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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
WonderTrader
14 documents
Alphalens
14 documents
backtesting.py
11 documents
Technical Analysis
9 documents
QTPyLib
8 documents
Lumibot strategies
7 documents
QuantRocket
7 documents
Awesome Quant
1 documents

Search the library

12,226 documents

SuperMind

This document proposes screening Chinese stocks for daily turnover between 3% and 12%, three consecutive declining sessions, and a bullish morning star candlestick pattern on the current day. It presents the combination as a way to use trading activity and…

EquitiesChina marketsTechnical indicatorsMarket microstructure
SuperMind

This document describes a Chinese equity screen for stocks in the metaverse industry. It combines three bullish technical crossovers—MACD crossing its signal line, a 5-period moving average crossing above the 10-period average, and the 5-period average…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This Chinese-language post proposes an equity screen using four conditions: daily amplitude above a threshold, a prior-day opening auction match at the limit-down price, a product of absolute price change and large-order net volume, and current volume above…

EquitiesChina marketsTechnical indicatorsSentiment
SuperMind

The document describes a simple Chinese equity screen combining daily price range, a closing price condition, and a large-order net-flow ranking. It presents the rules both as a conceptual selection recipe and as examples of indicator logic, then says to…

EquitiesChina marketsTechnical indicatorsMarket microstructure
SuperMind

This Chinese stock-screening proposal combines relative trading activity, historical limit-up frequency, and the opening gain measured at 9:25. Its initial rules select stocks ranked among the top 500 by volume ratio, with at least two limit-up sessions in…

China marketsEquitiesTechnical indicatorsMomentum
SuperMind

This A-share selection method combines amplitude above 1, a weekly five-period moving average crossing above the ten-period average, and a ranking based on large-order net volume. The article presents these as complementary signals: price movement, an…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This A-share screen combines MACD above zero, an upward-moving average condition, and turnover between 2% and 9%. The article interprets positive MACD and rising averages as signs of upward direction, while the turnover band is intended to avoid both very…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This short-term A-share screening method looks for stocks with amplitude above 1, a circulating share count no greater than 5.5 billion, and a volume ratio between 1.5 and 6. The article frames these filters as a way to find stocks with meaningful price…

EquitiesChina marketsVolatilityTechnical indicators
SuperMind

This A-share screen combines daily amplitude above 1 with a positive weekly MACD reading and a listing history longer than one year. The article then adds valuation and profitability constraints: price-to-earnings below 20, price-to-book below 3, and return…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This post describes a Chinese equity screening idea that combines membership in the metaverse concept with positive net buying by large participants during the opening auction and a prior-day measure of main-fund control. Its stated interpretation requires…

EquitiesChina marketsSentimentFactor investing
SuperMind

The post describes a simple random stock-selection process: buy ten stocks, hold them for five days, sell the two weakest performers, then randomly choose two replacements and repeat. It frames the strategy as a challenge to expert stock picking and notes…

EquitiesPortfolio constructionBacktesting
SuperMind

The document explains impermanent loss for decentralized exchange liquidity providers. AMMs maintain pool balances through pricing formulas; when an asset’s market price moves relative to its pool partner, arbitrage trades restore alignment and change the…

CryptoDeFiMarket makingRisk management
SuperMind

This stock screen combines three criteria: rank equities by capital strength, require yesterday’s turnover rate to exceed 8%, and select companies whose 2019 dividend payout ratio exceeded 25%. The accompanying explanation treats capital strength as an…

EquitiesChina marketsFactor investing
SuperMind

This post describes a stock screen combining two signals: an increase in holdings above 5% and moving averages that diverge upward. It interprets the holdings measure as possible recent buying interest and the moving-average pattern as an upward trend. The…

EquitiesTechnical indicatorsMomentumRisk management
SuperMind

This short-term A-share screening idea combines three filters: a prior-session price range above a stated threshold, appearance on the previous day’s trading activity list, and a high ranking in large-order net flow. The post interprets the combination as a…

EquitiesChina marketsMomentumMarket microstructure
SuperMind

This note describes an A-share screen that combines a metaverse industry filter, a stated free-float threshold, and a three-candle pattern described as a morning star. It presents the pattern as a possible reversal setup after a pullback, and suggests adding…

EquitiesChina marketsTechnical indicatorsMean reversion
SuperMind

This proposed Chinese stock screen selects companies classified in the metaverse theme, with prior-day actual turnover between 3% and 28%, and a listing or issuance date in 2021. The post treats the industry classification as a growth-oriented universe…

EquitiesChina marketsTechnical indicatorsRisk management
SuperMind

This proposed stock screen combines three filters: turnover between 3% and 12%, a newly formed KDJ bullish cross, and a positive institutional net-purchase measure. The post frames turnover as a liquidity and activity filter, the KDJ signal as a trend or…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This proposed Chinese equity screen focuses on stocks classified in the metaverse theme. It combines a price condition involving the five-day moving average with a directional filter: the product of the stock’s daily return and a measure of net large-order…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

The document proposes a stock screen combining intraday amplitude above 1, excluding ST-designated stocks, selection before 10 a.m., a named five-step limit-up method, and floating shares no greater than 5.5 billion. It describes float as a measure related…

EquitiesBreakoutTechnical indicatorsRisk management
SuperMind

The document describes a short-term stock screen combining a 14-period RSI below 65, three consecutive declining sessions, and a daily price change between -5% and 2.6%. It frames the conditions as a way to find weak stocks that may be positioned for a…

EquitiesTechnical indicatorsMean reversionBacktesting
SuperMind

This Chinese equity screening strategy selects stocks with turnover between 3% and 12%, three consecutive declining sessions, and return on equity above 15% for five consecutive years. The article presents the ROE filter as a way to favor firms with…

EquitiesFactor investingTechnical indicatorsRisk management
SuperMind

This document describes a Chinese equity screening rule combining daily amplitude above a threshold, higher successive lows, and upward separation among short, medium, and longer moving averages. Its indicator example compares five-, ten-, and twenty-period…

EquitiesTechnical indicatorsTrend followingRisk management