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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

4,510 documents

SuperMind

This Chinese stock screen combines a price-range condition with a turnover and opening-auction volume measure. It seeks stocks whose amplitude exceeds 1 and whose prior-day turnover multiplied by the ratio of today’s auction volume to yesterday’s volume…

EquitiesChina marketsTechnical indicatorsSentiment
SuperMind

This post describes a Chinese equity screen based on turnover ranges, a recent limit-up event within a lookback period, and additional turnover constraints. It interprets turnover as a measure of trading activity and a recent limit-up as a possible sign of…

EquitiesChina marketsSentimentTechnical indicators
SuperMind

This post describes a Chinese equity screening idea combining daily price amplitude, a share price below a stated threshold, and a ratio based on the previous day’s turnover and the current auction volume relative to the previous day’s volume. The proposed…

EquitiesChina marketsVolatilitySentiment
SuperMind

This community post outlines a Chinese stock screen combining four conditions: daily amplitude above one percent, membership in the robotics concept group, circulating market capitalization below 10 billion yuan, and a high ranking on large-order net flow.…

EquitiesChina marketsSentimentTechnical indicators
SuperMind

This post proposes buying stocks whose daily high-low range divided by the open exceeds one, whose institutional-flow measure is positive, and which are not flagged by its prior-day limit-up filter. It explains range and fund-flow readings as indicators of…

EquitiesChina marketsTechnical indicatorsSentiment
SuperMind

This post describes a short-term A-share screen combining three conditions: today’s accumulation ratio must exceed five percent, the outside-to-inside trading volume ratio must be above 1.3, and the stock must have had more than two limit-up days in the…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This post proposes selecting mainland Chinese main-board stocks associated with robotics, with turnover between 3% and 12%, float market capitalization below 10 billion yuan, and prior-day actual turnover between 3% and 28%. It treats turnover as a rough…

EquitiesChina marketsMomentumSentiment
SuperMind

This incomplete strategy sketch combines three proposed stock filters: a 2019 dividend payout ratio above 25%, net inflows from large orders during the afternoon, and convergence among at least five moving averages. It explains convergence as possible…

EquitiesChina marketsTechnical indicatorsSentiment
SuperMind

This note describes a Chinese stock screen combining an investor accumulation measure above 5% with a condition that the stock’s gain by 9:25 is below 6%. It interprets accumulation as a sign of buying interest and the limited early gain as a possible sign…

EquitiesChina marketsSentimentRisk management
SuperMind

This post describes a Chinese equity screen combining positive institutional activity, a threshold for the day's increase in holdings, and a 2021 date filter. It interprets the holding-change measure as a sign of buying interest and positive institutional…

EquitiesFactor investingSentimentBacktesting
SuperMind

This Chinese stock-screening idea combines three conditions: a market capitalization below 10 billion yuan, no recent company losses, and a prior-day 9:15 matching price at the daily limit down. It also requires the stock’s increase in holdings for the…

EquitiesChina marketsSentimentRisk management
Amberdata research

The newsletter reviews market reactions to the U.S. election, including a drop in equity volatility and expectations for possible regulatory changes affecting crypto. It connects those themes to options positioning: traders were concentrated in calls up to a…

CryptoOptionsVolatilitySentiment
SuperMind

This Chinese stock-screening note describes selecting companies in the metaverse concept group when auction-period main-fund net buying is positive, then ranking qualifying names by stock heat. It frames the concept membership as a way to focus on a popular…

EquitiesChina marketsSentimentExecution
BigQuant

The document summarizes research on whether investors react differently to corporate announcements made before major holidays. The study examines US stock repurchases, equity issuance, mergers, and quarterly earnings announcements from 1984 to 2012,…

EquitiesEvent-drivenSentimentStatistics
Amberdata research

This market snapshot argues that Bitcoin could benefit from anticipated U.S. regulatory changes, a proposed strategic reserve, supportive congressional sentiment, and lower interest rates. It combines this policy outlook with several market indicators: a…

CryptoMomentumOn-chain dataSentiment
SuperMind

This Chinese stock-screening post combines a metaverse-sector filter with auction-period buying signals. It looks for positive net buying attributed to major participants, large orders executed at sharply higher prices during the auction, and a threshold for…

EquitiesChina marketsMarket microstructureSentiment
Amberdata research

This market snapshot reviews BTC and ETH price movements, spot trading activity, ETF flows, DeFi activity, and Bitcoin holder behavior ahead of the April 2024 halving. It frames resistance levels and falling exchange volume and ETF demand as signs that…

CryptoSpot marketsOn-chain dataDeFi
Kraken Learn

The document explains the Crypto Fear and Greed Index as a daily sentiment gauge scored from 0 to 100. It outlines its components: volatility and market momentum or volume each contribute 25%, social media and surveys 15% each, and Bitcoin dominance and…

CryptoSentimentTechnical indicatorsBacktesting
SuperMind

This post describes an equity screen using an RSI below a stated threshold, the product of percentage price change and very-large-order net flow, and a rising 30-day moving average. The intended combination blends a momentum-related price trend with a…

EquitiesTechnical indicatorsMomentumTrend following
SuperMind

This Chinese-language post outlines an equity screen combining a daily price-range threshold, a ranking based on net large-order activity, and first-level bid volume exceeding ask volume. It presents these conditions as a way to find active stocks with…

EquitiesSentimentMarket microstructureTechnical indicators
BigQuant

This research review describes a study of whether year-over-year changes in company filings contain information about future stock returns and business performance. It compares filings using four text-similarity measures, sorts stocks by similarity, and…

EquitiesSentimentMachine learningFactor investing
SuperMind

This screen focuses on stocks classified in the metaverse industry. It requires a newly formed bullish KDJ crossover and prior-day auction turnover above 0.26. The article presents the crossover as a technical signal and auction turnover as a measure of…

EquitiesTechnical indicatorsMomentumSentiment
SuperMind

This stock-screening proposal combines a turnover range of 3% to 12%, greater displayed buy-one volume than sell-one volume, and a positive outstanding convertible-bond balance. Its rationale is that moderate trading activity may indicate liquidity, buy-side…

EquitiesMarket microstructureSentimentChina markets
SuperMind

This Chinese-language post describes a stock screen for the metaverse theme in China’s A-share market. It combines membership in the sector with a price-change filter and a ranking based on net large-order flow. The stated logic seeks stocks with an opening…

EquitiesChina marketsSentimentTechnical indicators