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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
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

12,226 documents

SuperMind

This Chinese stock-screening note describes a rule that combines daily price amplitude, a bounded turnover rate, and a ranking based on large-order net flow. Its rationale is to find shares with meaningful price movement and trading activity while using net…

EquitiesChina marketsVolatilityMarket microstructure
SuperMind

This document describes a Chinese equity screening rule combining daily amplitude above a threshold, a positive weekly MACD histogram, and exclusion of stocks that hit their daily price limit on the previous day. It presents versions of the rule for a…

China marketsEquitiesTechnical indicatorsMomentum
SuperMind

This document outlines a daily stock screen for Chinese A-shares. It selects stocks whose MACD is above zero, ranks qualifying names by market attention from highest to lowest, and requires positive net buying by major participants during the opening…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

The document outlines an A-share stock screen combining a 3%–12% turnover range, a market capitalization below 10 billion yuan, a profitability filter, and a signal described as main-fund control on the previous day. It also provides a sample indicator…

EquitiesChina marketsTechnical indicatorsRisk management
SuperMind

This stock-selection idea filters for RSI below 65 and a circulating market value between 5 billion and 10 billion yuan, then ranks qualifying stocks by that day’s auction amount and selects the top five. The article frames RSI as a short-term overbought or…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This document describes a screen for Shenzhen main-board stocks combining daily price movement, opening price relative to the 10-day moving average, and valuation limits. It seeks stocks with amplitude above 1%, an open within 5% of the moving average,…

EquitiesChina marketsTechnical indicatorsFactor investing
SuperMind

The document proposes a Chinese-equity selection screen combining prior-session price amplitude, a maximum free-float share count, and a price-position condition called “reverse covering.” Its examples operationalize that last condition as a close at or…

EquitiesTechnical indicatorsMean reversionChina markets
SuperMind

The proposed Chinese equity screen selects stocks with turnover between 3% and 12%, a newly formed KDJ bullish crossover, and at least one limit-up move during the preceding month. The article frames these conditions as a combination of trading activity, a…

China marketsEquitiesTechnical indicatorsMomentum
SuperMind

The document describes a China A-share screening idea focused on main-board stocks in the metaverse sector. It selects candidates whose volume ratio is above 1.5 and below 6, and whose daily price gain exceeds 1%. The stated rationale is to find stocks with…

EquitiesMomentumTechnical indicatorsChina markets
SuperMind

This post proposes screening Chinese metaverse-sector equities with circulating market capitalization above 10 billion yuan after their prior-day 9:15 opening-match price reached the limit-down level. The rationale is an expectation that stocks hit by an…

EquitiesChina marketsEvent-drivenMean reversion
SuperMind

This Chinese-language post describes an equity screen combining price amplitude above 1, a 2019 dividend ratio above 25%, market capitalization below 10 billion yuan, and positive profits. It frames the criteria as a way to find smaller companies with…

EquitiesChina marketsVolatilityFactor investing
SuperMind

This analysis describes the CSI Dividend Index and the Bosera CSI Dividend ETF that tracks it. The index selects 100 Shanghai and Shenzhen A-shares with high average after-tax cash dividend yields over the previous two years, then weights constituents by…

EquitiesChina marketsFactor investingPortfolio construction
SuperMind

This stock-selection method combines price range, recent large gains, and a trading-activity proxy. It looks for stocks with amplitude above 1, at least one daily gain of 10% or more during the past 25 trading days, and an external-to-internal trading volume…

EquitiesChina marketsMomentumVolatility
SuperMind

This short-term A-share screen combines metaverse sector membership with an early-session price condition and a fundamental filter. It selects stocks whose 9:25 gain is below 6% and whose year-over-year growth in net profit attributable to parent-company…

EquitiesChina marketsMomentumRisk management
SuperMind

This document presents a Chinese A-share screening rule that selects stocks with turnover between 3% and 12%, excludes Beijing-listed shares, and requires the institutional-flow indicator to be positive. It provides a corresponding platform formula and a…

EquitiesChina marketsMarket microstructureRisk management
SuperMind

This document describes a short-term A-share stock screen combining membership in the Metaverse theme with an opening-price condition and a measure based on price change and large-order trading activity. The stated rules require the previous close relative…

EquitiesChina marketsTechnical indicatorsMarket microstructure
SuperMind

This stock-screening idea combines three filters: companies without losses, a market capitalization below a stated ceiling, and a newly formed KDJ golden cross. It also ranks candidates by a measure of capital strength derived from turnover and trading…

EquitiesTechnical indicatorsMomentumChina markets
SuperMind

This document proposes screening stocks for amplitude above 1, MACD above its zero line, and first-level bid volume greater than first-level ask volume. It frames amplitude and MACD as technical strength filters and the order-book comparison as a way to…

EquitiesTechnical indicatorsMarket microstructure
SuperMind

This document describes a Chinese equity screen for stocks listed in 2021, with turnover between 3% and 12% and tradable share capital no greater than 5.5 billion shares. It gives a platform formula and a Python example that retrieves listed stocks, applies…

EquitiesChina marketsTechnical indicators
SuperMind

This document describes an equity screen combining price amplitude above 1, a daily control indicator above 21, and a positive daily MACD. It presents these conditions as a way to identify stocks with technical support and provides sample implementations for…

EquitiesTechnical indicatorsRisk management
SuperMind

This stock-selection idea screens Chinese A shares for turnover between 3% and 12%, a newly formed KDJ golden cross, and a K value below 20. The turnover band is intended to select stocks with some trading activity, while the low K value is treated as an…

China marketsEquitiesTechnical indicatorsMean reversion
SuperMind

This screen targets Chinese stocks in the metaverse category whose closing price is above the five-day moving average and whose large-order net activity exceeds 0.05 for three consecutive days. The article interprets the price condition as short-term…

EquitiesChina marketsMomentumTechnical indicators