for trading permissions and account status during initialization.
120 lines
6.5 KiB
MQL5
120 lines
6.5 KiB
MQL5
//+------------------------------------------------------------------+
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//| ManagementNet.mqh |
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//| AnimateDread |
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//| |
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//| THE ONE QUESTION NO RULE COULD ANSWER. |
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//| |
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//| A trade is +0.5R in front. Does it run to target, or give it all |
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//| back to the stop? |
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//| |
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//| Measured on 9,770 resolved firings: 46.0% continue to +2R, 54.0% |
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//| retrace. A balanced label on a large sample, and a PERFECT caller |
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//| would be worth +0.540 R per firing - against a pooled deficit of |
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//| -0.13 to -0.18 R. A quarter of it flips the sign of the strategy. |
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//| |
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//| WHY A MODEL AND NOT A RULE. Three rules were tried and all three |
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//| lost money: an ATR trail (+150.67 -> +90.56, worse as it widened),|
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//| a nearer target (-20.32), and a breakeven stop (-22.35 at +0.5R, |
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//| monotonically worse the earlier it fired). They fail for one |
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//| shared reason - a give-back and a pullback-before-a-run look |
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//| IDENTICAL at the moment you must act. That is a classification |
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//| problem wearing a rule's clothes, and a threshold on one number |
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//| cannot separate two populations that overlap on that number. |
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//| |
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//| ⚠ IT DOES NOT PREDICT DIRECTION, and that is the point. Direction |
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//| was measured dead in this project at bar level (rho 0.00-0.02) |
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//| and every architecture thrown at it returned no information out |
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//| of sample. This asks a CONDITIONAL question - given the move has |
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//| already happened, does it extend or exhaust - which is a question |
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//| about persistence and volatility, and volatility is the one thing |
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//| here that has ever been predictable. |
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//| |
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//| ⚠ AND IT TRAINS ON THE CROSSING, NOT ON THE ENTRY. The features |
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//| describe the bar where +0.5R was first touched: how fast it got |
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//| there, how much pain came first, what the market was doing at |
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//| that moment. Using the entry bar's state would be answering a |
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//| different question with the wrong evidence. |
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//| |
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//| ⚠ maeR AS STORED IN THE JOURNAL IS LOOKAHEAD FOR THIS. It is the |
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//| worst excursion over the WHOLE trade, including after the |
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//| crossing, and it separates the two classes beautifully (0.51 vs |
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//| 1.21) precisely because it contains the answer. The adverse |
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//| excursion used here is measured only up TO the crossing bar. |
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//+------------------------------------------------------------------+
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#ifndef WARRIOR_MANAGEMENT_NET_MQH
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#define WARRIOR_MANAGEMENT_NET_MQH
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#include "WarriorNet.mqh"
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#define MGMT_FEATURES 10
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//--- The crossing this model is asked about, in R. Matched to the measurement above.
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#define MGMT_TRIGGER_R 0.5
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//--- How long a virtual trade may stay open before it is abandoned unlabelled.
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#define MGMT_HORIZON 60
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class CManagementNet
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{
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private:
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CWarriorNet m_net;
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bool m_ready;
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string m_why;
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public:
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CManagementNet(void) : m_ready(false), m_why("not trained") {}
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~CManagementNet(void) {}
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bool Ready(void) const { return m_ready; }
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string Why(void) const { return m_why; }
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double AUC(void) const { return m_net.AUC(); }
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static string FeatureName(const int i);
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//--- P(this trade continues to target). <0 when there is no usable model.
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double Score(double &x[]) { return m_ready ? m_net.Score(x) : -1.0; }
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//--- TRAINED IN MEMORY, NEVER SERIALISED.
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//---
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//--- ALGLIB's MQL5 serializer under-allocates its output buffer and dies inside
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//--- CSerializer::Stop() - "array out of range in ap.mqh (1996,17)" - which killed three of four
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//--- H4 runs stone dead AFTER the model had trained and reported a perfectly good AUC. The same
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//--- family of bug already bit DFSerialize on compressed forests in this repo.
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//---
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//--- Nothing is lost by skipping it: the fit is deferred and walk-forward by design, so it is
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//--- rebuilt from history-so-far on every run regardless. A file would only be a cache of
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//--- something cheap, bought at the price of a crash.
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bool Train(CMatrixDouble &xy, const int rows, const string &names[])
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{
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//--- Embargo = the horizon. A virtual trade is a 60-bar window; rows closer than that to the
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//--- boundary overlap the validation set's first rows. In the training matrix each ENTRY bar
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//--- contributes two rows (long and short), so one horizon of bars is two horizons of rows.
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m_ready = m_net.Train(xy, rows, MGMT_FEATURES, names, MGMT_HORIZON * 2);
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m_why = m_net.Why();
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return m_ready;
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}
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};
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//+------------------------------------------------------------------+
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string CManagementNet::FeatureName(const int i)
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{
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switch(i)
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{
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//--- HOW IT GOT HERE. A move that reached +0.5R in one bar is a different animal from one
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//--- that ground there over fifteen, and nothing about the entry bar can express that.
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case 0: return "bars_to_cross";
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case 1: return "mae_before_cross_r"; // pain paid BEFORE the gain - never after it
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case 2: return "cross_speed_r_per_bar";
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//--- WHAT THE MARKET IS DOING AT THE CROSSING. Persistence is the whole question, and these
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//--- two are the direct measures of it: efficient and compounding, or cancelling.
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case 3: return "er_at_cross";
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case 4: return "vr_at_cross";
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case 5: return "regime_at_cross";
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//--- THE CROSSING BAR ITSELF. A wide bar closing at its extreme is an extension; a wide bar
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//--- closing mid-range is exhaustion, and they look the same in R.
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case 6: return "range_atr_at_cross";
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case 7: return "close_in_bar_at_cross";
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case 8: return "vol_rel_at_cross";
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//--- Which way the trade is facing, so one model serves both sides rather than two models
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//--- each trained on half the data.
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case 9: return "is_long";
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}
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return "?";
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}
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#endif // WARRIOR_MANAGEMENT_NET_MQH
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