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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
Quantopian lectures
45 documents
Binance API docs
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 China A-share screening idea starts with stocks in the metaverse theme, then requires the indicated 9:25 price change to be below 6% and positive large-order net inflow in the afternoon. The article describes the theme filter as a way to define the…

EquitiesChina marketsEvent-drivenMarket microstructure
SuperMind

This proposed China A-share screen combines three conditions: daily amplitude above 1%, positive prior-day main-fund flow, and turnover between 3% and 12%. The post frames the amplitude and turnover filters as ways to focus on active, liquid stocks, while…

EquitiesChina marketsTechnical indicatorsMarket microstructure
BigQuant

This forum post reports a data-quality anomaly in the CSI 1000 constituent history: a query finds 1,001 component records for the index on July 26, 2023. It shows how to query the component table for dates from 2015 onward, then group records by date for the…

EquitiesChina marketsStatistics
SuperMind

The document presents a Chinese equities screening idea combining a robot-industry concept, a circulating market value below 10 billion yuan, a turnover band of 3% to 12%, and exclusion of stocks associated with northbound capital. It suggests sorting…

EquitiesChina marketsFactor investing
ProRealCode

This ProRealTime indicator monitors the opening price range across Euronext, London, US, and Tokyo sessions, with an optional custom time window. On a one-minute chart, it tracks the range’s high and low during a configurable observation period, set to 15…

Technical indicatorsBreakoutEquitiesFutures
SuperMind

This Chinese-language post describes an equity screening idea that combines three conditions: RSI below 65, KDJ’s K line below 20, and a positive product of daily price change and net volume attributed to very large orders. The author presents RSI as a…

EquitiesTechnical indicatorsMean reversionRisk management
SuperMind

This stock-selection approach combines a market-capitalization ceiling, positive profitability, recent limit-up activity, and a price-range condition. The stated idea is to find relatively small companies showing strong recent price action while excluding…

EquitiesMomentumBreakoutRisk management
SuperMind

This stock screen combines three consecutive declining sessions with a daily price range above one percent and a stated turnover-rate band of two to nine percent. The document presents the conditions as a way to find shares with short-term downward momentum…

EquitiesTechnical indicatorsMomentumRisk management
SuperMind

This stock-screening method combines positive MACD readings with an upward arrangement of short-term moving averages. The document describes MACD as a way to identify positive price momentum and compares five-day and ten-day averages as a simple trend…

EquitiesTechnical indicatorsMomentum
BigQuant

This summary of a research report examines whether trade counts from tick-level transaction data can refine a traditional reversal factor in China’s order-driven A-share market. Trade count is defined as the number of matched transactions. The report says it…

China marketsEquitiesMean reversionFactor investing
SuperMind

This document describes an A-share stock selection screen combining daily price amplitude, a history of limit-up moves, and MACD above zero. It gives indicator conditions and a Python example using historical stock data. The intended idea is to focus on…

China marketsEquitiesTechnical indicatorsMomentum
BigQuant

The article summarizes a method for extracting priced common factors from stock returns. First, a Fama-MacBeth cross-sectional regression uses several return-predictive characteristics to estimate stocks’ expected returns. Stocks are then sorted into…

EquitiesFactor investingMachine learningStatistics
SuperMind

This daily stock-selection method combines price activity, past limit-up events, and valuation filters. It screens Shenzhen Main Board stocks for amplitude above 1, at least two limit-ups during the prior 500 days, a price-to-earnings ratio between 0 and…

EquitiesChina marketsBreakoutTechnical indicators
SuperMind

This short-term stock screen selects shares with amplitude above 1, ranks them by the day’s auction amount, keeps the top five, and requires positive net buying attributed to major participants. The article’s rationale is that large price movement and active…

EquitiesChina marketsMomentumTechnical indicators
BigQuant

The report uses Hong Kong Exchange disclosures on holdings associated with northbound Stock Connect trading seats to estimate stock positions and sector-level additions. It argues that aggregate flows can obscure differences among market participants, then…

China marketsEquitiesFactor investingBacktesting
SuperMind

This note proposes a short-term A-share screen based on daily price range, relative volume, and a ranking for net large-order flow. The written rule calls for amplitude above one, relative volume between 1.5 and 6, and a high large-order net-volume ranking.…

EquitiesTechnical indicatorsMomentumRisk management
SuperMind

This note describes an A-share stock screen combining MACD above zero, upward divergence among moving averages, and prior-day trading value above a stated threshold. It presents these conditions as signs of an upward market state, a rising trend, and…

EquitiesTechnical indicatorsMomentum
SuperMind

The article proposes screening Chinese stocks using three technical conditions: daily high-low amplitude above 1%, at least two limit-up events over a 500-day window, and a 14-period RSI below 65. It supplies indicator formulas and a Python-style example…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This article describes a Chinese stock screen combining turnover of 3% to 12%, a 2021 listing year, and a reversal pattern identified by the Chinese term “fanbao.” It provides sample indicator and Python-style snippets, including a three-session average…

EquitiesChina marketsTechnical indicatorsMean reversion
SuperMind

This stock-screening idea targets main-board Chinese equities associated with robotics. It combines turnover between 3% and 12%, a circulating market value below 10 billion yuan, and a rising 30-day moving average relative to the 60-day average. The article…

EquitiesChina marketsTechnical indicatorsMomentum
Stratmill research code

The document explains how to form and evaluate long-short stock portfolios, focusing on pairs trading. It compares hedge-ratio methods: ordinary least squares minimizes portfolio variance under a correlated random-walk and Gaussian framework, while total…

EquitiesPairs tradingPortfolio constructionBacktesting
BigQuant

This opinion article argues that quantitative trading is a tool used by larger market participants rather than the primary force setting a stock's longer-term direction. It describes how large orders might trigger automated buying or stop-driven selling,…

EquitiesMarket microstructureTechnical indicatorsRisk management
SuperMind

This opinion article argues that quantitative trading is a tool used by larger market participants rather than the primary force setting a stock's longer-term direction. It describes how large orders might trigger automated buying or stop-driven selling,…

EquitiesMarket microstructureTechnical indicatorsRisk management
SuperMind

This stock-selection recipe screens Chinese equities before each trading day for three conditions: MACD above zero, a positive price-to-earnings ratio, and a positive recent return. The return calculation compares the prior close with the close from an…

EquitiesChina marketsTechnical indicatorsFactor investing