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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
QuantRocket
7 documents
Lumibot strategies
7 documents
Awesome Quant
1 documents

Search the library

4,194 documents

BigQuant

This study constructs equity selection factors from trade by trade data to measure aggressive buying. It aggregates transactions into minute level buying and selling amounts, then derives buying share and buying intensity measures. The proposed factors can…

EquitiesFactor investingMarket microstructureBacktesting
SuperMind

The proposed screen targets mainland Chinese stocks using three characteristics: price amplitude above one, circulating market value above 10 billion yuan, and a shareholding-concentration measure described as below 20 percent. The article frames these…

EquitiesChina marketsVolatilityFactor investing
MQL5 code base

The article describes a framework for identifying crowded trading and distinguishing a bubble’s buildup from its unwinding. It estimates asset clustering from covariance and principal components, using the concentration of sector returns in important…

EquitiesFactor investingPortfolio constructionStatistics
vn.py community

This post presents a Chinese equity screening idea that combines a MACD value above zero with year-over-year net profit growth between 20% and 100%, framed around 2021. It explains the intent as pairing price momentum with a fundamental growth filter. The…

China marketsEquitiesMomentumTechnical indicators
SuperMind

This article describes a stock screen that combines turnover between 3% and 12%, a newly formed KDJ golden cross, and revenue in 2021 more than 1.1 times revenue in 2018. The proposed logic blends a measure of trading activity, a technical signal, and a…

EquitiesChina marketsTechnical indicatorsFactor investing
BigQuant

This report examines shifts in China’s A-share market and argues that both industry fundamentals and market style help explain relative sector returns. It describes a stepwise regression that attributes sector performance to beta, company size, cyclicality,…

China marketsEquitiesFactor investingStatistics
BigQuant

This research note evaluates 31 quality factors for stock selection in Hong Kong equities and compares their effectiveness with results in mainland A-shares. Twelve factors are reported as notably effective, particularly measures tied to operating cash flow…

EquitiesFactor investingStatisticsBacktesting
BigQuant

This Chinese-language weekly report presents a cautious near-term market view after large-weight industries weakened relative to smaller industries. It describes an industry allocation signal favoring market-cap-weighted exposure, which would reduce exposure…

EquitiesMomentumVolatilityFactor investing
BigQuant

This report is presented as the opening installment in a series on fundamental quantitative stock selection, focused on the lithium battery industry chain. Its stated aim is to combine fundamental information with traditional multi-factor selection,…

EquitiesChina marketsFactor investing
BigQuant

The document introduces Altman's Z-score as a composite financial-risk measure built from five ratios: working capital, retained earnings, earnings before interest and taxes, market equity relative to liabilities, and sales, each scaled against assets except…

EquitiesChina marketsFactor investingBacktesting
BigQuant

This research review examines momentum in China’s A-share market as institutional ownership and analyst attention have grown. It compares traditional lookback returns with measures that account for price paths, remove limit-up days, use earnings announcement…

EquitiesChina marketsMomentumFactor investing
BigQuant

This research summary examines how earnings forecasts can improve equity valuation and stock selection in China’s A-share market. It argues that historical return on equity alone has limited selection value there, while substituting forecast earnings for…

EquitiesChina marketsFactor investingStatistics
SuperMind

This Chinese-language post describes an A-share stock screen that ranks shares by capital strength, then selects the five highest by the day’s auction amount. It also filters for companies whose 2021 revenue divided by 2018 revenue exceeds 1.1, which the…

EquitiesChina marketsFactor investing
SuperMind

This note describes an equity screen that combines daily price movement with company profitability and a Bollinger Band condition. It seeks stocks with an amplitude above 1, return on equity above 15% for five consecutive years, and a close between the…

EquitiesTechnical indicatorsFactor investing
BigQuant

This submission describes a composite stock factor combining three ranked measures: three-year net profit growth, the inverse of summed turnover over five periods, and the inverse of five-period trading-amount variability. The intended profile is high growth…

EquitiesFactor investingStatisticsRisk management
SuperMind

This community post outlines a China A-share stock screen that excludes Beijing-listed companies and selects stocks with turnover between 3% and 12% and a positive but limited recent price gain. It then proposes refining the candidates using net profit…

EquitiesChina marketsMomentumFactor investing
BigQuant

The document reviews research on whether investor sentiment helps explain stock return anomalies or appears predictive because of spurious regression. Persistent predictors can seem to forecast returns in finite samples when expected returns also vary over…

SentimentStatisticsFactor investingEquities
BigQuant

This research summary examines high-frequency equity factors built from minute bars, tick data, and transaction-level records. The factors capture intraday skewness, downside volatility, reversals, late-session trading, price-volume relationships,…

EquitiesChina marketsHigh-frequency tradingFactor investing
MQL5 code base

This research summary explains a dynamic firm model in which companies can expand or shrink their operating scale, but face adjustment costs. Expansion and contraction options alter exposure to productivity shocks: the ability to reduce scale can buffer…

EquitiesFactor investingPortfolio constructionStatistics
BigQuant

The report treats corporate events as equity style factors and evaluates them within a multi-factor research framework. It describes differences in event prevalence across industries and relationships between event factors: private placements and dividends…

EquitiesFactor investingEvent-drivenStatistics
BigQuant

This Chinese-language article describes a customizable stock-selection strategy built around five rules, mainly seeking shares that appear oversold and stable, with some rules intended to identify possible rallies. It distinguishes rule-based coding from an…

EquitiesMean reversionBacktestingFactor investing
SuperMind

The document describes a Chinese A-share screening approach for Shenzhen main-board stocks. It selects shares with amplitude above 1, price-to-earnings ratios from 0 to 29.01, price-to-book ratios from 0 to 3.11, market capitalization below 10 billion yuan,…

EquitiesChina marketsFactor investingTechnical indicators
BigQuant

This A-share stock-selection approach combines an earnings-surprise proxy with the price response to earnings news. Instead of comparing reported profit with a numerical consensus estimate, it analyzes analyst research-report titles for wording that signals…

EquitiesChina marketsEvent-drivenMomentum
SuperMind

This strategy rebalances on the first trading day of each month, removes special-treatment stocks and shares listed on the STAR Market or Beijing Stock Exchange, then invests equally in the 30 stocks with the smallest market capitalizations. It has no…

EquitiesChina marketsFactor investingPortfolio construction