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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
Quantpedia
86 documents
TqSdk
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

4,194 documents

SuperMind

This A-share screen selects stocks with turnover between 3% and 12%, year-over-year net profit growth attributable to parent-company shareholders above 20% and no more than 100%, and excludes Beijing-listed shares. The post presents the regional exclusion as…

EquitiesChina marketsFactor investingRisk management
SuperMind

This screening rule targets Shenzhen main-board stocks with turnover from 3% to 12%, a newly formed KDJ bullish crossover, price-to-earnings ratio from 0 to 29.01, and price-to-book ratio from 0 to 3.11. The document frames the filters as a combination of…

EquitiesTechnical indicatorsMomentumFactor investing
SuperMind

This Chinese stock-selection proposal combines a cash-flow strength ranking, a share-price condition, and a historical dividend payout threshold. Its initial description cites a price of 18.5 yuan and a 2019 dividend ratio above 25%, with stronger capital…

EquitiesChina marketsFactor investingMomentum
SuperMind

This article outlines a daily Chinese stock screen using amplitude above 1%, a controlling-shareholder measure above 21%, and turnover between 2% and 9%. Its proposed refinement adds positive price-to-earnings and price-to-book ratios, with upper bounds of…

EquitiesChina marketsTechnical indicatorsFactor investing
BigQuant

The document introduces the manager-of-managers fund structure, in which a central manager allocates capital among independent subaccounts managed by different investment advisers. It distinguishes this approach from a fund of funds: MOM evaluates and…

Multi-assetPortfolio constructionFactor investingStatistics
SuperMind

The screen begins with stocks whose short-term trend is positive relative to a longer moving average, whose recent ten-day return is positive but below 35%, and whose multiple moving averages cluster together. The text interprets alignment as relative…

EquitiesTechnical indicatorsMomentumFactor investing
SuperMind

The screen selects stocks with an amplitude measure above one, RSI below 65, and year-over-year growth in net profit attributable to parent-company shareholders above 20% and no more than 100%. It combines a short-term price range condition and a momentum or…

EquitiesTechnical indicatorsMomentumFactor investing
BigQuant

This document gives a single daily factor example for Chinese stocks. It forms a price proxy by weighting the open and high, compares that proxy with its value four bars earlier, and takes the sign of the difference. The resulting direction signal is ranked…

EquitiesFactor investingTechnical indicators
SuperMind

This note proposes screening Chinese A-shares using three conditions: reported buying or position increase above five percent, year-over-year net profit growth above 20 percent and no more than 100 percent, and a 9:25 a.m. indicated gain below six percent.…

EquitiesChina marketsFactor investingRisk management
SuperMind

The document proposes a daily equity screen combining price range, company size, profitability, and trading activity. It selects stocks with a daily high-low range above one percent, market capitalization below 10 billion yuan, positive net income in each of…

EquitiesChina marketsTechnical indicatorsFactor investing
SuperMind

This Chinese stock screen combines three filters: daily price amplitude above a threshold, observations from 2021, and a 2019 dividend payout ratio above a stated level. The article interprets larger daily ranges as greater price movement and uses the…

EquitiesChina marketsVolatilityFactor investing
BigQuant

This research review examines whether actively managed U.S. equity funds favor firms focused on a single business and whether that preference reflects industry expertise. Its proposed mechanism is that a manager with an informational edge in one industry can…

EquitiesFactor investingPortfolio constructionStatistics
BigQuant

This document describes a China A-share stock selection and portfolio strategy ranked primarily by dividend yield. It filters out suspended and risk-flagged stocks, applies market-cap, positive and relatively low price-to-earnings, and share-price…

EquitiesChina marketsFactor investingPortfolio construction
BigQuant

The report presents a framework for timing gold using three proposed price drivers: value preservation, safe-haven demand, and speculation. It builds the first factor from US inflation expectations and trends in US real interest rates, the second from the…

CommoditiesFactor investingMomentumBacktesting
BigQuant

This brief explanation identifies two main reasons a quantitative factor may have low coverage: the coverage of its underlying input factors and the length of its calculation window. If an input dataset contains values for only a limited portion of the…

Factor investingStatistics
BigQuant

This Chinese-language report summarizes two overseas research papers. The first decomposes the book-to-market ratio into a market-to-intrinsic-value component and an intrinsic-value-to-book component, then examines which part relates to valuation-strategy…

EquitiesFactor investingVolatilityRisk management
BigQuant

The report summary describes a stock-selection factor built from a multinomial logistic model that estimates the probability of a large stock decline over the following month. It tests several decline thresholds and reports broad factor coverage, including…

EquitiesChina marketsMachine learningStatistics
SuperMind

The proposed Chinese stock screen combines a 20-day moving average above the 120-day average with RSI below 65 and a revenue ratio above 1.1 for 2021 compared with 2018. It presents the moving-average relationship as a filter for an upward trend, alongside…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

This research summary describes style drift in active equity mutual funds: departures from a fund’s stated investment mandate that can expose investors to unintended risks. It characterizes style along size, value versus growth, and momentum dimensions, and…

EquitiesFactor investingMomentumRisk management
Awesome Systematic Trading

This strategy ranks stocks monthly by the share of their trading volume occurring in recent earnings-announcement months. It uses a 48-month history and focuses on the latest 16 announcement months, then divides stocks into quintiles by the resulting…

EquitiesEvent-drivenFactor investingPortfolio construction
SuperMind

This research summary argues that consensus analyst estimates may offer limited incremental value once the market has incorporated shared information. It instead examines analyst actions that may carry less widely recognized information: renewed coverage…

EquitiesChina marketsEvent-drivenFactor investing
BigQuant

The note describes PATV, a stock-selection factor based on intraday trading volume. It first compares average volume over five-minute intervals with average volume over thirty-minute intervals, then ranks the resulting ratios across stocks. The factor…

EquitiesFactor investingStatistics