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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

3,481 documents

BigQuant

The document describes a seasonal earnings anomaly: companies may have predictable high- and low-profit quarters, yet announcements of peak or trough earnings can still surprise investors and produce abnormal stock returns. It attributes the mispricing…

EquitiesEvent-drivenBacktesting
BigQuant

The article introduces the Fama-French five-factor model as an extension of the three-factor framework. It describes market, size, book-to-market, profitability, and investment factors, and explains that multiple regression estimates a stock’s exposure to…

EquitiesFactor investingStatisticsMean reversion
BigQuant

These course notes discuss practical ways to follow a stock strategy built around pullbacks after strong stocks hit their price limits and later rebound with market sentiment. They caution that entering after a strategy has recently risen can mean buying…

EquitiesMomentumRisk managementPortfolio construction
BigQuant

This note presents a relative strength index calculation based on closing-price changes. It separates each change into its positive component and its absolute magnitude, then applies a smoothed moving average to each series. The ratio is transformed onto a…

Technical indicatorsMomentumStatistics
BigQuant

The document reviews quality investing as a composite of company characteristics, including profitability, growth, stability, capital structure, accounting quality, and investment. It compares reported findings for U.S. equities with cross-sectional results…

EquitiesFactor investingChina marketsStatistics
BigQuant

The document describes a style allocation approach that uses an illiquidity measure, called ILLIQ, to represent how much information is associated with each unit of trading value. It divides the stock universe into safer and riskier groups, then infers…

EquitiesFactor investingMomentumRisk management
BigQuant

The document surveys data used to build quantitative investment strategies and support trading and risk decisions. It groups inputs into market prices, volumes and trades; company financials and valuation; macroeconomic indicators and policy; technical…

Multi-assetStatisticsRisk management
BigQuant

This short forum exchange asks how to count trading days since a condition last became true. Its example starts counting on the session after the trigger: if the condition occurs on one date, the next trading day returns one and the following session returns…

EquitiesStatisticsTechnical indicators
BigQuant

The document summarizes research on whether informed investors use industry ETFs to hedge long positions in stocks with favorable company-specific information. It describes a paired measure combining hedge funds’ unusually large stock holdings with an…

EquitiesUS marketsEvent-drivenArbitrage
BigQuant

This practice report compares a DeepAlpha deep neural network with LightGBM in a daily A-share stock-selection strategy. Both models use the same 32 short-term price and volume factors and five-year training sample. The portfolio buys the ten highest-ranked…

China marketsEquitiesMachine learningFactor investing
BigQuant

The document describes an intraday trend strategy for Chinese equity index futures, based on a reported persistent opening momentum effect. It defines a bullish sequence as rising opening, low, and closing prices across bars, and a bearish sequence as…

FuturesChina marketsMomentumTrend following
BigQuant

This article proposes changing position sizes and take-profit distances in a grid strategy to recover from underwater positions sooner. Instead of a fixed base position, it describes increasing additions in stages as price falls: one unit per grid initially,…

Grid tradingPosition sizingRisk managementMean reversion
BigQuant

This research overview examines the development and current state of China’s pension arrangements, alongside the management of pension assets. It organizes retirement provision into three pillars: basic public pensions, occupational plans such as enterprise…

China marketsPortfolio constructionRisk management
BigQuant

The discussion explains why a small-cap daily strategy may signal a full exit on one day and then recommend buying the same stocks in a new task the next day. The response attributes this to daily portfolio recalculation: if the selection changes from one…

EquitiesExecutionPortfolio construction
BigQuant

This Chinese-language article describes a workflow for turning intraday trading data into daily stock-selection factors and using those factors in analysis and strategy development. Its example is a large-order-driven price-rise factor, alongside other…

EquitiesHigh-frequency tradingFactor investingBacktesting
BigQuant

This research summary argues that conventional momentum is a weak alpha signal in the Chinese stock market and proposes rebuilding it from intraday returns. The approach divides each trading day’s price change into five time segments, then recombines the…

EquitiesChina marketsMomentumFactor investing
BigQuant

This research summary outlines a monthly tactical framework for rotating among Chinese A-share industries. It combines two approaches: time-series timing based on industry classification, business-cycle indicators, fundamental forecasts, valuation…

EquitiesChina marketsMomentumVolatility
BigQuant

This Chinese-language research note analyzes recent trading value as a liquidity factor for stock selection. It describes changing the evaluation horizon to five-day returns, excluding stocks at their daily upper price limit to reflect execution difficulty…

EquitiesChina marketsFactor investingStatistics
BigQuant

The Traders Dynamic Index combines a smoothed RSI line, a signal line, a market base line, and volatility bands. Its configurable settings include RSI and smoothing periods, applied price, band period, overbought and oversold thresholds, and display toggles.…

Technical indicatorsMomentumVolatility
BigQuant

This discussion answers how to calculate indicators with chosen parameters in BigQuant. It points users to DAI SQL’s technical analysis operators, which use TA-Lib, and illustrates the approach with a moving average applied to an open-price series. A SQL…

Technical indicatorsEquities
BigQuant

This report introduction frames research into how factor and stock weights affect style exposure in multi-factor equity portfolios. It focuses on reducing unintended market-cap, industry, and other style biases, which the authors associate with past setbacks…

EquitiesFactor investingStatisticsBacktesting
BigQuant

The document introduces the Williams Overbought/Oversold Index, commonly called Williams %R, as a technical indicator calculated from closing price and the recent high-low range. Its formula compares the close with the highest high over a lookback period,…

Technical indicatorsEquities
BigQuant

The document discusses the growth of electronic trading and presents algorithmic execution as a tool for handling large orders in volatile markets. Its core methods include splitting a parent order into smaller trades, aligning execution with market-volume…

ExecutionMarket microstructureMachine learningRisk management
BigQuant

This example describes a high-dividend stock selection model for the Chinese equity market. It first excludes special-treatment stocks, suspended stocks, and Beijing Stock Exchange listings. Within the remaining universe, it selects the 300 largest companies…

China marketsEquitiesFactor investingBacktesting