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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

The document describes an A-share stock screen combining a 14-period RSI below 65, positive parent-attributable profit with year-over-year growth above 20% and no more than 100%, and turnover between 2% and 9%. The stated rationale is to combine a technical…

EquitiesChina marketsTechnical indicatorsFactor investing
BigQuant

This discussion addresses whether a trader should use hyperparameter search to find an optimal combination of existing factors. The response says that “optimal” needs a clear definition: it could mean the best backtest result or the best factor-analysis…

Factor investingMachine learningBacktestingStatistics
BigQuant

This research applies feature selection to multi-factor stock selection in the full Chinese A-share universe, with the CSI 300 and CSI 500 as benchmarks. It constructs industry- and market-cap-neutral strategies and tests feature ranking methods with…

EquitiesChina marketsFactor investingMachine learning
BigQuant

This brief BigQuant project note describes a stock strategy built from three factors that had undergone stability testing. It says the factor weights were selected through a grid search over three parameters, with a reported weighting of 1:8:1. The note also…

EquitiesFactor investingBacktestingRisk management
SuperMind

This Chinese equity screen selects main-board stocks associated with the robotics theme, with turnover between 3% and 12%, circulating market value below 10 billion yuan, and more than 365 days since listing. The page provides example selection logic and…

EquitiesChina marketsFactor investingBacktesting
BigQuant

The document outlines a strategy that dynamically evaluates macroeconomic event factors and selects those more closely associated with asset movements. It considers more than thirty indicators spanning economic growth, inflation, monetary conditions, and…

Multi-assetEvent-drivenFactor investingPortfolio construction
BigQuant

The document discusses converting one-minute stock data into daily observations for high-frequency price and volume factors. The example query constructs features such as volume shares across intraday intervals, price and volume correlations, correlations…

High-frequency tradingFactor investingStatisticsChina markets
SuperMind

This Chinese A-share screening proposal selects stocks with RSI below 65, year-over-year growth in parent-company net profit above 20% and up to 100%, and businesses outside finance, real estate, and insurance. The author frames the RSI condition as a way to…

EquitiesTechnical indicatorsMomentumFactor investing
BigQuant

This article proposes a qualitative framework for finding Chinese stocks with potential for medium- to long-term growth during annual and quarterly reporting periods. It combines three checks: whether recognized active investment firms appear among…

EquitiesChina marketsFactor investingStatistics
BigQuant

This platform discussion addresses how to understand a precomputed factor, using a MACD signal-line factor as its example. The response says that the platform does not provide the calculation process for such precomputed data. Users can inspect the factor's…

Factor investingTechnical indicatorsStatisticsEquities
FMZ forum

This market commentary explains the divergence between large, established A-share companies and smaller, often high-valuation stocks through shifts in economic, monetary, and regulatory conditions. It argues that improving results in traditional cyclical…

EquitiesChina marketsFactor investingMarket microstructure
Amberdata research

The document summarizes an equity factor study on whether analyst attention predicts future company fundamentals and stock returns. It proposes adjusting a conventional analyst-coverage measure with a linear regression that removes effects associated with…

EquitiesFactor investingStatisticsSentiment
BigQuant

This overview proposes constructing fund of funds portfolios from four groups: broad-market index ETFs, sector ETFs, index-enhanced funds, and quantitative funds. It compares passive index funds, enhanced products, and quantitative funds by their typical fee…

China marketsMulti-assetPortfolio constructionRisk management
SuperMind

This Chinese equity screen combines three types of filters: turnover between 3% and 12%, year-over-year growth in net profit attributable to parent-company shareholders above 20% and no more than 100%, and a stated threshold for large or very large order…

EquitiesChina marketsFactor investingRisk management
BigQuant

This introductory tutorial presents active equity management as a connected process: forecast stock-level excess returns with an alpha model, estimate exposures with a risk model, combine expected returns and risk through portfolio optimization, execute…

EquitiesFactor investingRisk managementPortfolio construction
SuperMind

This Chinese stock-screening example combines three conditions: price amplitude above 1, a KDJ value below 20, and return on equity above 15% for five consecutive years. It explains the selection as a blend of price movement, a technical indicator, and…

EquitiesTechnical indicatorsFactor investingRisk management
BigQuant

This research summary examines four MSCI smart beta equity indexes—value weighted, equal weighted, momentum, and minimum volatility—against a capitalization-weighted benchmark. Using monthly observations from 1999 through 2014, it applies principal component…

EquitiesFactor investingStatisticsPortfolio construction
SuperMind

This Chinese-language post proposes a stock screen combining a daily high-low range of at least one price unit, return on equity above 15% for five consecutive years, and ranking by stock popularity. The stated rationale is to find shares with notable price…

EquitiesFactor investingRisk managementChina markets
BigQuant

This research summary describes stock-selection factors built from tick-level aggressive buy and sell amounts. It applies an informed-trading probability model to filter noisy order flow, then forms informed sell share, informed buy share, and net informed…

EquitiesFactor investingMarket microstructureStatistics
BigQuant

This research summary examines factor weighting, orthogonalization, and timing through the relationship between composite information-coefficient weighting and Fama–MacBeth regressions. Under the stated condition that returns and factors are z-scored, it…

Factor investingStatisticsPortfolio construction
SuperMind

This document turns Peter Lynch’s PEG idea into a periodic stock-selection process for Chinese equities. It starts with companies in selected non-cyclical industries, then keeps the half scoring highest on net-profit growth and sales net margin. From that…

EquitiesFactor investingChina marketsPortfolio construction
BigQuant

This meetup compilation surveys practical topics in quantitative investing, including factor design, machine learning, strategy validation, portfolio sizing, live execution, and sector rotation. It recommends building a factor library by collecting and…

Factor investingMachine learningBacktestingPortfolio construction
NautilusTrader

The document proposes screening Chinese stocks in the metaverse theme by recent trading activity and company size, then adds a net-profit growth condition. Its final stated rules require the prior day’s turnover to exceed 8%, market capitalization to be at…

EquitiesChina marketsMomentumFactor investing