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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
WonderTrader
14 documents
Alphalens
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

This market note summarizes a difficult week for major Chinese equity indexes and sectors, then reports changes in factor behavior. It says quality and analyst sentiment factors strengthened relative to the prior week, while value, reversal, and alternative…

China marketsEquitiesFactor investingMomentum
BigQuant

This Chinese language literature digest summarizes research on return predictability and portfolio covariance estimation. One study examines stock prices and dividends in the Netherlands, the United Kingdom, and the United States over nearly four centuries.…

EquitiesFactor investingStatisticsPortfolio construction
BigQuant

This research summary examines how broad equity factors behaved across Chinese A-share industries from July 2009 through November 2018. It links differences in factor effectiveness to industry characteristics: small-cap effects were stronger in industries…

EquitiesChina marketsFactor investingPortfolio construction
BigQuant

This tutorial introduces two strategy-building approaches on BigQuant: an AI-driven workflow that trains a model from selected factors and filters, and a user-coded approach with explicit selection rules. It focuses on the latter, outlining how to clone a…

EquitiesChina marketsBacktestingFactor investing
BigQuant

This BigQuant example assembles a China A-share workflow from stock selection through backtesting. It selects eligible main board, STAR Market, and ChiNext stocks associated with the CSI 1000, then calculates current and lagged volume relative to a five-day…

EquitiesChina marketsTechnical indicatorsBacktesting
BigQuant

This meetup note explains factor exposure as an asset’s sensitivity to factor returns. It sketches a way to estimate that sensitivity: form a low-versus-high valuation long-short portfolio, treat its return series as the factor return, and regress an asset’s…

EquitiesFactor investingStatisticsPortfolio construction
BigQuant

This legacy platform example shows how to model a stock purchase at a specified price relative to the day’s open. A custom slippage model sets buy orders at 98% of the opening price, while sell orders use the current close. A daily order check compares the…

EquitiesExecutionBacktestingMarket microstructure
BigQuant

This discussion examines how to exclude Chinese convertible bonds after an issuer announces early redemption. The author found that the platform’s redemption-terms table showed one row each for two example bonds, including contractual trigger conditions,…

Fixed incomeChina marketsEvent-drivenBacktesting
BigQuant

This article discusses practical choices when tuning a short-term stock-selection strategy: starting capital, number of holdings, capital allocated per holding, holding period, and factor selection. Its author argues that the number of names and per-name…

EquitiesFactor investingPosition sizingBacktesting
BigQuant

The document examines whether rolling Fama-French five-factor (FF5) alphas can guide U.S. sector rotation. It compares FF5 with the three-factor model (FF3), using monthly returns for ten U.S. industry portfolios from 1964 to 2014. The rotation signal is…

Factor investingEquitiesPortfolio constructionBacktesting
BigQuant

This Chinese-language assignment turns a discretionary trading idea into a simple rule for constituents of the CSI 300: buy when the five-day moving average crosses above the ten-day average and MACD is positive, and sell otherwise. It also sketches a…

China marketsEquitiesTechnical indicatorsMomentum
BigQuant

This research summary tests whether negative sentiment in posts on Xueqiu, a Chinese investing forum, can help time major Chinese equity indexes. It describes using machine learning to classify post sentiment and building a weekly negative-sentiment ratio…

SentimentMachine learningEquitiesChina markets
BigQuant

The article summarizes research on how speculative stocks perform around earnings announcements. It measures speculative characteristics using proxies such as maximum daily return, idiosyncratic volatility, price, expected skewness, and jackpot probability,…

EquitiesEvent-drivenSentimentFactor investing
BigQuant

This brief support exchange asks how the numbers displayed after decision branches in a visual stockRanker model are calculated. The response points the reader toward material on tree models and information entropy, implying that the displayed values relate…

Machine learningStatistics
BigQuant

The article introduces quantitative trading as the use of mathematical models, statistical analysis, historical and real-time market data, and algorithms to guide or automate decisions. It describes stock screening and rule-based execution as common…

EquitiesMachine learningFactor investingBacktesting
BigQuant

This brief support exchange addresses a user’s report that a hyperparameter module raises a key error even though the key appears in the visual chart and can be found in code-mode parameters. The response attributes the issue to an error in the…

Machine learningBacktestingStatistics
BigQuant

This forum post describes an attempted 12–1 momentum strategy on S&P 500 constituents and reports two backtest problems: target-percent orders repeatedly encounter null prices, and a visual workflow produces no instruments or trades. The strategy ranks…

EquitiesUS marketsMomentumBacktesting
BigQuant

This brief describes a deep neural network approach intended for quantitative stock selection. Its stated implementation goals are to run on systems with limited memory, use GPU acceleration when available, and adapt the number of input features. It also…

EquitiesMachine learningBacktesting
BigQuant

The article explains five behavioral traps that it associates with retail trading losses: confirmation bias, reacting to noisy opening-auction signals, trying to recover losses through riskier trades, loss aversion that delays selling, and greed that delays…

Risk managementSentimentEquitiesChina markets
BigQuant

This meetup Q&A surveys several quantitative trading topics: using Level 2 order-book data, reproducing a legacy strategy, allocating idle capital to a gold ETF, factor decomposition, building CNN strategies, and portfolio optimization. Most answers point…

Portfolio constructionRisk managementMachine learningMarket microstructure
BigQuant

This forum post records an attempt to create an A-share factor from securities appearing on the trading ranking list, using a transaction category and several broker department codes. The submitted expression tests whether the category matches a specified…

EquitiesChina marketsFactor investingStatistics
BigQuant

The article presents a scenario analysis of how sustained high crude prices could affect energy-importing and energy-exporting economies. It argues that higher energy costs may shift income toward resource exporters, raise manufacturing expenses in importing…

CommoditiesVolatilityMulti-asset
BigQuant

The document introduces the task of developing a complete strategy from daily factors extracted with a high-frequency expression engine. It identifies strategy development as the topic of a meetup presentation and points readers to a related recording, but…

Factor investingMachine learningBacktesting
BigQuant

This report examines listed companies’ interest-bearing debt as a quantitative stock-selection and risk-screening measure. It defines the debt measure around short-term and long-term borrowings and bonds, and observes that debt ratios tend to reflect…

EquitiesRisk managementFactor investingBacktesting