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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 Chinese-language post outlines a stock screen combining a price-amplitude condition, a K-line condition below 20, and the previous close above the 250-day moving average. It presents reference implementations for a charting formula and Python, where the…

EquitiesTechnical indicatorsChina markets
SuperMind

This Chinese equities screen selects companies with intraday range of at least one percent, market capitalization no greater than 10 billion yuan, and positive net profit. It also requires three moving-average crossovers: the 5-day average above the 10-day,…

China marketsEquitiesTechnical indicatorsBreakout
SuperMind

This Chinese stock-selection idea combines a relative strength index below 65, a condition based on multiplying price change by net volume from very large orders, and a positive price-to-earnings ratio. The article presents the mix as a way to include both…

China marketsEquitiesTechnical indicatorsMarket microstructure
SuperMind

This Chinese equities screen combines three conditions: a shrinking negative MACD histogram on a 15-minute chart, at least two limit-up sessions within the prior 500 days, and convergence among at least five moving averages. The article interprets…

China marketsEquitiesTechnical indicatorsMomentum
SuperMind

The proposed screen seeks five non-ST Chinese stocks before 10:00 using price amplitude above 1 and prior-day trading value above 60 million, then ranks candidates by current percentage change. The article describes these conditions as a way to focus on…

EquitiesChina marketsVolatilityMomentum
SuperMind

This proposed Chinese stock screen selects companies associated with the metaverse theme, requires prior-day turnover above 8%, and applies opening-auction conditions involving price change and large and extra-large buy orders. The stated rule requires…

EquitiesChina marketsMarket microstructureExecution
SuperMind

This stock screen combines a positive MACD condition with a share price below 12 yuan and a recent high criterion described as the stock's high being the highest over two days. It proposes screening before the trading session, although the reference Python…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

The document describes a stock screen combining three conditions: amplitude above 1, three consecutive limit-up sessions through the prior day, and a price below 12 yuan. It presents the pattern as a way to find active, high-attention stocks and gives a code…

EquitiesMomentumChina marketsTechnical indicators
SuperMind

This proposed A-share screen combines three filters: membership in the metaverse theme, positive net buying attributed to major participants during the opening auction, and an upward spread in moving averages. The stated moving-average rule compares the…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

This A-share stock screen combines a turnover range of 3% to 12%, a positive 10-day gain below 35%, and at least one limit-up event in the previous month. The article characterizes the setup as a momentum-oriented search for stocks that have recently shown…

EquitiesChina marketsMomentumBreakout
SuperMind

This document outlines a Chinese stock screen combining price amplitude above 1, return on equity above 15% for five consecutive years, and a stock code beginning with 60. It frames amplitude as a volatility filter, persistent ROE as a profitability filter,…

EquitiesChina marketsFactor investingTechnical indicators
SuperMind

This stock selection approach combines a price range condition, a turnover and volume activity measure, and year-over-year net profit growth. It screens for stocks with amplitude above one, a product of the prior day's turnover rate and the current auction…

EquitiesChina marketsTechnical indicatorsFactor investing
SuperMind

This Chinese equity screening idea selects stocks with daily amplitude above 1, a listing history longer than three years, and a rising DEA indicator. The rationale is that larger price ranges may coincide with greater trading activity, while excluding…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

The document describes a Chinese stock selection rule that seeks shares with turnover between 3% and 12%, listed in 2021, and associated with the metaverse theme. It presents this as a way to narrow the universe to newer listings in a targeted sector. The…

EquitiesChina marketsTechnical indicatorsFactor investing
SuperMind

This screening proposal combines a daily price-range condition, consistently high return on equity over five years, and an opening price near short-term moving averages. The suggested refinement places the open between the prior ten-day and twenty-day…

EquitiesFactor investingTechnical indicatorsStatistics
SuperMind

This stock-screening example combines a metaverse concept filter with an upward-sloping thirty-day moving average and a weekly five-day moving average crossing above the ten-day average. It frames the conditions as a way to find stocks with both sector…

EquitiesTechnical indicatorsMomentumChina markets
SuperMind

This Chinese equity selection rule filters for turnover between 3% and 12%, a positive product of the stock’s price change and super-large-order net volume, and a gain below 6% during the final five minutes before the close. The article presents the…

EquitiesChina marketsMarket microstructureTechnical indicators
SuperMind

This note describes a Chinese equity screen combining daily price range, large-order net buying, and year-over-year net profit growth attributable to shareholders of the parent. Its stated final rule requires amplitude above 1, a high large-order net volume…

EquitiesChina marketsFactor investingTechnical indicators
SuperMind

This stock selection rule screens for RSI below 65, a K indicator below 20, and circulating market value between 5 billion and 10 billion yuan. The article presents the combination as a way to identify stocks with weak technical readings while restricting…

EquitiesTechnical indicatorsChina marketsMean reversion
SuperMind

The article explains naive Bayes classification and applies it to a stock selection strategy. The classifier estimates the probability of each outcome from historical labeled observations, assuming features are conditionally independent and equally…

EquitiesMachine learningTechnical indicatorsBacktesting
SuperMind

This stock-selection proposal combines turnover between 3% and 12%, a positive ten-day gain below 35%, and a weekly close crossing above its 30-week moving average. The turnover band is intended to select actively traded shares, the return filter limits…

EquitiesTechnical indicatorsTrend followingBacktesting
SuperMind

The document describes a simple stock screen combining three conditions: daily amplitude above 1%, the current high matching the highest high over two days, and a stock code beginning with 60. The first two conditions target recent price movement and a…

EquitiesTechnical indicatorsMomentum