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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
Binance API docs
45 documents
Quantopian lectures
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

BigQuant

This forum post reports a difference in how a trading platform handles a day counter in development backtests versus simulated trading. The counter behaves as expected in backtests but remains at one in simulation, prompting questions about whether the…

BacktestingExecutionRisk management
vn.py community

This forum exchange investigates why a VeighNa trading script fails to find contracts even though the graphical Studio client receives market data. Participants explain that a strategy module may start before contract queries finish, and that simply adding a…

FuturesExecutionMarket microstructure
vn.py community

This short forum exchange discusses a timing problem in a 15-minute bar strategy: a signal is generated when a bar closes during a trading break, so an order submitted immediately may fail because the market is closed. The question also raises the…

ExecutionMarket microstructureRisk management
Lumibot

This example outlines a daily workflow that combines browser-based research, trade review, and optional publication of a trade receipt. A research agent visits a configured site, captures evidence and a screenshot, and returns claims, contradictions, and…

EquitiesExecutionRisk managementBacktesting
MQL5 code base

This EURUSD strategy places pending orders around the previous day's high and low, seeking to enter in the direction of a range break. The described setup places a buy above the prior high and a sell below the prior low, adjusted for spread. Both orders are…

ForexBreakoutExecutionRisk management
FMZ forum

The article distinguishes planned stop losses from sudden losses that occur when a stop cannot be executed at its intended level. It describes fixed stops based on a price or loss limit, trailing stops that follow conditions such as moving averages or…

FuturesRisk managementExecutionPosition sizing
vn.py

This VeighNa guide compares database choices for storing trading data, including embedded SQLite, relational systems such as MySQL and PostgreSQL, and non-SQL options such as MongoDB, InfluxDB, DolphinDB, Arctic, and LevelDB. It describes their broad storage…

Multi-assetMarket microstructureExecutionBacktesting
MQL5 code base

This short note describes a basic trading-platform script that records close prices alongside date and time fields, then writes the records to a comma-separated file in the platform’s default files folder. The intended use is to make price observations…

EquitiesExecution
MQL5 code base

This brief indicator description explains how tick events can be collected from a trading terminal into an array and shown on screen. Each displayed tick can carry a flag identifying the type of event: a change to bid, ask, last traded price, or volume, or…

Market microstructureHigh-frequency tradingExecution
NautilusTrader

This document explains how a trading system’s in-memory cache holds recent market data and current execution state for strategies and other components. Data engines update the cache as they process events; for quotes, trades, and bars, successful writes…

ExecutionMarket microstructureRisk management
Amberdata research

This report examines Bitcoin spot liquidity across six market regimes, focusing on the October liquidation cascade. It tracks order book depth at several distances from mid-price, exchange volume shares, and a composite resilience measure based on depth…

CryptoMarket microstructureExecutionRisk management
BigQuant

This platform guide describes two ways to organize data preparation and simulated trading. In one workflow, a separate task cleans and stores factors, then a trading task consumes its output. In the other, one task first prepares and saves the data and then…

ExecutionBacktesting
MQL5 code base

This Expert Advisor monitors open positions as a group and can close them when combined profit reaches a configured take-profit level or combined loss reaches a stop-loss threshold. The thresholds can be measured as percentages or in the account’s deposit…

Risk managementPosition sizingExecution
BigQuant

The article discusses three reported Chinese equity-market changes: wider daily price limits for risk-warning stocks, expanded after-hours fixed-price trading, and revised ChiNext listing standards that place more weight on growth and research investment. It…

China marketsEquitiesExecutionMarket microstructure
FMZ forum

This tutorial explains how to collect market data for many trading pairs through aggregated exchange endpoints and organize it for a multi-symbol strategy. Using Binance futures and Huobi spot as examples, it shows how to normalize different response formats…

CryptoFuturesSpot marketsExecution
Hummingbot docs

These release notes describe updates to Hummingbot trading infrastructure, including four new perpetual futures connectors and changes to Gateway’s decentralized exchange integration. The connector additions support order and position workflows across…

Perpetual futuresBacktestingExecutionMarket making
MQL5 code base

The document describes a library that lets an MT5 strategy run in the tester’s mathematical mode. Its workflow first runs an Expert Advisor to save tick data, then uses that data in a later test. The article shows example logs for both stages and says the…

BacktestingExecution
BigQuant

This strategy selects stocks that open above the previous close and have a five-day closing-price average above the ten-day average. Among qualifying stocks, it ranks by price-to-earnings ratio in ascending order and chooses the first ten; purchases are…

EquitiesMomentumTechnical indicatorsBacktesting
QTPyLib

This tutorial explains how to bring market data from external providers or existing CSV files into QTPyLib for strategy backtesting. It outlines supported download routes for daily and intraday bars from Yahoo Finance, Google, and Interactive Brokers, with…

BacktestingFuturesExecution
MQL5 code base

The document describes an Expert Advisor for manual trading that applies stop-loss and take-profit levels to market and pending orders. Its controls include when trailing begins, the trailing distance from the current price, the profit threshold for moving a…

ForexExecutionRisk managementPosition sizing
WonderTrader

This code describes a Dual Thrust style breakout strategy applied across a list of instruments. It calculates a reference range from prior bars using the highest high and close and the lowest low and close, then scales that range by separate parameters to…

FuturesBreakoutTechnical indicatorsExecution
OctoBot

This guide describes how to make an OctoBot webhook reachable by an external signal provider such as TradingView. It uses Tailscale Funnel to publish the webhook port through a stable HTTPS address without configuring router port forwarding. The setup…

ExecutionMarket microstructure
BigQuant

This article outlines a workflow for adding intraday monitoring and automated execution to a BigQuant equity strategy. Its premise is that factor calculations may produce a next-day trading plan only after the market closes, leaving no mechanism to react to…

EquitiesExecutionMarket microstructureChina markets
vn.py community

A VeighNa community discussion investigates a CTA backtest in which the recorded position appears to exceed the strategy's actual holdings. The trader reports opening seven contracts, then seeing several stop orders close quantities that add up to more than…

FuturesBacktestingExecution