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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
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

4,194 documents

BigQuant

This Chinese-language project note describes an attempt to improve a stock strategy using technical factors. The author combines volatility, price, momentum, and liquidity measures, and filters stocks with unusually high or low characteristics in an effort…

EquitiesFactor investingMomentumVolatility
BigQuant

The note compares two strategy versions and argues that both feature quality and model choice matter. It uses a cooking analogy to convey that useful factors cannot fully compensate for a weak model, and a capable model still depends on informative inputs.…

Machine learningFactor investingRisk management
SuperMind

The document describes a Chinese equity screening rule that combines turnover constraints with a three-day price condition. It proposes selecting stocks with turnover between 3% and 12%, three consecutive declining sessions, and turnover between 2% and 9%.…

EquitiesTechnical indicatorsFactor investingChina markets
SuperMind

This post proposes screening Chinese stocks for daily amplitude above 1, a 2019 dividend ratio above 25%, and a high that is the highest across a two-day window. It interprets the amplitude as a way to find more active shares, the historical dividend filter…

China marketsEquitiesMomentumTechnical indicators
SuperMind

This Chinese equity screen combines daily price amplitude, a change in controlling shareholders, and a rule excluding stocks that hit the price limit on the previous day. Its final stated version adds a price-to-book ceiling and a minimum year-over-year…

EquitiesChina marketsTechnical indicatorsFactor investing
SuperMind

This document presents a Chinese equity selection rule that combines price range with profitability and valuation filters. It selects stocks whose intraday high-low range exceeds the stated threshold, whose return on equity has remained above the stated…

EquitiesChina marketsFactor investingRisk management
SuperMind

The document outlines a Chinese equity screen combining daily price range, turnover, and historical revenue growth. Its initial rules seek stocks with an amplitude above one, turnover between 2% and 9%, and revenue in 2021 more than 1.1 times revenue in…

EquitiesChina marketsFactor investingRisk management
BigQuant

The document explains how an ascending percentile rank converts a factor’s cross-sectional ordering into a normalized value. For each stock, sort the factor from lowest to highest, assign its rank, and divide that rank by the total number of stocks in the…

EquitiesStatisticsFactor investing
SuperMind

The post outlines a Chinese A-share stock screen combining price amplitude, a historical dividend payout threshold, a market-cap ceiling, and positive earnings. Its final stated selection logic requires amplitude above 1, a 2019 payout ratio above 25%,…

EquitiesChina marketsFactor investingRisk management
BigQuant

The document compares methods for using high-frequency factors with strong short effects to improve a CSI 500 index-enhancement strategy. It distinguishes screening out stocks before building the strategy from removing them afterward, and describes combining…

China marketsEquitiesFactor investingHigh-frequency trading
Awesome Systematic Trading

This document presents an annual U.S. equity strategy that ranks firms by research and development spending relative to market capitalization. At the end of April, it forms a long portfolio from the highest-ranked group and a short portfolio from the…

EquitiesFactor investingPortfolio constructionBacktesting
SuperMind

This Chinese-language post outlines a stock screen combining price range, profitability, opening-auction net buying, and technical conditions. Its initial criteria are a daily high-low range of at least one price unit, return on equity above 15% in each of…

EquitiesTechnical indicatorsMomentumFactor investing
BigQuant

This forum post shows a workflow for preparing Chinese stock data to neutralize valuation measures by industry and market capitalization. It joins daily bars, price-to-book values, market capitalization, and industry classifications, then pivots valuation…

China marketsEquitiesFactor investingStatistics
BigQuant

This beginner overview surveys several approaches to quantitative stock selection: multi-factor scoring or regression, style rotation, money-flow signals, momentum and reversal, analyst consensus, ownership concentration, and trend following. For style…

EquitiesFactor investingTrend followingMomentum
SuperMind

This stock screen selects Chinese equities with turnover between 3% and 12%, an IPO year of 2021, and return on equity above 15% in each of the previous five years. It combines a liquidity-related trading activity filter with a historical profitability…

EquitiesChina marketsFactor investing
SuperMind

This summary of a Chinese securities research report examines how to time and select consumer-sector equities, focusing on home appliances and food and beverage. It argues that return on equity (ROE) relates to long-run returns and valuation levels, while…

EquitiesFactor investingChina marketsPortfolio construction
BigQuant

The report summary presents a two-layer framework for improving the stock universe used in multi-factor strategies. Rigid filters aim to ensure that securities are tradable, while flexible filters seek to improve universe quality. The flexible layer…

EquitiesFactor investingPortfolio constructionRisk management
vn.py community

This post describes a developer’s short-term, multi-factor research tool for Chinese equities and emphasizes using consistent execution assumptions when assessing strategy results. Its stated rules include selling at the trigger-time price when a next-day…

EquitiesChina marketsFactor investingBacktesting
SuperMind

The document outlines a Chinese A-share selection approach combining a technical condition, a fundamental growth filter, and a weekly trend signal. It looks for stocks with RSI below 65, parent-company net profit growth above 20% and no more than 100%, and a…

EquitiesChina marketsTechnical indicatorsMomentum
BigQuant

This article introduces alpha and beta through market and multifactor models, describing alpha as return unexplained by modeled risk exposures. It explains how active portfolios might seek positive alpha while keeping factor exposures aligned with a…

Factor investingPortfolio constructionStatisticsRisk management
BigQuant

This document explains the PB-ROE framework as a valuation relationship: higher expected return on equity is associated with higher price-to-book multiples, with log PB described as linearly related to expected ROE. It reviews the theoretical basis and…

EquitiesFactor investingStatisticsBacktesting
BigQuant

This document profiles the China Securities Consumer Leaders Index, which selects 50 large, higher-quality companies from the discretionary and staple consumer sectors across the Shanghai and Shenzhen markets. It is intended to represent leading consumer…

EquitiesChina marketsFactor investing
SuperMind

The document outlines a Chinese A-share stock screen that selects shares with daily amplitude above 1%, excludes Beijing-listed stocks, caps market value at 10 billion yuan, and requires positive return on equity across the past 60 periods. It illustrates…

EquitiesChina marketsTechnical indicatorsFactor investing