mirror of
https://github.com/asavinov/intelligent-trading-bot.git
synced 2026-05-04 08:26:19 +00:00
129 lines
4.3 KiB
JSON
129 lines
4.3 KiB
JSON
{
|
|
"api_key": "<binance-key>",
|
|
"api_secret": "<binance-secret>",
|
|
|
|
"telegram_bot_token": "<token>",
|
|
"telegram_chat_id": "<chat-id-to-publish-messages>",
|
|
|
|
"data_folder": "C:/DATA_ITB",
|
|
|
|
// === DOWNLOAD AND MERGE ===
|
|
|
|
"symbol": "BTCUSDT",
|
|
|
|
"data_sources": [
|
|
{"folder": "BTCUSDT", "file": "klines", "column_prefix": ""}
|
|
],
|
|
|
|
// === GENERATE FEATURES ===
|
|
|
|
"feature_sets": [
|
|
{"column_prefix": "", "generator": "talib", "feature_prefix": "", "config": {"columns": ["close"], "functions": ["SMA"], "windows": [1, 5, 10, 15, 60]}},
|
|
{"column_prefix": "", "generator": "talib", "feature_prefix": "", "config": {"columns": ["close"], "functions": ["LINEARREG_SLOPE"], "windows": [5, 10, 15, 60]}},
|
|
{"column_prefix": "", "generator": "talib", "feature_prefix": "", "config": {"columns": ["close"], "functions": ["STDDEV"], "windows": [5, 10, 15, 60]}}
|
|
],
|
|
|
|
// === LABELS ===
|
|
|
|
"label_sets": [
|
|
{"column_prefix": "", "generator": "highlow2", "feature_prefix": "", "config": {"columns": ["close", "high", "low"], "function": "high", "thresholds": [2.0], "tolerance": 0.2, "horizon": 60, "names": ["high_20"]}},
|
|
{"column_prefix": "", "generator": "highlow2", "feature_prefix": "", "config": {"columns": ["close", "high", "low"], "function": "low", "thresholds": [2.0], "tolerance": 0.2, "horizon": 60, "names": ["low_20"]}}
|
|
],
|
|
|
|
// === TRAIN ===
|
|
|
|
"label_horizon": 60,
|
|
"train_length": 525600,
|
|
|
|
"train_features": [
|
|
"close_SMA_1", "close_SMA_5", "close_SMA_10", "close_SMA_15", "close_SMA_60",
|
|
"close_LINEARREG_SLOPE_5", "close_LINEARREG_SLOPE_10", "close_LINEARREG_SLOPE_15", "close_LINEARREG_SLOPE_60",
|
|
"close_STDDEV_5", "close_STDDEV_10", "close_STDDEV_15", "close_STDDEV_60"
|
|
],
|
|
|
|
"labels": [
|
|
"high_20",
|
|
"low_20"
|
|
],
|
|
|
|
"algorithms": [
|
|
{
|
|
"name": "lc", // Unique name will be used as a column suffix
|
|
"algo": "lc", // Altorithm type is used to choose the train/predict function
|
|
"params": {"penalty": "l2", "C": 1.0, "class_weight": null, "solver": "sag", "max_iter": 100},
|
|
"train": {"is_scale": true, "length": 1000000, "shifts": []},
|
|
"predict": {"length": 1440}
|
|
}
|
|
],
|
|
|
|
"features_horizon": 100, // Minimum data length for computing features (in online mode). Take it from feature generator parameters
|
|
|
|
// === AGGREGATION AND POST-PROCESSING ===
|
|
|
|
"score_aggregation_sets": [
|
|
{
|
|
"column": "trade_score", // Output column name: positive values - buy, negative values - sell
|
|
|
|
"buy_labels": ["high_20_lc"],
|
|
"sell_labels": ["low_20_lc"],
|
|
|
|
"parameters": {
|
|
"point_threshold": null, // Produce boolean column (optional)
|
|
"window": 3, // Aggregate in time
|
|
"combine": "difference", // "no_combine" (or empty), "relative", "difference"
|
|
"coefficient": 1.0,
|
|
"constant": 0.0
|
|
}
|
|
}
|
|
],
|
|
|
|
// === SIGNAL RULES FOR TRADING ===
|
|
|
|
"signal_model": {
|
|
"rule_name": "",
|
|
|
|
"signal_columns": ["buy_signal_column", "sell_signal_column"],
|
|
|
|
"parameters": {
|
|
"buy_signal_threshold": 0.05,
|
|
"sell_signal_threshold": -0.05
|
|
},
|
|
"notification": {
|
|
"buy_notify_threshold": 0.02,
|
|
"sell_notify_threshold": -0.02,
|
|
"trade_icon_step": 0.05,
|
|
"notify_frequency_minutes": 1,
|
|
"notify_signal": true,
|
|
"notify_transaction": true,
|
|
"notify_diagram": false
|
|
}
|
|
},
|
|
|
|
"train_signal_model": {
|
|
"data_start": 0,
|
|
"data_end": null,
|
|
|
|
"buy_sell_equal": false,
|
|
"direction": "long",
|
|
"topn_to_store": 10,
|
|
|
|
"grid": {
|
|
"buy_signal_threshold": [0.02, 0.03, 0.04, 0.05, 0.1, 0.15],
|
|
"sell_signal_threshold": [-0.02, -0.03, -0.04, -0.05, -0.1, -0.15]
|
|
}
|
|
},
|
|
|
|
"rolling_predict": {
|
|
// int, null or string with date which will be resolved using time_column and removed from source data
|
|
"data_start": "2020-02-01 00:00:00",
|
|
"data_end": null,
|
|
|
|
// One of these 3 parameters can be null and will be computed from the other two
|
|
"prediction_start": null, // First row for starting predictions, for example, "2022-02-01 00:00:00"
|
|
"prediction_size": 10080, // How many predictions, for example, 1 week 7*1440
|
|
"prediction_steps": 4, // How many train-prediction steps
|
|
|
|
"use_multiprocessing": false,
|
|
"max_workers": 8
|
|
}
|
|
}
|