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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

This stock selection example combines a positive MACD reading and rising, diverging daily moving averages with filters for Shenzhen Main Board companies. It restricts price-to-earnings and price-to-book ratios to stated ranges, then suggests sorting…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

The article proposes screening Chinese stocks in the metaverse theme using concurrent technical signals and a measure of large-order net buying. Its stated conditions are three upward crossovers—MACD over its signal line, price over the five-day average, and…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

This document describes a Chinese equity screening rule combining turnover, displayed order-book volume, and intraday price range. It selects stocks with turnover between 3% and 12%, greater displayed bid volume than ask volume, and an amplitude threshold…

EquitiesChina marketsTechnical indicatorsMarket microstructure
SuperMind

This note describes a Chinese stock screen combining turnover between 3% and 12%, a daily gain greater than 1% relative to a market or sector comparison, and metaverse-related classification. It frames the method as a blend of price activity and thematic…

EquitiesChina marketsMomentumVolatility
SuperMind

This note proposes screening Chinese equities for a daily trading range above 1%, activity during 2021, and a measure described as institutional buying. The example defines the institutional condition as a rolling 20-session measure where at least 20% of…

EquitiesChina marketsVolatilityStatistics
SuperMind

This note outlines a Chinese equity screen combining daily price range, a stock-code filter, and weekly MACD conditions. It selects shares whose high-to-low range exceeds 1% of the prior close, whose code begins with 60, and whose weekly MACD signal is above…

EquitiesChina marketsTechnical indicatorsVolatility
SuperMind

This stock-selection idea builds a watchlist from three conditions: daily price amplitude above one percent, at least one limit-up event in the prior 25 days, and a previous-day 09:15 matching price at the limit down. The accompanying rationale treats large…

China marketsEquitiesVolatilitySentiment
SuperMind

This Chinese equity screening method evaluates stocks after each trading day’s close. It selects stocks whose MACD is above zero, whose price-to-earnings ratio is positive, and whose MACD is rising relative to the prior observation. The document presents the…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

This Chinese equity screen selects stocks with an amplitude above 1, circulating market capitalization above 10 billion yuan, and no limit-up on the previous day. The stated rationale is to combine a volatility threshold with company size while excluding…

EquitiesChina marketsVolatilityTechnical indicators
SuperMind

This daily stock screen combines a positive MACD reading with a ranking by individual-stock heat and moving-average confluence. The initial description calls for at least five overlapping moving averages, while the final proposed logic relaxes that condition…

EquitiesMomentumTechnical indicatorsSentiment
SuperMind

This Chinese A-share screen selects main-board stocks with turnover between 3% and 12%, at least one limit-up event in the prior 25 days, and a daily close more than 1% above the previous close. The article also gives a formula reference and a Python example…

EquitiesMomentumBreakoutChina markets
SuperMind

The document distinguishes two broad uses of multi-factor models: regression models, which focus on explaining outcomes, and ranking models, which aim to identify stocks with attractive returns. Within the regression approach, it describes two ways to obtain…

Factor investingStatisticsEquities
SuperMind

The document describes a Chinese stock screen that combines three filters: membership in the metaverse sector, positive institutional activity, and a positive price-to-earnings ratio. It presents the screen as a way to identify companies in a chosen theme…

EquitiesFactor investingRisk management
SuperMind

This proposed equity screen looks for stocks with a stated amplitude threshold, at least one daily gain of 10% or more during the prior 25 trading days, and a positive price-to-earnings ratio. Its stated rationale is to combine elevated price movement and…

EquitiesChina marketsVolatilityMomentum
BigQuant

This weekly report summarizes factor returns across broad Chinese equity universes and several index or liquidity-based stock pools. It describes positive performance for profitability and book-to-price factors in the full market, while size, beta, and…

EquitiesChina marketsFactor investingMomentum
SuperMind

This stock-selection proposal targets Chinese equities associated with the metaverse concept. It screens for a volume ratio between 1.5 and 6 and a weekly moving-average crossover, then adds a positive price-to-earnings ratio below 150 in its final stated…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This stock-selection post describes a screen for companies classified in the metaverse industry. Its stated criteria include a volume ratio above 1.5 and below 6, at least one daily gain of 10% or more during the prior 25 trading days, and, in the final…

EquitiesMomentumTechnical indicatorsChina markets
SuperMind

This note presents a simple stock screen for companies in the metaverse theme with circulating market capitalization above 10 billion yuan. It selects stocks whose opening price is within roughly five percent of the ten-day moving average of opening prices.…

EquitiesChina marketsTechnical indicatorsBacktesting
SuperMind

This note describes an A-share stock screen combining daily amplitude above 1%, a robot-industry theme, circulating market capitalization below 10 billion yuan, and positive recent net profit. It also refers to ordering candidates by popularity. The…

EquitiesChina marketsVolatilityTechnical indicators
SuperMind

This Chinese equity screen combines a daily amplitude threshold, at least two limit-up events over a 500-day lookback, and a three-session limit-up streak ending the prior day. It aims to find shares with substantial price movement and repeated strong upward…

EquitiesMomentumBreakoutTechnical indicators
SuperMind

This stock selection idea ranks shares by volume ratio and retains the top 100, then filters for stocks listed for more than 30 days whose 30-day moving average is rising. The intended rationale is to combine unusually high recent trading activity with a…

EquitiesMomentumTechnical indicatorsStatistics
BigQuant

A stock screen for a moving average crossover can return no matches if its query loads only the target date. The note explains that time-series indicators need earlier observations to calculate their rolling values, so the data query should begin before the…

EquitiesTechnical indicatorsStatistics
FMZ forum

The document proposes a research data model for representing a limited, conditional SEC exemption related to eligible trading venues and tokenized NMS stocks. It argues against reducing regulatory status to a single approval flag and instead recommends…

EquitiesRisk management