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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
WonderTrader
14 documents
Alphalens
14 documents
backtesting.py
11 documents
Technical Analysis
9 documents
QTPyLib
8 documents
Lumibot strategies
7 documents
QuantRocket
7 documents
Awesome Quant
1 documents

Search the library

12,226 documents

SuperMind

This proposed mainland Chinese stock screen targets non-ST main-board shares with turnover between 3% and 12% and circulating market value between 5 billion and 10 billion yuan. It adds a five-day limit-up style condition, described through checks of future…

EquitiesChina marketsMomentumBreakout
SuperMind

This proposed stock screen selects non-Beijing A-shares with amplitude above one and ranks candidates by the day’s opening-auction amount, keeping the top five. Its rationale is that large amplitude may identify stocks with greater price movement, while high…

EquitiesChina marketsTechnical indicatorsExecution
SuperMind

This document describes a Chinese equity screen for stocks associated with the metaverse theme. It combines positive net buying attributed to major participants during the opening auction with afternoon large-order net inflows. The accompanying indicator…

EquitiesChina marketsMarket microstructureSentiment
SuperMind

This document presents a Chinese stock screen requiring a prior-day appearance on the Longhubang trading activity list, a price amplitude above 1, and circulating market value above 200 million yuan. It describes amplitude as a measure of short-term movement…

EquitiesChina marketsVolatilityTechnical indicators
SuperMind

This document describes a Chinese equity screen combining a turnover-rate range of 3% to 12%, a stock code beginning with 60, and seven consecutive daily declines during 2021. It provides formula and Python examples that operationalize those conditions,…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

This stock-screening note proposes selecting shares in the metaverse industry when the current opening price is near the ten-day moving average and the prior day’s 9:15 matching price was at the daily limit-down level. It frames the average-price condition…

EquitiesTechnical indicatorsChina marketsMean reversion
SuperMind

This Chinese-language strategy note describes a daily stock screen combining a 14-period RSI below 65, three consecutive bearish sessions, and turnover between 2% and 9%. It presents the conditions as a way to pair a momentum oscillator and recent price…

EquitiesTechnical indicatorsMomentumRisk management
SuperMind

This stock screen looks for shares with MACD above zero, upward movement in short-term moving averages, and turnover within a stated range. The technical indicators are meant to identify upward conditions, while the turnover filter aims to exclude stocks…

EquitiesChina marketsTechnical indicatorsMomentum
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 introduction explains a one-period binomial model for a call option. The underlying asset starts at 100 and can move to either 110 or 90 by the next day; with a strike of 100 and interest rates set to zero, the call pays 10 in the up state and nothing…

OptionsDerivatives pricingRisk management
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
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