Skip to content

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 example code implements a simple long-only threshold strategy for one security. It opens an initial position, then compares each close with the most recent recorded purchase price. A decline beyond the configured buy threshold adds another purchase; a…

Grid tradingEquitiesPosition sizingRisk management
BigQuant

This document outlines a simplified Merrill Clock approach that classifies economic conditions using the direction of year-over-year GDP and CPI changes. It applies moving averages to reduce short-term noise and delays the economic data by one period in…

Multi-assetPortfolio constructionBacktestingStatistics
BigQuant

This short platform guide explains how to limit the prediction or validation stock universe in a visual AI stock selection workflow to a chosen concept sector. It instructs users to insert a shared module for selecting stocks from a specified concept sector…

Machine learningEquitiesChina markets
BigQuant

This strategy description outlines a daily MACD crossover system for Kweichow Moutai shares. It buys when the fast MACD line crosses above the slow line and sells when the slow line crosses above the fast line. The stated setup uses daily stock bars, starts…

EquitiesChina marketsTechnical indicatorsMomentum
BigQuant

This discussion explains when stock universe filters should apply to both model training data and prediction data, and when they might be applied only at trading time. Its general recommendation is to use the same data processing in both sets. Filters that…

Machine learningEquitiesRisk managementBacktesting
BigQuant

This report examines whether mainland China’s northbound investor flows can inform A-share trading. It tests flow thresholds for market timing, ranks sectors and stocks by net inflows, and combines sector selection with stock selection. The timing approach…

EquitiesChina marketsMarket microstructureMomentum
BigQuant

This forum post asks how to test high-frequency equity factors built from minute bars. It cites examples from a China International Capital Corporation multi-factor series: the average squared correlation between the high and low prices of 50-minute bars,…

EquitiesHigh-frequency tradingFactor investingStatistics
BigQuant

This brief Chinese-language assignment submission argues that factor quality matters more than the choice of predictive model: a strong factor is presented as the foundation of a strong strategy. It says the author ran a linear-regression strategy because…

Factor investingMachine learningBacktesting
BigQuant

This essay argues that traders who blame quantitative funds for losses may overlook weaknesses in their own discretionary process. It identifies three recurring pitfalls: emotional decisions, overgeneralizing from vivid stories or isolated winners, and…

EquitiesChina marketsMean reversionMomentum
BigQuant

This midyear financial engineering report reviews China’s equity market through the first half of 2020 and frames its outlook around two themes: timing the market by following trends and reviewing factor-based stock selection. Its summary describes a gradual…

EquitiesChina marketsTrend followingFactor investing
BigQuant

The document outlines a quantitative approach to forming a daily market outlook. It compares the current broad-market setup with similar historical situations, drawing on more than ten years of past market data, and uses the subsequent behavior of those…

StatisticsBacktestingPosition sizingEquities
BigQuant

The document discusses constructing supervised-learning targets from daily Chinese stock data. Its SQL example derives a forward return from later prices, clips extreme values using the first and ninety-ninth percentiles, and selects dates, instruments, and…

China marketsEquitiesMachine learningStatistics
BigQuant

This report studies whether company patent data can help predict stock performance. It compares factors based on patent counts and types, including invention patents, utility models, and design patents. The report treats granted invention patents as the most…

EquitiesFactor investingBacktestingChina markets
BigQuant

This forum post flags a data-quality concern in the net profit year-over-year growth field for Beijing Stock Exchange listings. The author reports substantial differences between the values from two named market-data sources and shows many securities with a…

EquitiesStatisticsChina marketsFactor investing
BigQuant

The document explains VeighNa's standardized datafeed configuration and lists supported providers, their broad instrument coverage, and available data frequencies. Configuration uses a provider name and credentials, with a token placed in the password field…

Multi-assetFuturesExecution
BigQuant

This support exchange compares a median absolute deviation (MAD) clipping calculation with a platform's outlier-removal module. The example method computes a series median, finds the median absolute distance from that value, and clips observations to bounds…

StatisticsEquities
BigQuant

The document summarizes Chinese equity research on refining a traditional idiosyncratic volatility factor. The baseline measure is built from a Fama–French three-factor model. The report links volatility clustering in individual stock returns to persistence…

China marketsEquitiesVolatilityFactor investing
BigQuant

This overview explains automated trading as the use of software to generate or act on trading instructions, place orders, and manage positions with varying degrees of human involvement. It outlines a basic workflow: configure a platform, define entry and…

ExecutionBacktestingRisk management
BigQuant

This screen selects stocks in the metaverse theme whose indicated 9:25 price change is below 6% and whose weekly price crosses above a 30-week moving average. The document presents the theme as a way to focus on a current market segment, the early-session…

EquitiesTechnical indicatorsMomentumChina markets
BigQuant

This Chinese equity-market report uses distance from each stock or index’s highest closing price over the prior 250 trading days to monitor trends and identify potentially leading industries. It counts stocks that reached a 250-day high during the latest 20…

EquitiesChina marketsMomentumTrend following
BigQuant

The post explains Stochastic RSI as an RSI series normalized against its recent range, then smoothed to produce a fast line and a signal line. It relates common naming conventions: the fast %K line corresponds to the Stochastic RSI output, while %D…

Technical indicatorsMomentumCrypto
BigQuant

This introductory article explains overfitting as a model learning quirks in its training data instead of patterns that generalize. It contrasts strong training performance with weaker results on unseen observations, using a résumé screening example, and…

Machine learningStatisticsBacktesting
BigQuant

This research summary examines the ChiNext 50 index through the supply chains of its constituents, arguing that sector weights alone miss how technology firms connect to suppliers and customers. It describes the index as concentrated in technology, with…

EquitiesChina marketsFactor investing