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Kennisbibliotheek

Samenvattingen en belangrijkste inzichten van boeken, papers, artikelen en code die onze AI-agents lezen, geschreven door de onderzoeksagent van Stratmill. Elke pagina verwijst naar het origineel.

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

Doorzoek de bibliotheek

191 documenten

NautilusTrader

This reference explains how the Nautilus trading framework models a listed share or ETF as an equity instrument. It describes required identifiers, venue symbol, quote currency, price precision and increment, timestamps, and optional metadata such as lot…

AandelenSpotmarktenOrderuitvoering
NautilusTrader

This reference explains how a bar represents open, high, low, close, and volume data for a specified bar type. A venue or provider may supply bars, or a trading system may build them from quote ticks, trade ticks, or smaller bars. Bar type carries…

MarktmicrostructuurBacktestenOrderuitvoering
NautilusTrader

This indicator extends a price channel with two intermediate levels, crossover signals, and optional stop-loss and take-profit markers. It defines five channel levels: the high and low boundaries, the midpoint, and two intermediate levels positioned between…

Technische indicatorenUitbraakRisicobeheerBacktesten
NautilusTrader

This overview explains how NautilusTrader simulates strategies against historical data. A backtest engine processes a historical data stream through components that are also used in live trading, including portfolios, strategies, execution algorithms, and…

BacktestenOrderuitvoeringMarktmicrostructuurRisicobeheer
NautilusTrader

This reference explains an order-rejection event in an execution system. A rejection marks an order as terminal, updates the order and cache, and is published to the message bus for handlers such as a strategy’s rejection callback. The event commonly follows…

OrderuitvoeringMarktmicrostructuurRisicobeheer
NautilusTrader

This design document explains how NautilusTrader captures state-changing messages in a durable, ordered event log. Each run has its own sequence numbers, entries, and manifest; the log can be inspected, verified, or replayed to rebuild cache state. Captured…

OrderuitvoeringBacktestenMarktmicrostructuurRisicobeheer
NautilusTrader

This documentation explains platform support for listed, crypto, spread, and binary options, including differences in their metadata and identifiers. It describes subscribing to venue-provided Greeks either for an individual contract or for a series-level…

OptiesCryptoPrijsbepaling van derivatenBacktesten
NautilusTrader

The document explains how a trading system represents instruments across spot assets, futures, options, swaps, CFDs, betting markets, and synthetic instruments. Each instrument has a unique symbol-and-venue identity, while its definition carries details such…

Multi-assetRisicobeheerOrderuitvoering
NautilusTrader

This guide explains how an execution system applies order events, interprets command outcomes, retries requests, persists state, and reconciles local orders with venue reports. It distinguishes definitive local failures, confirmed venue results, and unknown…

OrderuitvoeringMarktmicrostructuurRisicobeheer
NautilusTrader

This technical reference explains how a synthetic instrument represents a locally calculated price derived from other instruments. Formulas can express averages, spreads, baskets, or ratios; the instrument is assigned a synthetic venue and uses specified…

Multi-assetOrderuitvoeringMarktmicrostructuur
NautilusTrader

The document explains an order-canceled event in an execution system: it records an order entering the terminal canceled state, updates the order and cache, and is published to the message bus. Cancellation events may originate from a venue, a simulated…

OrderuitvoeringMarktmicrostructuur
NautilusTrader

This guide explains deterministic simulation testing for a concurrent trading system. It describes how a seed-controlled runtime can make task scheduling, timer events, random draws, and channel delivery repeatable, allowing a failure to be replayed and…

BacktestenStatistiekOrderuitvoering
NautilusTrader

This example configures a live-node application to run a Bollinger Band mean-reversion strategy against the Architect AX sandbox on a EUR/USD perpetual instrument, using one-minute midpoint bars. It sets a Bollinger period of 20 with a two-standard-deviation…

ValutahandelPerpetuele futuresTerugkeer naar het gemiddeldeTechnische indicatoren
NautilusTrader

This tutorial demonstrates a component-level backtest workflow using NautilusTrader. It loads historical Binance ETH/USDT trade ticks, configures a simulated spot venue with a cash account and maker-taker fees, and aggregates ticks into bars. A strategy…

CryptoTechnische indicatorenTrendvolgendOrderuitvoering
NautilusTrader

This guide explains how NautilusTrader stores and accesses market data through a Parquet catalog backed by a Rust storage layer. It covers local and cloud storage, timestamp precision, compression choices, file organization, typed data queries, and…

BacktestenOrderuitvoeringMarktmicrostructuurRisicobeheer
NautilusTrader

This documentation describes an order event raised when a trading venue refuses a cancellation request. The execution engine applies the event to the order, updates the cache, and publishes it through the message bus. A typical state change moves an order…

OrderuitvoeringMarktmicrostructuur
NautilusTrader

This document explains how NautilusTrader builds, publishes, and verifies release artifacts across Python packages, Rust crates, Docker images, and GitHub Releases. Its release process anchors package integrity to a draft GitHub release: artifacts are…

RisicobeheerOrderuitvoering
NautilusTrader

This document explains how NautilusTrader’s shared network clients add trading-system behavior to HTTP, WebSocket, and raw TCP transports. It covers quota sharing, proxy selection, connection reuse, retries, response limits, streaming deadlines, and…

OrderuitvoeringMarktmicrostructuurStatistiekRisicobeheer
NautilusTrader

A stop-limit order waits for a specified trigger price, then submits a limit order at the chosen limit. This combines a conditional trigger with control over the worst acceptable execution price, making it useful for price-protected exits or breakout…

OrderuitvoeringRisicobeheerValutahandelUitbraak
NautilusTrader

This example configures a backtest for a mean-reversion strategy on an AUDUSD perpetual contract. It feeds quote data into a backtest engine, forms one-minute midpoint bars, and instantiates a strategy configured with Bollinger Bands and RSI. The listed…

ValutahandelTerugkeer naar het gemiddeldeTechnische indicatorenBacktesten
NautilusTrader

This tutorial explains a two-input market-making setup for a Lighter perpetual linked to Nvidia shares. The Lighter order book supplies the price anchor, while Databento US equity top-of-book quotes provide a normalized signal: the equity mid is compared…

MarketmakingAandelenCryptoPerpetuele futures
NautilusTrader

This example demonstrates how a backtest engine can model automatic liquidation on a margin account holding an inverse Bitcoin perpetual. It configures a simulated venue with liquidation enabled, starts with one BTC, and submits a market buy for 10,000,000…

CryptoPerpetuele futuresBacktestenRisicobeheer
NautilusTrader

This reference explains how NautilusTrader connects to exchanges, brokerages, and data providers through modular adapters. It lists supported integrations and their categories and stability labels, then outlines the common functions these adapters are…

OrderuitvoeringMarktmicrostructuurCryptoFutures
NautilusTrader

This documentation explains how to build Nautilus trading systems in Rust or Python. The Rust path supports actors, strategies, data and execution engines, risk management, backtesting, portfolios, and live trading; Python components can run on the shared…

OrderuitvoeringBacktestenMarktmicrostructuurCrypto