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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

22,592 documents

SuperMind

The document describes a stock screen requiring price amplitude above 1%, turnover greater than 2% and below 9%, and a 2019 dividend payout ratio above 25%. It presents amplitude and turnover as measures of market activity and uses the historical payout…

EquitiesChina marketsFactor investingRisk management
BigQuant

This market review describes a year of changing styles in Chinese equities: cyclical and growth themes led during the recovery, followed by a shift toward value later in the year. It argues that a high earnings base and flattening growth expectations could…

EquitiesChina marketsFactor investingMachine learning
SuperMind

This proposed Chinese mainland equity screen selects main-board stocks with a 14-period RSI below 65, a daily gain above 1%, and turnover between 3% and 12%. The accompanying examples show how to calculate RSI and daily returns, filter for listed shares…

EquitiesChina marketsTechnical indicatorsMean reversion
BigQuant

This industry-selection approach adapts William O’Neil’s CAN SLIM framework by calculating relative strength at the sector level. The report proposes a high relative-strength reading as an early screening signal for industries that may lead the market during…

EquitiesMomentumTechnical indicatorsChina markets
BigQuant

This study develops an equity factor for company competitiveness across four dimensions: technology, products, internal controls, and capacity to sustain and improve existing advantages. It combines measurable indicators from these areas, then adjusts the…

EquitiesFactor investingPortfolio constructionBacktesting
BigQuant

This equity-factor study compares several ways to measure illiquidity and examines whether less liquid stocks earn higher subsequent returns. Its microstructure measures are quoted spread, effective spread, and price-impact lambda; it also tests Amihud’s…

EquitiesFactor investingMarket microstructureStatistics
SuperMind

This A-share screening recipe combines three conditions: daily price amplitude above 1%, a nonempty name for an outstanding convertible bond, and return on equity above 15% for five consecutive years. It is intended to pair a price-movement filter with a…

China marketsEquitiesFactor investingRisk management
BigQuant

This article introduces trend following, mean reversion, arbitrage, and high-frequency trading, then argues that trend following is the most accessible of these approaches for individual A-share investors. It describes trend following as entering in the…

China marketsEquitiesTrend followingMean reversion
SuperMind

This note describes an A-share stock screen focused on the metaverse industry. It selects stocks with a volume ratio above 1.5 and below 6, a reversal-pattern measure above 0.5, and market capitalization between 1 billion and 10 billion yuan. The article…

China marketsEquitiesTechnical indicatorsMean reversion
SuperMind

The document describes an A-share stock screen combining three technical conditions: price amplitude above a threshold, MACD below zero two days earlier, and the 20-day moving average above the 120-day average. The moving-average relationship is intended to…

EquitiesChina marketsTechnical indicatorsTrend following
SuperMind

The document proposes a short-term stock screen combining three conditions: daily amplitude above 1, upward movement or divergence in moving averages, and appearance on the previous day’s 龙虎榜, a list of stocks with notable trading activity. It frames the…

China marketsEquitiesMomentumTechnical indicators
BigQuant

The document explains how to construct a DMA feature as the difference between a short-period and a long-period simple moving average. It identifies three inputs: the underlying price or feature, the short window, and the long window. Its worked example uses…

Technical indicatorsStatisticsEquities
SuperMind

This A-share screening rule requires turnover between 3% and 12%, an opening price within 5% of the 10-day moving average, and at least one session with a gain of 10% or more during the previous 25 trading sessions. The document frames these conditions as a…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This intraday A-share screen selects non-ST stocks with price amplitude above 1, ranks candidates by the day’s opening auction amount, and keeps the top five before 10 a.m. It also cites a “five-step limit-up” condition, expressed as a sequence of rising…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

This A-share screening method combines three price-based conditions: RSI below 65, seven consecutive sessions with down candles, and a positive gain below 35% over the latest 10 sessions. The document explains the intent as filtering for stocks that have not…

EquitiesChina marketsTechnical indicatorsMean reversion
SuperMind

This post outlines a Chinese stock screen requiring turnover within a specified band, a daily gain above a threshold, main-board listing, and minimum company size. Its stated rationale is to focus on actively traded stocks that are rising while avoiding very…

EquitiesTechnical indicatorsChina markets
ProRealCode

This charting indicator converts selected market capitalization levels into corresponding share prices. The user supplies shares outstanding in millions; the script multiplies that figure by the current price to estimate market capitalization, chooses a…

EquitiesTechnical indicators
SuperMind

This post describes a stock selection screen for Chinese equities. It selects stocks with a daily high-low range above a threshold, positive afternoon large-order net inflow, and exclusion of the STAR Market. It treats a wide range as a sign of greater price…

EquitiesVolatilityMarket microstructureTechnical indicators
BigQuant

This report examines whether price momentum signals behave differently according to which types of traders account for trading volume. It divides A-share participants into retail, medium, large, and institutional groups based on order size, then compares…

EquitiesMomentumMean reversionFactor investing
BigQuant

This short data-support exchange explains a discrepancy between stock prices shown by two Chinese market data services. The response attributes the difference to BigQuant providing backward-adjusted prices and notes that providers can use different…

EquitiesChina marketsBacktestingStatistics
SuperMind

This Chinese equity screen looks for stocks associated with the robotics concept, with daily amplitude above 1%, circulating market value below 10 billion, and a close above the previous session’s low. The article explains the last condition as a possible…

EquitiesTechnical indicatorsChina marketsRisk management
SuperMind

This stock screen combines three conditions: turnover between 3% and 12%, a reversal pattern described as an engulfing move, and a short-term price average above a longer moving average. The accompanying examples outline how to filter for turnover, calculate…

EquitiesTechnical indicatorsMomentumChina markets
SuperMind

This post describes a Chinese equity screen focused on companies classified in the metaverse theme. It selects shares whose relative volume falls within a specified band and whose MACD DEA line is rising. The post explains the volume condition as a way to…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

This post proposes screening Chinese equities using a historical dividend measure alongside price activity: a stated 2019 dividend ratio above 25%, intraday amplitude above 1, and a 9:25 price rise below 6%. It frames the combination as a way to find active…

EquitiesChina marketsFactor investingTechnical indicators