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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 post describes a Chinese stock-selection screen combining three conditions: current amplitude above a threshold, a prior-day 9:15 indicative auction price at the limit-down price, and prior-day turnover above 60 million. It frames these filters as a way…

EquitiesChina marketsSentimentTechnical indicators
SuperMind

This overview explains chip distribution as the estimated quantity of shares held across different purchase-price ranges. A distribution chart is presented as a way to infer where investors’ costs cluster, how concentrated holdings may be, and how those…

EquitiesMarket microstructureSentimentTechnical indicators
Amberdata research

This market commentary connects falling U.S. inflation readings and a surprise credit downgrade with changing risk appetite across traditional and crypto markets. It describes stronger altcoin performance as Bitcoin dominance eased, and highlights bullish…

CryptoOptionsVolatilitySentiment
SuperMind

This Chinese-language post presents a stock-selection screen for companies in the metaverse sector. It requires yesterday’s turnover rate to exceed 8% and current best-bid quantity to be greater than best-ask quantity. The author interprets the order-book…

China marketsEquitiesMarket microstructureSentiment
SuperMind

This stock screen targets companies classified in the metaverse theme, requiring prior-day actual turnover between 3% and 28%, then ranks qualifying names by individual stock popularity. The note describes the theme classification and turnover measure, but…

EquitiesChina marketsSentimentRisk management
SuperMind

This post describes a stock screen using turnover between 3% and 12%, a positive change in the KDJ K line, and descending ranking by a stock heat measure. Its intended approach is to favor shares with rising momentum and greater attention among those meeting…

EquitiesChina marketsTechnical indicatorsMomentum
Amberdata research

This conference recap presents qualitative themes about institutional participation in digital assets. It reports that attendees observed broader participation by traditional financial institutions, and links growing interest to regulatory, market-structure,…

CryptoMarket microstructureSentimentMulti-asset
SuperMind

This short-term screening idea selects stocks classified in the metaverse theme during 2021, appearing on the previous day’s trading leaderboard, and showing a positive return over the prior ten days below 35 percent. The post presents leaderboard appearance…

China marketsEquitiesMomentumTechnical indicators
Lumibot

This proposed Chinese-equity screen combines three initial conditions: market capitalization below 10 billion yuan, no reported losses, and a daily increase in position share above five percent. It also uses the product of price change and large-order net…

China marketsEquitiesMomentumSentiment
SuperMind

This Chinese equity screen selects stocks associated with the metaverse theme, filters for prior-day actual turnover between specified bounds, and ranks candidates by large-order net buying activity. The proposed rationale is that moderate-to-high turnover…

EquitiesChina marketsSentimentExecution
BigQuant

The essay examines limits of using large language models and deep learning as autonomous trading decision makers. It contrasts their strength in finding patterns in historical data with the market researcher’s need to reason about current conditions, causal…

Machine learningStatisticsExecutionSentiment
SuperMind

The document proposes screening Chinese A-share stocks associated with the metaverse theme that appeared on the previous day’s Dragon-Tiger list and have an outside-to-inside volume ratio above 1.3. It interprets a high ratio as a sign of stronger buying…

China marketsEquitiesSentimentTechnical indicators
Amberdata research

This market snapshot examines a broad crypto selloff alongside macroeconomic and policy developments. It tracks spot prices, realized volatility, trading volume, open interest, funding, ETF flows, stablecoin supply, order-book depth, and DeFi liquidations.…

CryptoVolatilityPerpetual futuresMarket microstructure
SuperMind

This Chinese A-share screening idea combines three filters: a metaverse industry classification, positive institutional flow, and more than two limit-up days within a ten-day window. It aims to identify thematically focused stocks with positive institutional…

EquitiesChina marketsMomentumBreakout
SuperMind

This stock screen combines a 14-period RSI below 65, a positive product of daily percentage change and a measure of very large-order net inflow above 1, and negative returns across seven consecutive sessions. The stated rationale is to find stocks that have…

China marketsEquitiesMean reversionTechnical indicators
SuperMind

This document presents a Chinese stock screen built around three conditions: membership in the metaverse theme, positive net buying by major participants during the opening auction, and a fund-strength measure ranked from high to low. Its rationale is to…

EquitiesChina marketsMomentumSentiment
SuperMind

This note describes a Chinese equity screen requiring RSI below 65, positive afternoon large-order net inflow, and strong performance since 2021, with the stated final rule focusing on stocks in the top decile for both net inflows and cumulative gains. The…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

This selection idea combines three filters for mainland Chinese stocks: membership in the metaverse concept, positive net buying attributed to major traders during the auction, and prior-day actual turnover above 3% and no more than 28%. The stated rationale…

EquitiesChina marketsSentimentMarket microstructure
SuperMind

This Chinese equity screening example selects stocks listed in the current year, with turnover between 3% and 12%, and positive net buying by major participants during the opening auction. The article frames the turnover band as a way to focus on active,…

China marketsEquitiesSentimentMarket microstructure
BigQuant

This research note describes an equity timing framework that combines more than thirty indicators across liquidity, economic conditions, valuation, capital flows, technical signals, and investor sentiment. It aggregates the indicators into a score ranging…

EquitiesTechnical indicatorsSentimentStatistics
SuperMind

This Chinese-language article describes an A-share stock screen that selects companies classified in the metaverse sector, with circulating shares no greater than 5.5 billion and institutional flow above zero. It defines the flow measure as institutional net…

EquitiesChina marketsSentimentStatistics
SuperMind

This stock selection approach combines daily price range, persistent positive large-order net volume, and a signal that institutions are buying during price declines. The stated filters require an amplitude above 1 and large-order net volume above 0.05 for…

EquitiesTechnical indicatorsSentimentChina markets
SuperMind

This stock screen selects equities with MACD above zero, a positive price-to-earnings ratio, and a high ranking for net main-fund inflows on the previous day. The note frames these conditions as indicators of upward momentum, positive earnings valuation, and…

EquitiesMomentumTechnical indicatorsSentiment