egutierrez
63a9cb5273
Datascience: aggregate_by_group, deduplicate_entities/relations, detect_drift, diff_entities/relations, extract_entities/relations_llm, hotness_score, melt, merge_graphs, pivot, build_entity/relation_schema_prompt. Finance: avellaneda_stoikov_quotes, generate_gbm_prices, generate_taker_order, hawkes_intensity + módulo finance.py. Cybersecurity: envelope_encrypt/decrypt + módulo cybersecurity.py. Pipelines: extraction_pipeline, monte_carlo_market, run_market_sim. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
1.2 KiB
1.2 KiB
name, kind, lang, domain, version, purity, signature, description, tags, uses_functions, uses_types, returns, returns_optional, error_type, imports, tested, tests, test_file_path, file_path
| name | kind | lang | domain | version | purity | signature | description | tags | uses_functions | uses_types | returns | returns_optional | error_type | imports | tested | tests | test_file_path | file_path | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| generate_taker_order | function | py | finance | 1.0.0 | pure | generate_taker_order(alpha: float, size_min: float, size_max: float, buy_prob: float, seed: int | None) -> dict | Genera una market order de taker con tamano distribuido segun power-law (Pareto). Alpha bajo produce ordenes mas grandes (ballenas). |
|
false |
|
false | python/functions/finance/finance.py |
Ejemplo
order = generate_taker_order(
alpha=2.0,
size_min=1.0,
size_max=100.0,
buy_prob=0.5,
seed=42,
)
# {'side': 'buy', 'qty': 3.7}
Notas
Funcion pura cuando se fija seed. Con seed=None el resultado es no deterministico.
La distribucion Pareto con alpha=2 modela bien la distribucion empirica de tamaños de ordenes en mercados reales.
size_max actua como techo (clipping) para evitar ordenes extremas.
Retorna dict con keys: side ('buy' o 'sell') y qty (float redondeado a 1 decimal).