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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

12,226 documents

SuperMind

This introductory overview explains quantitative trading as the conversion of market observations and decision rules into mathematical models and computer programs. It outlines a typical process: analyze historical price, volume, and timing data; design a…

StatisticsBacktestingExecutionMean reversion
SuperMind

The document describes a Chinese A-share stock screen focused on the metaverse sector. It selects stocks whose opening price is less than 6% above the prior close, whose price chart resembles a rounded arc, and whose Bollinger Band width is below 0.05. The…

EquitiesChina marketsTechnical indicatorsVolatility
SuperMind

This Chinese stock-selection note describes a screen that ranks companies by descending capital strength, limits turnover to a band above 2% and below 9%, and selects firms with market capitalization under 10 billion yuan that are not loss-making. It…

EquitiesChina marketsTechnical indicatorsRisk management
SuperMind

This stock-selection example combines a historical dividend payout filter with a liquidity screen. It selects shares whose 2019 dividend payout ratio exceeded 25% and whose prior-day turnover was above 60 million, then ranks candidates by a stated measure of…

EquitiesChina marketsFactor investingTechnical indicators
SuperMind

This note proposes a simple screen for Chinese stocks associated with the metaverse theme. It selects companies with a circulating share count no greater than 5.5 billion and a share price around 18.5 yuan; the sample code uses a price interval from 18 to 19…

EquitiesChina marketsPortfolio constructionStatistics
SuperMind

This Chinese equity screening idea combines a daily price range filter, a history of limit-up moves, and year-over-year earnings-per-share growth. It seeks stocks with an amplitude above one percent, at least two qualifying limit-up events within the…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

This note describes a Chinese equity screen for stocks associated with the metaverse theme. It combines positive institutional activity with a ranking by capital strength, which the article also describes as selecting larger stocks. The proposed process…

EquitiesChina marketsMarket microstructureStatistics
SuperMind

This document presents a stock-selection idea that combines membership in the metaverse theme with a rising 30-day moving average and a positive weekly-price condition. It frames the combination as a way to find equities with recent strength and an upward…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

This document outlines an equity screen combining a daily high-low range threshold, five consecutive years of return on equity above 15%, and institutional ownership. Its refined rule translates the institutional buying idea into a minimum holding of 100,000…

EquitiesFactor investingRisk management
SuperMind

The document describes a Chinese stock selection approach that targets companies associated with the metaverse, requires a positive institutional-flow measure, and excludes stocks described as having hit the daily price limit on the prior day. The proposed…

EquitiesChina marketsSentimentEvent-driven
SuperMind

This Chinese equities selection rule screens for turnover between 3% and 12%, a circulating market value between 5 billion and 10 billion yuan, and a positive weekly price bar. The document presents these filters as a way to focus on actively traded stocks…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

The document describes a Chinese equities screen using turnover between 3% and 12%, a positive product of price change and net large-order flow, and a limit on tradable shares. It frames these filters as a way to combine trading activity, capital flows,…

EquitiesChina marketsMomentumMarket microstructure
SuperMind

This note proposes selecting Chinese stocks in the metaverse theme that appeared on the prior day’s Dragon and Tiger List and had an amplitude greater than 1. It frames the thematic classification, unusual market attention, and price range as clues about…

EquitiesChina marketsVolatilitySentiment
SuperMind

This note describes a Chinese A-share screening idea that combines three conditions: at least five moving averages converge, the stock ranks by large-order net volume, and its 9:25 quoted gain is below 6%. The author interprets these as signs of price…

EquitiesChina marketsTechnical indicatorsMarket microstructure
SuperMind

This Chinese equity screen selects stocks associated with the metaverse concept, requires the 30-day moving average to be rising, and looks for seven consecutive down sessions. The proposed interpretation is that a favorable medium-term trend may coexist…

China marketsEquitiesTechnical indicatorsMean reversion
SuperMind

This stock screen combines three conditions: amplitude above 1, a shrinking negative MACD histogram on a 15-minute interval, and previous-day opening-auction turnover above 0.26. The rationale is to find shares with meaningful price movement, improving…

China marketsEquitiesTechnical indicatorsMomentum
SuperMind

This community post describes a short-term stock selection idea combining a gap-up condition, net inflow attributed to major investors, low valuation, and a small market-cap filter. The author presents the approach as a compact model, and commenters…

China marketsEquitiesBreakoutBacktesting
SuperMind

The proposed screen selects stocks with turnover between 3% and 12%, an external-to-internal trading volume ratio above 1.3, and return on equity above 15% across five consecutive years. It combines a liquidity and trading-activity filter with a measure of…

EquitiesFactor investingTechnical indicators
SuperMind

This Chinese-language post proposes a stock screen combining daily price range, an estimate of prior-day major-investor control based on money flow, and association with the metaverse theme. It describes the approach as using both technical and fundamental…

China marketsEquitiesMomentumTechnical indicators
SuperMind

This Chinese stock screening note proposes selecting shares with MACD above zero, a specified company concept, and a reported ownership concentration ratio above 21%. Its stated rationale is that positive MACD may indicate upward momentum, while the company…

EquitiesTechnical indicatorsMomentumChina markets
SuperMind

This short-term A-share screen combines three conditions: RSI below 65, parent-attributable net profit growth above 20% and no more than 100%, and a positive daily MACD reading. The document presents RSI as a way to find stocks that may have rebound…

China marketsEquitiesTechnical indicatorsMomentum
SuperMind

This A-share screening rule combines a turnover range of 3% to 12%, a rising DEA signal, and a close above the previous session’s low. The document explains the turnover filter as a way to focus on actively traded stocks and treats rising DEA and the price…

China marketsEquitiesTechnical indicatorsMomentum
SuperMind

This document describes a Chinese equity screen for stocks classified in the metaverse theme. It selects shares trading above their five-day moving average and where the KDJ indicator has just formed a bullish cross. The proposed logic combines a thematic…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This brief introduction contrasts linear regression of factor data with decision trees. Its central point is that market returns may not relate to factors in a simple linear way, so a tree-based method is worth considering when studying how factors…

EquitiesMachine learningFactor investingStatistics