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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-selection proposal requires RSI below 65, seven consecutive sessions in which the close is no higher than the open, and positive large-order net fund flows during the afternoon trading session. Its example implementation also sets an…

EquitiesChina marketsMomentumTechnical indicators
BigQuant

This research note summarizes evidence that changes in the wording and structure of company filings can contain information about future operating performance and equity returns. The underlying study compares the text of SEC annual and quarterly reports with…

EquitiesUS marketsSentimentStatistics
SuperMind

This stock screen combines three conditions: a 14 period RSI below 65, displayed bid volume greater than ask volume, and a bullish engulfing pattern. The article frames the combination as a way to select shares with relatively favorable technical and order…

EquitiesTechnical indicatorsSentimentRisk management
SuperMind

This note describes a daily A-share screening rule combining three filters: membership in the metaverse sector, a positive institutional-flow measure, and a top-five ranking by the day’s auction amount. The intended pool emphasizes active stocks and uses…

China marketsEquitiesSentimentMarket microstructure
SuperMind

This proposed stock screen combines three conditions: amplitude above one, a shortening negative MACD histogram on a 15-minute chart, and an auction-period return between minus two and five. The accompanying rationale treats larger amplitude as a way to find…

EquitiesTechnical indicatorsMomentumSentiment
SuperMind

This note presents a stock screen using RSI below 65, a positive product of daily price change and large-order net volume, and exclusion of stocks that hit the daily price limit on the prior session. It frames these conditions as a way to combine a momentum…

China marketsEquitiesTechnical indicatorsSentiment
SuperMind

This short-term stock screen looks for three conditions: an intraday range above 1% of the prior close, afternoon large-order net inflow, and a daily maximum decline between 4% and 5%. The document frames the combination as a way to locate stocks that have…

EquitiesMean reversionTechnical indicatorsSentiment
BigQuant

This April 2020 market note combines a long-term trend assessment, short-term liquidity view, sector preferences, and tracking of A-share fund flows. It says a market breadth model had turned bearish and describes weakening turnover and a declining stock of…

China marketsEquitiesStatisticsRisk management
BigQuant

This summary of a Changjiang Securities study explains a stock-selection factor based on the balance between active and passive buying. Active buying occurs when an investor’s order trades against displayed sell orders; passive buying places a limit order…

EquitiesSentimentFactor investingStatistics
SuperMind

This post describes a stock screen combining a daily amplitude condition, membership in a robotics-related concept, a market-capitalization ceiling, and a run of consecutive declining sessions. It outlines how those filters could be combined in a…

EquitiesTechnical indicatorsSentimentRisk management
MQL5 code base

The Smart Money Index (SMI) is presented as an intraday indicator for interpreting market sentiment through price behavior at different points in the trading session. Its premise is that news-sensitive traders may react strongly near the open, while more…

SentimentTechnical indicatorsMarket microstructure
SuperMind

The document describes a stock screen that combines three conditions: daily price amplitude above a threshold, MACD above its zero line, and positive net buying attributed to major participants during the opening auction. The intended rationale is to find…

EquitiesTechnical indicatorsMomentumSentiment
SuperMind

This Chinese stock-selection proposal looks for shares with amplitude above 1, a prior-day appearance on the trading leaderboard, and a pattern described as an engulfing or reversal move. The rationale is that a wide range may signal short-term opportunity,…

EquitiesChina marketsVolatilityTechnical indicators
SuperMind

This document outlines an equity screen combining three conditions: membership in the metaverse theme, positive net buying attributed to major participants during the opening auction, and bid-side displayed volume greater than ask-side volume. Its rationale…

EquitiesChina marketsMarket microstructureSentiment
SuperMind

This document describes a Chinese A-share screening rule focused on the metaverse theme and pre-open auction activity. It selects stocks whose indicated 9:25 price is less than 6% above the previous close, with positive auction movement and specified buying…

EquitiesChina marketsMarket microstructureSentiment
BigQuant

The document gives brief examples of using large-scale and unconventional data to inform investment research. Satellite images of retail and office parking areas are described as a way to estimate business activity, while satellite monitoring of shipping is…

Multi-assetSentimentMachine learning
BigQuant

This article discusses how to manage strategy exposure during changing market conditions. It contrasts concentrating capital in one stock with spreading risk across positions or strategies, noting that concentration can produce sharp gains as well as large…

EquitiesRisk managementPosition sizingSentiment
BigQuant

This brief Chinese-language strategy notice describes a minute-frequency approach to pursuing stocks that reach their daily price limits. It says the model monitors three dimensions across the market: concept or theme popularity, capital flows, and price…

EquitiesChina marketsMomentumBreakout
SuperMind

This stock screen selects Shanghai-listed shares whose codes begin with 60, whose turnover rate is between 3% and 12%, and whose afternoon large-order buying is at least as strong as selling. The accompanying example checks turnover and large-order fields,…

EquitiesChina marketsSentimentMarket microstructure
SuperMind

This Chinese stock-selection post proposes screening for shares with an amplitude above 1 and large-order net volume above 0.05 for at least three consecutive days, then ranking candidates by popularity. It frames amplitude as a price-movement measure and…

EquitiesTechnical indicatorsSentimentRisk management
SuperMind

The document proposes selecting securities with an amplitude threshold after three consecutive limit-up sessions, then ranking candidates by market attention or trading activity. The rationale is that repeated limit-ups indicate strong short-term buying…

China marketsEquitiesMomentumSentiment
BigQuant

The document describes a stock-price forecasting study that compares a Kalman filter, XGBoost, and a hybrid that uses XGBoost to select features before passing them to a Kalman filter. Inputs include price and volume data, accounting measures, and quarterly…

EquitiesMachine learningStatisticsSentiment
SuperMind

This article outlines a stock screen using three conditions: daily high-low amplitude above 1%, weekly MACD above its zero line, and first-level bid volume greater than first-level ask volume. The intended combination uses price movement and trend indicators…

EquitiesChina marketsTechnical indicatorsMarket microstructure
SuperMind

This stock selection article proposes screening for turnover between 3% and 12%, three consecutive declining sessions, and relatively strong fund flow. The intent is to find shares that have recently weakened while still showing a favorable capital-flow…

EquitiesChina marketsTechnical indicatorsSentiment