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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
Quantpedia
86 documents
TqSdk
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
Lumibot strategies
7 documents
QuantRocket
7 documents
Awesome Quant
1 documents

Search the library

9,660 documents

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…

BacktestingExecutionMarket microstructureRisk management
Lumibot

This broker integration guide explains how LumiBot handles Bitunix USDT perpetual futures. It covers account funding, leverage requests, hedge-mode requirements, order precision, reduce-only closes, and historical candle retrieval. The integration does not…

CryptoFuturesPerpetual futuresExecution
OctoBot

This FAQ explains how OctoBot Cloud users can evaluate strategies and crypto baskets through paper trading with virtual funds, and says strategy performance is assessed periodically through historical backtesting. It notes that results vary with market…

CryptoBacktestingRisk managementExecution
MQL5 code base

This short description covers an Expert Advisor designed to close open positions according to a selected scope: all positions, only positions currently in profit, or only positions currently at a loss. The note credits the original idea to James Malwitz and…

Risk managementExecutionPosition sizing
FMZ guides

The guide outlines a basic structure for automated strategies in JavaScript, Python, Rust, and C++. A main loop repeatedly runs strategy logic, while a sleep interval controls polling frequency in live trading and playback speed in backtests. Its examples…

ExecutionBacktestingTechnical indicators
MQL5 code base

This Expert Advisor trades signals from an X-period candle channel system. A signal is generated when a bar closes after breaking through the channel, and the system can close an open position once it has been held longer than a configured time limit. The…

ForexBreakoutExecutionBacktesting
MQL5 code base

This indicator description explains a signal based on the intersection of three moving averages ordered from fastest to slowest. It separates arrows for crosses that occurred on an earlier bar from “ghost” arrows marking an intersection on the current bar.…

Technical indicatorsMomentumExecution
MQL5 code base

This Expert Advisor uses a moving average to generate directional trading signals. When the current ask is above the moving-average value from the prior bar, it signals a buy; when the current bid is below that value, it signals a sell. The description…

Technical indicatorsTrend followingExecutionRisk management
MQL5 code base

This document describes an Expert Advisor that opens trades when a bar closes and the TSI_CCI indicator cloud changes color. It identifies the signal timing and notes that the indicator file must be installed for the advisor to run. A trading library is…

ForexTechnical indicatorsBacktestingExecution
BigQuant

The document raises a practical trading question: how to enforce a minimum holding period using trading days rather than calendar days. Its example calculates elapsed time by subtracting the last rebalance date from the current date, which counts weekends…

ExecutionStatisticsBacktesting
Stratmill research code

This document introduces HftBacktest, a Rust framework for developing and running high-frequency trading and market-making strategies. Its backtesting approach replays tick-level market data and aims to model important execution effects, including feed…

High-frequency tradingMarket makingMarket microstructureBacktesting
MQL5 code base

This Expert Advisor tests a time-based breakout approach. At 15:00 Moscow time, it places a buy stop and a sell stop 100 points from the current price, with a 200-pip stop loss on each order and no take-profit target. If one order triggers, the other remains…

BreakoutExecutionRisk managementBacktesting
Amberdata research

This report reviews 2024 activity in centralized crypto spot and derivatives markets. It describes how exchange and asset trading volumes changed through the year, noting periods of high activity across major venues and tokens. It suggests using volume…

CryptoFuturesPerpetual futuresArbitrage
FMZ forum

This tutorial shows how to use a strategy interface to modify and inspect a running JavaScript trading program. The strategy polls an API for a command, extracts the text after a delimiter, logs the submitted expression, and passes it to JavaScript’s eval…

Execution
MQL5 code base

This document describes an alert-enabled signal indicator built around the classic Money Flow Index. It marks signals when the oscillator exits overbought or oversold territory, then adds configurable sound alerts, email messages, and mobile push…

Technical indicatorsForexExecution
Binance API docs

This documentation explains spot trading commissions as the combination of standard, tax, and special rates. It distinguishes account commission queries, which report current rates for a symbol and include maker, taker, buyer, and seller components, from…

CryptoSpot marketsExecutionRisk management
pysystemtrade

This example assembles a futures trend-following system on hourly data and shows how to choose among vanilla accounting, simulated market orders, and simulated limit orders. The system combines raw data, trading rules, forecast scaling and combination,…

FuturesTrend followingExecutionBacktesting
vn.py community

This short VeighNa forum exchange discusses running multiple strategies on the same instrument when one strategy places orders with position locking enabled. The question asks whether other strategies sharing the same PositionHolding object also need to use…

ExecutionPosition sizingPortfolio construction
Hummingbot docs

This overview explains Hummingbot executors as components that manage order lifecycles under conditions set by controllers using market data. It lists executor categories for positions, dollar-cost averaging, grids, arbitrage, time-weighted execution,…

ExecutionMarket makingDeFiSpot markets
vn.py community

This discussion addresses duplicated work in multi-signal trading systems when each signal independently processes ticks and bars using a bar generator and array manager. It recommends centralizing those components in the main strategy when signals use the…

Multi-assetTechnical indicatorsExecution
MQL5 code base

This brief note introduces standard named pipes as a way for developers to communicate with the MetaTrader 4 terminal environment without relying on potentially unsafe DLLs. It describes pipe access as operating through familiar file-style reads and writes,…

Execution
MQL5 code base

This framework outlines pre-trade checks for a robot sending a market buy order. It obtains the current ask and bid, computes optional stop-loss and take-profit levels, and adjusts those levels when they fall inside the broker’s minimum stop distance. It…

ExecutionRisk managementPosition sizing
MQL5 code base

This document describes an educational MetaTrader 5 panel for manually entering trades on hedging accounts. A trader chooses BUY or SELL; the panel sizes positions by a configured percentage risk and submits a broker-side stop loss with an optional…

Risk managementPosition sizingExecution
MQL5 code base

This indicator description focuses on supply and demand zones and their behavior over time. It reports the number of times zones are retested and identifies levels that switch roles, such as support becoming resistance or resistance becoming support. Users…

Technical indicatorsExecution