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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

4,194 documents

SuperMind

This stock screen combines three filters: daily price amplitude above 1%, a dividend yield above 25% attributed to 2019, and a condition intended to exclude stocks that hit the upper price limit the previous day. The article presents the combination as a way…

EquitiesTechnical indicatorsFactor investingRisk management
SuperMind

The proposed Chinese equity screen combines four conditions: relatively high price range, a robotics concept classification, free-float market value below the stated threshold, and evidence of institutional buying. The article offers example screening logic…

EquitiesChina marketsFactor investingRisk management
SuperMind

This A-share stock screen combines a 14-period RSI below 65 with a signal for main-fund control on the previous day and a dividend ratio above 25% for 2019. Its final stated rule adds earnings per share above one yuan and market capitalization above two…

EquitiesTechnical indicatorsFactor investingChina markets
SuperMind

The article describes a screen for metaverse-related stocks on China’s Shenzhen main board. Candidates must have appeared on the prior day’s trading leaderboard and fall within stated valuation ranges: price-to-earnings from 0 to 29.01 and price-to-book from…

EquitiesChina marketsEvent-drivenFactor investing
SuperMind

This stock-selection approach combines market activity with a profitability screen. It looks for shares with amplitude above 1, turnover between 2% and 9%, and return on equity above 15% for five consecutive years. The article presents ROE as a way to…

EquitiesFactor investingStatisticsRisk management
BigQuant

The supplied summary describes research on alternative data and a hiring-count signal for Chinese equities. It says overseas use of alternative data is still developing, with most applications aimed at short-term opportunities, and identifies six…

EquitiesFactor investingEvent-drivenBacktesting
SuperMind

This post proposes screening Chinese stocks using three conditions: a 2019 dividend payout ratio above 25%, no limit-up session on the previous day, and at least five moving averages converging. It presents moving-average convergence as a possible sign of…

EquitiesChina marketsTechnical indicatorsFactor investing
SuperMind

This Chinese stock-screening note combines a historical dividend-ratio requirement with measures of trading activity and an upward-moving-average pattern. It describes selecting stocks with a 2019 dividend ratio above 25%, relatively strong capital-flow…

EquitiesChina marketsTechnical indicatorsFactor investing
Stratmill research code

This Python class implements a broad collection of formula-based equity signals using daily close, open, high, low, volume, returns, and volume-weighted average price data. Its methods translate rank, correlation, rolling-window, change, volatility, and…

EquitiesFactor investingTechnical indicatorsBacktesting
SuperMind

This equity screening proposal combines three conditions: a dividend payout ratio above 25% in 2019, evidence of main-holder control on the prior day, and a daily position increase above 5%. The article presents these as signs of shareholder distributions,…

EquitiesChina marketsFactor investing
SuperMind

This stock screen combines a price-movement condition, a technical signal, and a profitability history. It selects stocks with amplitude above 1, MACD above its zero line, and return on equity above 15% in each of five years. The document interprets these…

EquitiesTechnical indicatorsFactor investing
SuperMind

This stock screen requires price amplitude above 1, prior-day trading value above 60 million, and a PE ratio above zero. It combines a short-term measure of price movement and market activity with a basic valuation filter. The document provides formulas for…

EquitiesTechnical indicatorsFactor investingChina markets
SuperMind

This article describes a factor test of price-to-earnings ratio as a stock selection signal among CSI 300 constituents. It divides stocks into five groups, then compares group returns under weekly and monthly rebalancing. The reported qualitative result is…

EquitiesFactor investingBacktestingChina markets
SuperMind

The document proposes a Chinese stock screen combining three conditions: daily amplitude above a threshold, evidence interpreted as main-fund control on the prior day, and membership in the beverage manufacturing industry as a proxy for beverage and alcohol…

EquitiesChina marketsTechnical indicatorsVolatility
SuperMind

This document describes a Chinese equity screen for Shenzhen main board companies associated with beverage and alcohol imports or exports. It selects stocks with turnover between 3% and 12%, price-to-earnings ratios from 0 to 29.01, and price-to-book ratios…

EquitiesChina marketsFactor investing
SuperMind

This stock screen combines three conditions: at least five moving averages coincide, the stock’s ten-day return is positive but below 35, and revenue in 2021 divided by revenue in 2018 exceeds 1.1. The note explains the moving averages using 5-, 10-, 20-,…

EquitiesTechnical indicatorsMomentumFactor investing
SuperMind

This Chinese A-share screening proposal combines a volatility condition with two size filters: amplitude above 1, circulating market capitalization above 10 billion yuan, and enterprise scale above 200 million yuan. The accompanying indicator reference…

EquitiesChina marketsVolatilityFactor investing
BigQuant

This report reviews the weekly returns and directional changes of 16 equity factors. For the week covered, a three-month price momentum or reversal measure led with a reported return of 1.45%, while the 24-day Relative Strength Index returned 0.43%. All…

EquitiesFactor investingMomentumTechnical indicators
SuperMind

This Chinese-language post outlines an A-share stock screen for the metaverse theme. Its initial conditions select stocks with prior-day turnover above 8% and exclude stocks that closed at the daily limit. The final version adds a market-cap filter selecting…

EquitiesChina marketsTechnical indicatorsFactor investing
SuperMind

This research summary examines whether excluding stocks ranked poorly by high-frequency factors can improve a Shanghai-Shenzhen 300 index-enhancement portfolio. It compares three construction methods: combine standardized factors into one score, use a…

China marketsEquitiesHigh-frequency tradingFactor investing
BigQuant

This research summary investigates the A-share small-cap premium, comparing its strength across market-cap segments, industries, and global markets. It reports a pronounced size effect across the broader A-share market and within CSI 500 constituents, but a…

EquitiesChina marketsFactor investingStatistics
SuperMind

This stock screen combines a turnover range of 3% to 12%, a rising DEA condition, and a profitability filter based on ROE. The initial description requires ROE above 15% for five consecutive years, while the proposed final screen and formula retain that…

EquitiesTechnical indicatorsMomentumFactor investing