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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
QuantRocket
7 documents
Lumibot strategies
7 documents
Awesome Quant
1 documents

Search the library

22,592 documents

SuperMind

The document proposes an A-share stock screen combining daily range, recent limit-up behavior, and buying activity attributed to large orders during the opening auction. A candidate must have a daily high-low range above 1%, at least one limit-up day in the…

EquitiesChina marketsMomentumBreakout
SuperMind

This article proposes screening Chinese equities for market value below 10 billion yuan, a volatility condition, and positive profitability over recent years. It describes combining a price range measure with a subjective assessment of company quality and…

EquitiesChina marketsTechnical indicatorsFactor investing
SuperMind

This Chinese-language post outlines a stock screen that ranks shares by trading-volume strength and selects those near the top of the ranking. It adds a 15-minute MACD condition: the green histogram bars should be shrinking, which the post interprets as a…

China marketsEquitiesMomentumTechnical indicators
SuperMind

This post proposes a short-term Chinese equity screen using three conditions: prior-session amplitude above 1%, tradable share count no greater than 5.5 billion, and at least one limit-up during the first three months of 2021. The rationale is to combine…

EquitiesVolatilityBreakoutRisk management
SuperMind

This post describes a Chinese equity screening rule combining current turnover, top-of-book order volume, and previous-day turnover. It selects stocks with turnover between 3% and 12%, more displayed volume at the best bid than at the best ask, and prior…

EquitiesMarket microstructureTechnical indicators
SuperMind

The post proposes a Chinese equity screen for beverage and alcohol import or export stocks. It combines an amplitude threshold with three moving averages aligned in a bullish order, described as simultaneous golden crosses, then selects a limited number of…

EquitiesTechnical indicatorsMomentumChina markets
BigQuant

This document is a brief summary of an A-share quantitative market-timing report titled around the possibility that a lower open can offer an opportunity. It reports contemporaneous observations on sector strength, index valuations, sector relative…

EquitiesChina marketsTechnical indicatorsStatistics
SuperMind

This A-share selection rule combines three conditions: a daily range above 1%, weekly MACD above zero, and at least two limit-up events within a 500-day lookback. The document presents repeated limit-up moves as a possible sign of strength, with the range…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

This stock selection rule screens for A-shares with a daily high-low range above 1% and turnover between 2% and 9%. It combines a volatility measure with trading activity and a market classification filter. The document also sketches an implementation using…

EquitiesChina marketsVolatilityTechnical indicators
BigQuant

This research summary surveys dynamic allocation methods for equity style factors. It organizes the approaches by whether they use return information, risk information, or both, adapting methods originally used in broad asset allocation. The study first…

EquitiesChina marketsFactor investingPortfolio construction
SuperMind

The article describes an equity screen combining three conditions: membership in the metaverse theme, a prior-day close above the 250-day moving average, and a rising-bottom pattern. It explains the latter as a retest after a decline and rebound, where the…

EquitiesTechnical indicatorsChina marketsRisk management
BigQuant

This report compares several Chinese language models as assistants for discovering equity liquidity factors over a specified historical period. Each model proposes data inputs and a formula built from trading volume, turnover, amount, or price. The author…

EquitiesChina marketsFactor investingMachine learning
BigQuant

This weekly report assesses the Chinese equity market after a rebound in early June 2022. Its timing framework compares 20-day and 120-day moving averages for a broad market index and combines their distance with a market breadth or “profit effect” measure.…

EquitiesChina marketsTechnical indicatorsTrend following
SuperMind

This post proposes screening stocks in the metaverse industry using two conditions: price or average price above a five-day moving average, and prior-day auction turnover above 0.26. It interprets the moving-average condition as a short-term upward trend and…

EquitiesTechnical indicatorsMomentumChina markets
SuperMind

This Chinese-language post presents an A-share screening rule that combines a 14-period RSI below 65, a ratio of outside-market to inside-market trading above 1.3, and a volume ratio between 1.5 and 6. It frames the order-flow ratio as a proxy for buying…

EquitiesTechnical indicatorsMomentumChina markets
Awesome Systematic Trading

This document describes an event-driven long strategy that combines corporate repurchase announcements with upcoming earnings dates. It screens US-listed stocks, excludes the smallest market-cap quartile, and looks for buyback announcements of at least 5% of…

EquitiesEvent-drivenPosition sizingBacktesting
SuperMind

This Chinese stock-selection strategy filters for an RSI below 65, circulating market capitalization between 5 billion and 10 billion yuan, and prior-day turnover above 8%. The accompanying Python example calculates a 14-period RSI, applies the three…

EquitiesTechnical indicatorsStatisticsChina markets
BigQuant

This document summarizes a Chinese research report on measuring listed companies’ technological innovation capacity. It identifies factor construction and testing by industry as a central topic, alongside building an enhanced portfolio for a strategic…

China marketsEquitiesFactor investing
BigQuant

This study proposes a stock-selection factor derived from intraday volume patterns. It defines a daily volume “tide” by smoothing minute-level volume with a nine-minute neighborhood, locating its peak, and identifying low-volume points before and after that…

China marketsEquitiesFactor investingStatistics
MQL5 code base

This indicator creates synthetic Japanese candlesticks over a configurable period by averaging the price series used in its calculations. It visually emphasizes candle shapes classified as hammers or inverted hammers, using separate colors for the two types.…

Technical indicatorsEquities
BigQuant

This report examines industry exposures in an existing multi-factor stock-selection portfolio, tests how the model performs across sectors, and constructs industry-neutral long and short portfolios. It identifies sectors where the model appeared unsuitable…

China marketsEquitiesFactor investingPortfolio construction
BigQuant

This note offers informal Sharpe-ratio thresholds for screening strategies under a stated evaluation context: a single strategy rotating half-capital among at least three stocks, with million-level capacity and a backtest covering roughly three years. It…

StatisticsBacktestingRisk managementEquities
SuperMind

The document proposes an A-share stock screen combining daily price amplitude, a specified share-price level, and a weekly close above its 30-week moving average. It presents the rules as a way to combine volatility, a price filter, and a trend signal. It…

EquitiesChina marketsTechnical indicatorsTrend following
SuperMind

This A-share screening idea selects stocks with RSI below 65, seven consecutive down days, and an opening move below 6% at 9:25. It combines a technical condition, an extended run of declining sessions, and a limit on the current day's early price change.…

EquitiesTechnical indicatorsMean reversionChina markets