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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

79,386 documents

Amberdata research

The podcast account follows Jake Ostrovskis’s move from global macro trading into crypto OTC markets. It describes his focus on fair value and volatility dislocations, and the OTC desk’s role in arranging large or tailored trades across spot, options, CFDs,…

CryptoOptionsVolatilityMarket making
BigQuant

This document is a brief summary of an A-share quantitative market-timing report titled around the possibility that a lower open can offer an opportunity. It reports contemporaneous observations on sector strength, index valuations, sector relative…

EquitiesChina marketsTechnical indicatorsStatistics
SuperMind

This A-share selection rule combines three conditions: a daily range above 1%, weekly MACD above zero, and at least two limit-up events within a 500-day lookback. The document presents repeated limit-up moves as a possible sign of strength, with the range…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

This stock selection rule screens for A-shares with a daily high-low range above 1% and turnover between 2% and 9%. It combines a volatility measure with trading activity and a market classification filter. The document also sketches an implementation using…

EquitiesChina marketsVolatilityTechnical indicators
BigQuant

This research summary surveys dynamic allocation methods for equity style factors. It organizes the approaches by whether they use return information, risk information, or both, adapting methods originally used in broad asset allocation. The study first…

EquitiesChina marketsFactor investingPortfolio construction
BigQuant

This document explains how to combine absolute, time-series momentum with relative, cross-sectional momentum in a multi-asset portfolio. It describes a unified portfolio framework that treats each pair of instruments as a relative-momentum opportunity,…

FuturesMulti-assetMomentumTrend following
MQL5 code base

The Math-System indicator presents a set of target support and resistance levels for an anticipated price move. The document points readers to related Murrey Math indicators, placing this tool in a family of chart-based level systems. It states that the…

Technical indicatorsRisk management
SuperMind

The article describes an equity screen combining three conditions: membership in the metaverse theme, a prior-day close above the 250-day moving average, and a rising-bottom pattern. It explains the latter as a retest after a decline and rebound, where the…

EquitiesTechnical indicatorsChina marketsRisk management
MQL5 code base

This indicator visualizes a volume-weighted moving average as a cloud that fills the chart background. The moving average acts as the boundary separating the cloud’s colors, providing a visual reference for price movement around the average. It also displays…

Technical indicators
BigQuant

This report compares several Chinese language models as assistants for discovering equity liquidity factors over a specified historical period. Each model proposes data inputs and a formula built from trading volume, turnover, amount, or price. The author…

EquitiesChina marketsFactor investingMachine learning
BigQuant

This weekly report assesses the Chinese equity market after a rebound in early June 2022. Its timing framework compares 20-day and 120-day moving averages for a broad market index and combines their distance with a market breadth or “profit effect” measure.…

EquitiesChina marketsTechnical indicatorsTrend following
BigQuant

This article proposes six checks to run before deploying a strategy that has performed well in historical backtests. It recommends perturbing data with delays, missing observations, and outliers; scanning core parameters for broad regions of acceptable…

BacktestingRisk managementExecutionStatistics
Freqtrade

This Freqtrade strategy example applies an Almgren–Chriss style execution schedule to position entries and exits. It estimates a parameter called kappa from rolling price variability, candle range, and volume, using it to shape the fraction traded in each…

ExecutionMarket microstructureRisk managementTechnical indicators
BigQuant

This brief Chinese-language forum answer addresses how to use the data parameter in a quantitative trading workflow. It notes that scheduled functions receive both data and context as inputs, pointing readers toward the platform documentation for details.…

Technical indicatorsBacktesting
MQL5 code base

This document describes a MetaTrader 5 version of EMA Levels that can display indicator values from timeframes other than the active chart. It supports the platform’s timeframes and offers automatic second- and third-higher-timeframe choices that adjust when…

Technical indicators
SuperMind

This post proposes screening stocks in the metaverse industry using two conditions: price or average price above a five-day moving average, and prior-day auction turnover above 0.26. It interprets the moving-average condition as a short-term upward trend and…

EquitiesTechnical indicatorsMomentumChina markets
Amberdata research

This market snapshot links macroeconomic conditions with Bitcoin and Ethereum developments. It discusses strong US employment data and Federal Reserve expectations, compares reported outflows from Bitcoin ETFs with steadier Ethereum ETF flows, and reviews…

CryptoSentimentVolatility
SuperMind

This Chinese-language post presents an A-share screening rule that combines a 14-period RSI below 65, a ratio of outside-market to inside-market trading above 1.3, and a volume ratio between 1.5 and 6. It frames the order-flow ratio as a proxy for buying…

EquitiesTechnical indicatorsMomentumChina markets
Awesome Systematic Trading

This document describes an event-driven long strategy that combines corporate repurchase announcements with upcoming earnings dates. It screens US-listed stocks, excludes the smallest market-cap quartile, and looks for buyback announcements of at least 5% of…

EquitiesEvent-drivenPosition sizingBacktesting
SuperMind

This Chinese stock-selection strategy filters for an RSI below 65, circulating market capitalization between 5 billion and 10 billion yuan, and prior-day turnover above 8%. The accompanying Python example calculates a 14-period RSI, applies the three…

EquitiesTechnical indicatorsStatisticsChina markets
MQL5 code base

NDuet combines moving averages with a semaphore signal to guide trade timing. The two moving averages use different periods to define trend direction, while the semaphore indicator identifies a possible point to enter or settle a trade. The description says…

Technical indicatorsTrend following
BigQuant

This document summarizes a Chinese research report on measuring listed companies’ technological innovation capacity. It identifies factor construction and testing by industry as a central topic, alongside building an enhanced portfolio for a strategic…

China marketsEquitiesFactor investing
MQL5 code base

Super SAR combines Parabolic SAR direction changes with SuperTrend confirmation. Green or red arrows indicate a potential entry when SAR changes position and SuperTrend agrees. A gray arrow marks an SAR direction change without SuperTrend confirmation,…

Technical indicatorsTrend followingVolatility
MQL5 code base

This indicator summarizes trend direction across seven Blau stochastic indicators set to different timeframes. Each indicator is represented by a line whose color reflects whether its histogram is rising or falling: dark lime for growth and orange for…

Technical indicatorsMomentum