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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

16,761 documents

Amberdata research

This educational article develops a hypothetical Bitcoin strategy in Backtrader using market prices, volume, and a stock-to-flow valuation series. It enters when the MACD signal crosses above zero while a short-to-long simple moving-average comparison still…

CryptoMomentumBacktesting
MQL5 code base

This document describes a semaphore-style indicator built from two OsMA calculations applied to the price series’ Open and Close values. It produces a signal when the difference between those indicator values changes sign. The signal timing therefore follows…

Technical indicatorsMomentumBacktesting
Zipline

This small Zipline example selects Apple shares during initialization and configures per-share commission and volume-share slippage. On every data callback, it submits an order for ten shares and records the current share price. The example therefore…

EquitiesExecutionBacktestingRisk management
MQL5 code base

The iSarX4 indicator displays four Parabolic SAR calculations at once. It sets the first calculation’s step from a starting parameter, then increases the step for each subsequent calculation by a fixed increment; all four share a maximum acceleration…

Technical indicatorsTrend followingBacktesting
MQL5 code base

This document describes an Expert Advisor that trades signals from the XFisher_org_v1 oscillator. A signal is formed when a bar closes with a crossing between the oscillator’s main and signal lines, accompanied by a change in the indicator cloud’s color. The…

ForexTechnical indicatorsBacktesting
BigQuant

The post shares a one-minute grid trading strategy that uses the prior day’s close as a center price and divides prices into bands. It opens an initial position, then changes holdings when the price moves between grid regions, subject to cash and…

Grid tradingBacktestingPosition sizing
MQL5 code base

This Expert Advisor trades a price channel during configured hours. At the start of the trading window, it places limit orders at both channel boundaries and sets take-profit levels toward the opposite boundary. It uses no stop loss. At the end of the…

ForexMean reversionExecutionBacktesting
BigQuant

This example describes a two-stock pairs strategy based on the assumed long-term relationship between securities. It regresses one stock's price on the other's, then standardizes the regression residual using its recent mean and standard deviation. When the…

EquitiesPairs tradingMean reversionBacktesting
SuperMind

This Chinese-language post describes an equity screen that combines daily amplitude above 1%, a positive but limited ten-day gain, and a morning star candlestick pattern. Its rationale is to seek active stocks that have risen recently without becoming…

EquitiesTechnical indicatorsMomentumChina markets
NautilusTrader

This example demonstrates how signal delivery behaves when an actor publishes another signal from inside its own signal callback. A backtest engine runs a publishing actor, an optional second subscriber, and an initial publisher. The first actor prints…

BacktestingExecution
ProRealCode

This indicator combines a trailing Average True Range stop with the Average Directional Index. It selects between wider and narrower ATR multipliers according to whether ADX is rising or falling, with an optional threshold rule that applies the narrower…

Technical indicatorsTrend followingVolatilityRisk management
SuperMind

The document describes a Chinese stock-selection idea combining three conditions: a reported increase in buying position, parent-company net profit growth within a stated range, and a shortening MACD histogram on a 15-minute chart. It interprets the first…

China marketsEquitiesMomentumTechnical indicators
QTPyLib

The document explains how QTPyLib’s Blotter connects to Interactive Brokers through TWS or IB Gateway, receives market data, and distributes updates to algorithms through ZeroMQ. It can also store tick and minute data in MySQL for later research and…

BacktestingExecutionMarket microstructure
Kraken Learn

The document introduces AI driven crypto trading bots and describes their intended role: analyze market data, identify patterns, and adjust trading decisions as conditions change. It contrasts these systems with discretionary trading, emphasizing continuous…

CryptoMachine learningBacktestingRisk management
BigQuant

The document describes a Chinese equity strategy that screens for stocks trading below book value, excludes flagged or suspended shares and recent listings, then selects the smallest companies by market capitalization. It equally weights ten holdings and…

EquitiesChina marketsFactor investingBacktesting
Awesome Systematic Trading

The strategy ranks currency futures using purchasing power parity data as a currency-value signal. Its description proposes a universe of roughly ten to twenty currencies, estimates fair values using OECD PPP figures adjusted with monthly CPI and…

ForexFuturesFactor investingBacktesting
MQL5 code base

This document explains how to combine Forexite’s daily MetaStock-format quote files into a single instrument history file for import into MetaTrader 4. The workflow downloads and unpacks daily archives, then runs a script with the instrument name and date…

ForexCommoditiesBacktesting
vn.py community

A VeighNa forum question asks how stock transaction costs are represented in backtests when sell-side stamp duty has a minimum charge. The question distinguishes commissions charged on both buys and sells from stamp duty charged only on sales, and asks…

EquitiesBacktestingExecution
BigQuant

This research note studies return skewness as a cross-sectional factor for commodity futures. It tests long-short and long-only portfolios across all contracts, agricultural contracts, and non-agricultural contracts, then explores lookback choices, ATR-based…

FuturesCommoditiesFactor investingVolatility
SuperMind

This proposed Chinese equity screen combines a turnover range of three to twelve percent with concept and valuation filters. It targets stocks associated with robotics and beverage or alcohol-related business, limits circulating market value to below one…

China marketsEquitiesFactor investingStatistics
SuperMind

This stock-selection proposal combines a price-range filter with weekly trend indicators. It seeks shares whose high-to-low range exceeds one percent of the previous close, whose weekly MACD is above zero, and whose five-period moving average crosses above…

China marketsEquitiesMomentumTechnical indicators
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