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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

27 documents

vn.py

This guide explains the CTA strategy workflow in VeighNa Fusion, from connecting to the trading gateway and creating a strategy instance to configuring parameters, initializing, starting, and stopping it. Each instance has its own target contract, parameter…

FuturesExecutionRisk managementBacktesting
vn.py

The document explains how to use a market-depth trading interface for live, manual intraday trading in a single futures contract. After connecting a trading gateway and opening a contract chart, the ladder displays price levels, bid and ask quantities, best…

FuturesExecutionMarket microstructure
vn.py

This guide explains how to enable a trading gateway in VeighNa Station or load one from a startup script, connect through VeighNa Trader, and view account, position, order, trade, and contract information. Gateway settings can be edited in the application or…

FuturesOptionsEquitiesExecution
vn.py

This guide explains how to construct, monitor, and trade synthetic spreads in the VeighNa SpreadTrading module. A spread can combine several contract legs using a formula, including pricing legs that are not traded, which supports relationships involving…

FuturesCommoditiesArbitragePairs trading
vn.py

This code example outlines a vn.py workflow for backtesting an ATR-RSI strategy on a Chinese equity index futures contract. It configures the instrument, minute interval, historical dates, commissions, slippage, contract size, tick size, and starting…

FuturesBacktestingTechnical indicatorsStatistics
vn.py

This guide explains how to use Fusion’s data center to download domestic futures one-minute history into a local database, inspect existing records, update them, and build continuous contracts. Users first load the available instruments, choose an exchange,…

FuturesBacktestingChina markets
vn.py

This guide explains how to use historical backtests and parameter optimization as research checks before deploying a trading strategy. It outlines setup choices such as the instrument and exchange, bar interval, date range, fees, slippage, contract…

BacktestingRisk managementStatisticsFutures
vn.py

This guide describes an execution module that runs algorithms in a separate process, lets users configure and monitor orders, and supports manual order routing across multiple accounts. Its five examples illustrate different execution behaviors: TWAP divides…

ExecutionMarket microstructureFuturesHigh-frequency trading
vn.py

This guide explains how VeighNa Elite Trader’s CTA template can filter synthetic bars received outside configured trading sessions, preventing out-of-session data from affecting strategy indicators. It describes obtaining a sample filter configuration…

FuturesMarket microstructureExecution
vn.py

The document demonstrates a vn.py workflow for backtesting a statistical arbitrage strategy on a two-leg futures spread. It defines a spread as the price difference between two futures contracts, sets the backtest interval and trading assumptions, loads…

FuturesPairs tradingArbitrageBacktesting
vn.py

This notebook demonstrates a basic command-line workflow for operating a trading engine through a CTP gateway. It loads connection settings, initializes the engine, and connects to the server. The example then queries available contracts, account balances,…

FuturesExecution
vn.py

The document explains how to connect VeighNa trading software to Excel through its ExcelRtd module and PyXLL. After installing and configuring the commercial PyXLL add-in, users can enable the module in VeighNa Station or load it in a startup script. The…

FuturesExecutionMarket microstructure
vn.py

This document explains a portfolio management interface for monitoring strategy-level positions, trades, and profit and loss during the trading day. It treats each order source, such as manual trading or a strategy module, as a separate portfolio and…

FuturesPortfolio constructionRisk management
vn.py

This example demonstrates a portfolio-strategy backtest for a pair trading strategy on two Dalian Commodity Exchange continuous contracts. It configures minute data over a specified historical interval and supplies commission rates, slippage, contract sizes,…

FuturesPairs tradingBacktestingExecution
vn.py

This Python example describes a process manager for a CTA futures strategy using vn.py and the CTP gateway. A parent process checks the clock and launches a child process during configured daytime and overnight trading windows. The child creates the event…

FuturesExecutionChina markets
vn.py

This document explains a graphical workflow for researching CTA strategies with historical data. It covers downloading market data, configuring a backtest with instrument details and trading costs, and reviewing equity, drawdown, daily profit and loss, and…

BacktestingFuturesStatisticsRisk management
vn.py

This guide explains how to use VeighNa’s CTA strategy module to load strategy classes, create instances, initialize them with historical data, and start or stop automated trading. It describes how instances can trade different futures contracts with separate…

FuturesExecutionRisk managementBacktesting
vn.py

This example runs two existing futures strategies independently, using separate instruments, date ranges, trading costs, contract sizes, and capital settings. It then adds their result data frames, removes missing rows, and passes the combined data to a…

FuturesBacktestingPortfolio construction
vn.py

This documentation explains how to load and operate VeighNa’s CTA strategy module. It covers adding strategy instances, selecting contracts and parameters, loading historical data, restoring saved variables, subscribing to market data, and enabling automated…

FuturesExecutionRisk management
vn.py

This reference catalogs calculation functions available in the VeighNa Elite Trader CTA module. It groups common tools by their required inputs and outputs, covering moving averages, momentum and rate-of-change measures, volatility, trend strength and…

Technical indicatorsFuturesExecution
vn.py

The document explains how historical market data supports CTA strategy initialization, backtests, parameter optimization, and research. It outlines importing externally sourced data into a local environment and recommends checking file reliability, timestamp…

BacktestingFuturesRisk management
vn.py

This guide describes a user interface for running execution algorithms and explains how to configure an order’s instrument, side, price, quantity, duration, interval, and open-or-close instruction. It focuses on order execution rather than deciding what to…

ExecutionMarket microstructureFuturesRisk management
vn.py

This operational guide explains how to connect a VeighNa Fusion account to a CTP futures interface and check that contract lookup, market-data subscription, and order functions are working. It outlines prerequisites such as obtaining the correct broker…

FuturesExecutionMarket microstructure