Skip to content

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
Lumibot strategies
7 documents
QuantRocket
7 documents
Awesome Quant
1 documents

Search the library

12,226 documents

SuperMind

The article outlines an equity screen combining price amplitude above a stated threshold, rising lows as a sign of an improving base, and a ranking by stock or industry attention. It includes example formula logic and Python-like pseudocode, with the latter…

EquitiesTechnical indicatorsMomentumRisk management
SuperMind

This proposed equity screen selects companies with price amplitude above one percent, market capitalization within 10 billion, positive average net profit, and a current low below the previous session’s low. The article’s example code extends those…

EquitiesTechnical indicatorsRisk management
SuperMind

This Chinese stock-selection proposal combines three filters: price amplitude above one, a rounded chart pattern, and a nonempty name for outstanding convertible bonds. A referenced indicator formula expresses the amplitude and chart-shape conditions, while…

EquitiesTechnical indicatorsRisk management
SuperMind

This stock-selection method screens companies in the metaverse industry using three simultaneous bullish crossovers: MACD above its signal line, the 5-day moving average above the 10-day average, and the 5-day average above the 20-day average. It also…

EquitiesTechnical indicatorsMomentumChina markets
SuperMind

This code example demonstrates a data workflow for a FinRL stock-trading project. It fetches a single stock’s price history through both yfinance and FinRL’s Yahoo downloader, then downloads a Dow 30 universe over configured training and trading periods. A…

EquitiesMachine learningBacktestingStatistics
SuperMind

This stock-selection example combines three filters: RSI below 65, revenue in 2021 more than 1.1 times its 2018 level, and an opening price within 6% of the prior close. It proposes selecting the first N qualifying stocks and holding them for one year. The…

China marketsEquitiesTechnical indicatorsSentiment
SuperMind

The proposed Chinese equity screen selects stocks classified in the metaverse industry when the open is near a ten-day moving average and the 2019 dividend ratio exceeds 25%. The post presents a formula-style version and a Python example. It frames…

EquitiesChina marketsTechnical indicatorsFactor investing
SuperMind

The document proposes a Chinese equity screening rule combining three chart conditions: price amplitude above a threshold, a rounded price pattern, and three consecutive declining closes. It interprets the amplitude condition as a way to find active stocks,…

China marketsEquitiesTechnical indicatorsMean reversion
SuperMind

This Chinese equity screen selects companies in the beverage and alcohol import-export industry when turnover falls within a specified band and the opening price is near the ten-day moving average of closing prices. The post describes the approach as…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This note describes a stock screen that combines technical conditions with a basic growth measure. It proposes selecting stocks with at least five aligned moving averages, ranking them by net large-order volume, and retaining those whose revenue in 2021 was…

EquitiesTechnical indicatorsMomentumRisk management
SuperMind

This note presents a simple Chinese equity screen for companies classified in the metaverse industry. It selects stocks above a stated scale threshold that appeared on the previous day's exchange trading list, using industry membership, a financial size…

EquitiesChina marketsEvent-driven
SuperMind

This Chinese equity screen selects stocks with daily amplitude above 1, a reversal or engulfing-style price pattern, and circulating market capitalization above 10 billion yuan. The article describes these filters as a mix of technical conditions and a size…

China marketsEquitiesTechnical indicatorsMean reversion
SuperMind

This Chinese equity screening proposal combines a daily amplitude threshold above 1, a top-five rank by the day’s auction amount, and a closing price above its five-day moving average. It interprets large amplitude and strong auction activity as signs of…

China marketsEquitiesTechnical indicatorsMomentum
SuperMind

This article explains industry rotation in China’s A-share market, describing how economic cycles, policy, fundamentals, and herding can cause leadership to shift across sectors. It outlines a momentum approach that ranks industry indexes by weighted returns…

China marketsEquitiesMomentumTrend following
SuperMind

This stock-selection method screens for companies listed in 2021, with turnover between 3% and 12%, and a price shape described as rounded over the previous 20 days. The article frames turnover and listing year as basic filters, then adds a recent…

EquitiesTechnical indicatorsMomentumChina markets
SuperMind

This stock screen combines three conditions: a 14-period RSI below 65, first-level bid volume greater than ask volume, and a dividend ratio above 25% based on 2019 data. The article presents these filters as a way to combine a technical indicator, order-book…

EquitiesTechnical indicatorsSentimentRisk management
SuperMind

This post describes a Chinese-equity screening rule that combines membership in the metaverse theme with positive net buying attributed to major participants during the opening auction. It further limits candidates to Shenzhen main-board stocks using…

EquitiesChina marketsMomentumFactor investing
SuperMind

This article outlines a Chinese stock selection screen using daily price range, market capitalization, profitability, and MACD. The initial rules look for stocks whose high-to-low range exceeds 1%, whose market value is below 10 billion yuan, whose net…

EquitiesChina marketsTechnical indicatorsMean reversion
SuperMind

This Chinese-language article describes a mainland China stock screen combining technical and fundamental filters. It selects main-board shares with RSI below 65, a daily gain above 1%, market capitalization below 10 billion yuan, and positive net profit.…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This Chinese equity screening proposal combines trading activity with a past-event filter. It ranks stocks by volume ratio and selects the top 100, treating a higher ratio as a sign of stronger investor attention or fund activity. It also requires stocks to…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

This stock selection rule combines four daily conditions: price range relative to the close, at least two limit-up moves within a rolling 500-day window, current volume above 10,000 lots, and an opening price above the prior close. The document describes…

China marketsEquitiesTechnical indicatorsMomentum
SuperMind

This post describes a stock screen combining daily price amplitude above 1, positive institutional money flow, and a 10-day return greater than zero but below 35%. Its example indicator logic aggregates positive net institutional flow across five periods,…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

This post outlines a Chinese A-share screening rule using three conditions: current trading volume above 10,000 lots, an opening price above the prior close, and a positive 10-day return below 35%. It presents the volume condition as a proxy for stronger…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

This stock selection idea combines membership in the metaverse concept group with two technical conditions: the close is above the prior day’s low, and the KDJ indicator has just produced a bullish K-over-D cross while its J value is rising. The document…

EquitiesTechnical indicatorsMomentumPosition sizing