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Biblioteca de conhecimento

Resumos e ideias principais, escritos pelo agente de investigação da Stratmill, dos livros, artigos científicos, artigos e código consultados pelos nossos agentes de IA. Cada página inclui uma ligação para o original.

Quant Q&A
20,364 documentos
SuperMind
12,226 documentos
OKX Learn
8,431 documentos
Strategy library
7,910 documentos
MQL5 code base
7,090 documentos
BigQuant
3,481 documentos
Bitget Academy
3,298 documentos
MQL5 articles
3,012 documentos
TradingView scripts
1,976 documentos
ProRealCode
1,507 documentos
Deribit Insights
1,232 documentos
Machine Learning for Trading
1,124 documentos
arXiv papers
1,033 documentos
Amberdata research
766 documentos
FMZ forum
682 documentos
FMZ digest
662 documentos
vn.py community
560 documentos
QuantInsti blog
511 documentos
Galaxy Research
340 documentos
QuantStart
246 documentos
Stratmill research code
219 documentos
Robot Wealth
195 documentos
NautilusTrader
191 documentos
Hummingbot docs
181 documentos
Paradigm research
175 documentos
Lumibot
164 documentos
Kraken Learn
163 documentos
Biblioteca de cursos de quant
157 documentos
OctoBot
152 documentos
Cryptohopper blog
144 documentos
Systematic trading blog (Rob Carver)
132 documentos
Qlib
116 documentos
TqSdk
86 documentos
Quantpedia
86 documentos
Hyperliquid docs
79 documentos
Freqtrade
68 documentos
Hudson & Thames
62 documentos
Awesome Systematic Trading
61 documentos
backtrader
54 documentos
vn.py
50 documentos
Binance API docs
45 documentos
Aulas Quantopian
45 documentos
FMZ guides
38 documentos
pysystemtrade
34 documentos
Freqtrade docs
32 documentos
quant-trading
31 documentos
FinRL
28 documentos
Zipline
22 documentos
FMZ live strategies
21 documentos
Jesse
17 documentos
pyfolio
16 documentos
Alphalens
14 documentos
WonderTrader
14 documentos
backtesting.py
11 documentos
Technical Analysis
9 documentos
QTPyLib
8 documentos
QuantRocket
7 documentos
Lumibot strategies
7 documentos
Awesome Quant
1 documentos

Pesquisar na biblioteca

34 documentos

pysystemtrade

This Python module defines four types of trading forecasts from price or carry series. Its breakout rule locates the rolling high-low range, measures the current price relative to the range midpoint, scales that reading, and smooths it with an exponentially…

Rutura de níveisCarryReversão à médiaIndicadores técnicos
pysystemtrade

This risk stage calculates portfolio risk for several position representations. It can pass optimized portfolio weights directly to the portfolio stage, or estimate risk from original positions after buffering and rounding. For the latter path, it gathers…

Construção de carteirasGestão do riscoDimensionamento de posições
pysystemtrade

This document explains how a futures trading system uses several instrument sets: the full catalog, instruments sampled for price data, instruments with adjusted prices, and the smaller sets used in simulation or production backtests. It describes…

FuturosTestes históricosConstrução de carteirasExecução
pysystemtrade

This code models order and trade state for a scalping system. When flat with no open orders, it places buy and sell limit orders around the current price, with their distance based on a volatility-like measure R and a configurable multiplier. After one order…

ExecuçãoGestão do riscoDimensionamento de posiçõesTestes históricos
pysystemtrade

This documentation explains the production workflow for pysystemtrade, from obtaining market prices and generating desired positions to sending orders and reconciling accounting information. It covers the production system’s components and data flow, broker…

ExecuçãoMicroestrutura de mercadoFuturosCâmbio
pysystemtrade

This code implements a portfolio stage that recalculates instrument positions across dates. For each date, it builds an optimization objective from target contract positions, a covariance estimate, contract values, transaction costs, previous positions,…

Construção de carteirasDimensionamento de posiçõesExecuçãoGestão do risco
pysystemtrade

This position-sizing stage converts a combined trading forecast into a subsystem position. It scales the forecast by an average position size derived from the account’s daily cash volatility target and the instrument’s volatility, then normalizes by the…

Dimensionamento de posiçõesVolatilidadeGestão do risco
pysystemtrade

This document describes a raw-data stage in a futures trading system that prepares reusable price and carry calculations for later forecasting. It retrieves daily, natural-frequency, and hourly prices; computes absolute daily and hourly price changes; and…

FuturosVolatilidadeCarryEstatística
pysystemtrade

The code builds a portfolio of instruments through a greedy selection process. It first scores each eligible instrument individually, then repeatedly adds the candidate that gives the highest estimated portfolio Sharpe ratio. Correlations enter through a…

Construção de carteirasGestão do riscoDimensionamento de posiçõesExecução
pysystemtrade

This system stage combines already scaled and capped forecasts from multiple trading rules for an instrument. It aligns rule weights with available forecasts, adjusts weights when forecasts are missing, carries weights forward across dates, smooths them with…

Construção de carteirasGestão do risco