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Knowledge library

Summaries and key ideas, written by Stratmill's research agent, of the books, papers, articles and code our AI agents read. Each page links to its original.

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

Search the library

9,660 documents

MQL5 code base

This Expert Advisor bases its trading decisions on two moving averages, with periods of five and four, on a five-minute chart. It assigns separate take-profit and stop-loss levels to buy and sell positions. The decision conditions are evaluated only when a…

Technical indicatorsForexExecutionBacktesting
NautilusTrader

This example configures a composite market-making strategy that uses NVDA equity quotes as its signal and quotes an NVDA perpetual contract on Lighter. The settings specify a maximum position and trade size, a half-spread, inventory and signal skew factors,…

Market makingPerpetual futuresEquitiesExecution
Lumibot

This documentation explains why a trading strategy may need its own view of the current date and time. The strategy's clock reflects the simulated point in time during a backtest and the relevant time during live trading. This matters when historical logic…

BacktestingExecution
MQL5 code base

This brief describes an expert advisor that monitors account equity relative to balance and closes all open positions once equity reaches a configured percentage above balance. Its stated scope covers positions across symbols and magic numbers, so the…

Risk managementPosition sizingExecution
NautilusTrader

An OrderFilled event represents an execution against an order, whether the execution completes the order or only fills part of it. The execution engine applies the event to the order, updates the cache, and publishes it through the message bus. Fills can…

ExecutionMarket microstructure
NautilusTrader

A market order tells a venue to execute a specified quantity promptly at the best available price. The document outlines when traders might use one, such as urgent risk reduction or entering a liquid, fast-moving market, and shows how an order can include…

ExecutionForexMarket microstructureRisk management
vn.py community

The discussion explains a timing issue in CTA strategies using the CTP interface: order status updates may arrive before trade updates, and the position is updated with the trade notification. A strategy that reacts to a fully filled order inside its order…

ExecutionMarket microstructureRisk management
Hyperliquid docs

This documentation summarizes eligibility and account limits for Hyperliquid sub-accounts. A master account can create up to ten after reaching the stated trading-volume threshold; further volume milestones allow additional accounts, subject to a maximum of…

CryptoExecution
Lumibot

This example describes a daily SPY strategy that assigns market analysis and order decisions to separate AI agents. The research agent compares the latest completed daily close with its 20-bar average and reports the date, observed prices, evidence for and…

Machine learningTrend followingRisk managementExecution
MQL5 code base

iSpread is a chart indicator that displays the spread for each bar as a histogram, marks the minimum spread over a chosen period with a horizontal line, and shows the current spread in the indicator window. These elements provide a visual summary of spread…

Market microstructureExecutionTechnical indicators
BigQuant

This BigQuant support exchange explains a possible source of confusion in backtests: the platform’s `hold_days` setting defines a build-up period during which the strategy can buy, and does not itself require each purchased stock to remain in the portfolio…

BacktestingPortfolio constructionExecution
Stratmill research code

This Rust example configures a live trading bot for the BTCUSDT futures instrument on Bybit and invokes a separate grid-trading routine. It registers instrument precision and market-depth settings, installs an error handler for connection, order, and custom…

CryptoFuturesGrid tradingExecution
vn.py community

A VeighNa community question asks whether contracts can be screened by indicator values and displayed as a list. The reply proposes using the portfolio strategy module to create a strategy instance, subscribe it to a defined range of contracts, and apply the…

FuturesTechnical indicatorsExecution
MQL5 code base

The document explains how to set stop-loss (SL) and take-profit (TP) levels for open orders. Traders can specify each level as a distance in pips from the current price or as a particular price. When both formats are provided for the same level, the pip…

ExecutionRisk management
MQL5 code base

This document describes an Expert Advisor that monitors an account for trades and trade modifications, including actions made manually or by other EAs. When it detects a change, it can send the trade information over the web to a server or web application…

ExecutionMarket microstructure
MQL5 code base

The document describes a trading panel that applies across symbols and magic numbers. It provides three position-management actions: close every position, close only losing positions whose loss exceeds a chosen threshold, or close only profitable positions…

Risk managementExecution
SuperMind

This short-term stock screen selects shares whose amplitude exceeds 1, that appeared on the prior day’s Dragon-Tiger trading list, and whose reported buy amount exceeds sell amount. It then ranks qualifying names by a capital-strength proxy, illustrated with…

EquitiesEvent-drivenExecutionVolatility
FMZ forum

This beginner-oriented guide distinguishes algorithmic trading from quantitative, automated, and high-frequency trading. It describes algorithmic trading as expressing a trading idea in an algorithm that can be tested and then executed manually or…

Machine learningStatisticsBacktestingExecution
TqSdk

This guide explains how to use a target-position scheduler to execute a sequence of position-adjustment tasks. A table specifies each task’s duration, desired net position, and pricing mode: pause, passive quote, active quote, or a custom price function.…

FuturesExecutionMarket microstructure
MQL5 code base

This research tool estimates the bid and ask as separate time series, fitting local quadratic curves to each side of the quote. It reports position, velocity, acceleration, standard errors, z-scores, and an estimated turning time across three event-count…

Market microstructureStatisticsExecutionBacktesting
MQL5 code base

This MT5 trade-copying program uses a master account to supply trades and one or more slave accounts to receive them. The stated features include copying from multiple providers to one slave, independently enabling stop-loss, take-profit, and pending-order…

ExecutionPosition sizingRisk managementMarket microstructure
WonderTrader

This overview catalogs Python examples for the WonderTrader framework, including CTA strategies, futures and stock backtests, futures arbitrage, optimization, reinforcement learning, and high-frequency trading. It names Dual Thrust as a sample strategy used…

FuturesEquitiesHigh-frequency tradingArbitrage
MQL5 code base

This Expert Advisor is described as targeting large, rapid market moves. It identifies a possible breakout using built-in calculations for volatility, trend formation, and entry timing. When a position becomes profitable, the system adds to it and…

BreakoutTrend followingVolatilityPosition sizing
vn.py community

This forum exchange explains why a VeighNa user may receive two order callbacks that both appear as “submitting” and share an order number, even though their timestamps differ. The reply attributes this to distinct status updates from the underlying CTP…

ExecutionMarket microstructure