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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
Lumibot strategies
7 documents
QuantRocket
7 documents
Awesome Quant
1 documents

Search the library

3,481 documents

BigQuant

A brief forum exchange addresses a user whose stock strategy appears not to run. The response suggests two checks: use English names for features, and print the daily buy and sell candidate lists to see whether any stocks meet the strategy’s conditions. The…

EquitiesExecution
BigQuant

This research summary proposes combining price-to-book ratio (PB) with return on equity (ROE) to find companies with stronger fundamentals and lower valuations in China’s A-share market. It treats ROE and other operating measures as indicators of value…

China marketsEquitiesFactor investingPortfolio construction
BigQuant

This market-monitoring report summarizes Chinese trading conditions for July 13, 2022. It reviews broad index and sector performance, then gauges equity sentiment using limit-up and limit-down counts, next-day returns for stocks that had hit either limit,…

EquitiesFuturesSentimentMarket microstructure
BigQuant

This student submission translates a Chinese “dragon returning” trading approach into a factor-based stock strategy. It first identifies strong sectors with sector momentum, then selects leading stocks within them using stock momentum and price-volume…

China marketsEquitiesMomentumMean reversion
BigQuant

The document summarizes a study of dividend-focused Smart Beta strategies in Chinese equities. It argues that dividend factors show a consistent ranking pattern across the CSI 300, CSI 500, and broader market universe, with higher-dividend portfolios…

EquitiesFactor investingChina marketsBacktesting
BigQuant

The document surveys a Chinese securities research team’s work on applying artificial intelligence to quantitative investing. It organizes that research around model evaluation, factor discovery, overfitting controls, synthetic data, and methods intended to…

Machine learningFactor investingEquitiesPortfolio construction
BigQuant

This document summarizes a securities research report on constructing factors from high-frequency data, with a focus on combining intraday and day-level information. It frames the choice of calculation method around whether price and volume signals retain…

EquitiesHigh-frequency tradingFactor investingMomentum
BigQuant

This Chinese-language post discusses connecting BigQuant research with Guojin Securities’ QMT platform for automated live trading. Its concrete example is a stock strategy that first processes daily data to select a watchlist, then monitors those names and…

China marketsEquitiesBreakoutHigh-frequency trading
BigQuant

This equity research note examines suppliers of radio-frequency components for active phased-array radar amid anticipated military equipment upgrades in China. It explains that active arrays connect a separate transmit/receive module to each radiating…

China marketsEquities
BigQuant

This report tests the ratio of research and development spending to revenue as an equity-selection factor across industries. Single-factor tests find some effectiveness in technology-oriented sectors, including pharmaceuticals, electronics, communications,…

China marketsEquitiesFactor investingPortfolio construction
BigQuant

The note answers whether factors shown in BigQuant’s factor dashboard can be referenced directly. It says they cannot be called directly from the dashboard; users need to open a factor’s detail page and extract its expression. When available, the displayed…

Factor investing
BigQuant

The document gives a brief historical overview of quantitative investing. It describes how advances in computing made it practical to store and process large amounts of historical data, supporting the use of statistical and mathematical models in investment…

StatisticsMachine learningBacktesting
BigQuant

A BigQuant user raises a timing problem involving premarket data processing in backtests. In the example, a signal generated on one day leads to an order for the next day; premarket history in the backtest appears to expose that day’s open and close. Such…

BacktestingExecutionMarket microstructureEquities
BigQuant

This educational article introduces support vector machines (SVMs) as classification models, with examples framed around separating two classes using features. It explains the maximum-margin objective: choose a decision boundary that stays as far as possible…

Machine learningStatistics
BigQuant

This report challenges mean-variance optimization assumptions that returns are normally distributed, volatility captures risk symmetrically, and portfolios should maximize return per unit of risk. It instead frames investor concerns as preserving principal…

Multi-assetPortfolio constructionRisk managementStatistics
BigQuant

This article explains a Dual Thrust trend-following method and its application to a basket of nickel, rebar, and coking coal futures. It defines a range from historical highs, lows, and closes, then sets upper and lower breakout thresholds around the current…

FuturesCommoditiesTrend followingBreakout
BigQuant

The article evaluates whether a stock’s overnight return, measured from the prior close to the next open, can proxy for firm-level investor sentiment. The rationale is that retail investors may place orders outside regular market hours, concentrating demand…

EquitiesSentimentMean reversionStatistics
BigQuant

This reference describes several candidate fitness objectives for genetic programming that produces equity factors. It defines IC information ratio as the mean information coefficient divided by its standard deviation, with the information coefficient…

EquitiesFactor investingMachine learningStatistics
BigQuant

This report examines shortcomings in the Henriksson–Merton (HM) and Treynor–Mazuy (TM) models for assessing fund managers’ market and style timing. TM represents beta adjustment as a gradual quadratic pattern, while HM assumes a two-state exposure shift;…

StatisticsFactor investingPortfolio construction
BigQuant

This report overview defines smart beta as a systematic, rules based way to obtain exposure to selected investment factors. It compares the United States and China through their ETF markets, describing differences in product scale, factor coverage, and index…

Factor investingEquitiesChina marketsUS markets
BigQuant

The document outlines the five factors used to explain differences in stock returns: market excess return, company size, book-to-market value, profitability, and investment. It describes each as a comparison between groups of stocks, such as small versus…

EquitiesFactor investingStatisticsPortfolio construction
BigQuant

This BigQuant example builds a daily Chinese-stock portfolio by ranking eligible shares on 30-day turnover variability relative to their industry group. It filters out risk-warning stocks and applies price and listing-age conditions, then selects five names…

EquitiesChina marketsFactor investingPortfolio construction
BigQuant

This market note reviews a modest rebound in Chinese equities and discusses the forces behind it. It attributes the recovery partly to expectations of improved second-quarter corporate earnings and reduced global risk aversion. It also cautions that…

EquitiesChina marketsPortfolio constructionRisk management