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
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
QuantRocket
7 documents
Lumibot strategies
7 documents
Awesome Quant
1 documents

Search the library

3,481 documents

BigQuant

This study treats a convertible bond as combining straight-bond value and embedded equity-option value, and examines how bond returns relate to the underlying stock. It reports positive return correlation across conversion-status groups, with average…

Fixed incomeOptionsFactor investingPortfolio construction
BigQuant

The document describes a stock-selection research task: detect a recent unusual move, then retrieve that event day’s opening price for use in a later buy condition. The example defines an event as trading volume more than twice the previous comparison value…

EquitiesEvent-drivenBacktesting
BigQuant

The document introduces the Key Reversal technical indicator and names its inputs: closing, high, and low prices, along with lookback lengths and a day parameter. Its pseudocode defines a lower band from the lowest low over a selected window and an upper…

Technical indicatorsBreakout
BigQuant

The document gives a brief overview of artificial intelligence, from the field’s origins to its wider adoption as data, computing hardware, and algorithms advanced. It describes AI as systems that model aspects of human reasoning and notes its use in…

Machine learningSentimentPortfolio construction
BigQuant

The article outlines a workflow for reconstructing and simulating a Chinese public fund’s equity holdings. It scrapes disclosed stock codes and portfolio weights for a China Merchants CSI 300 enhanced index fund, then assumes quarterly rebalancing: the…

China marketsEquitiesMachine learningBacktesting
BigQuant

The research note introduces APB, a stock factor intended to estimate buying and selling pressure from the relationship between price and volume. It defines the measure as the logarithm of the ratio between an equally weighted average price and a…

EquitiesChina marketsFactor investingStatistics
BigQuant

This report summary compares two ways to classify the investment style of equity funds for fund-of-funds research. Holdings-based analysis infers style from reported portfolio positions, while returns-based analysis infers it from portfolio performance.…

EquitiesPortfolio constructionStatistics
BigQuant

This brief BigQuant forum answer addresses how to inspect the holding date for a particular stock position during a backtest. It points to retrieving the position from the backtest context by instrument and reading the position’s last sale date. That date…

EquitiesBacktesting
BigQuant

The document summarizes research on stock resiliency, labeled RES, as an expanded measure of liquidity. The cited study examines whether stocks with greater illiquidity earn a return premium, using resiliency as an additional measure alongside conventional…

EquitiesMarket microstructureStatisticsFactor investing
BigQuant

This daily futures strategy uses Bollinger Bands to signal directional trades when the close reaches or crosses an outer band. The middle band is an N-period simple moving average of closing prices, with upper and lower bands set by adding or subtracting K…

FuturesBreakoutTechnical indicatorsBacktesting
BigQuant

The note explains why a stock’s closing price shown on a quantitative trading platform can differ substantially from the price shown by a brokerage or market-data app. The platform adjusts historical price data to account for corporate actions, so the…

EquitiesChina markets
BigQuant

This empirical study adapts the Fama–French five-factor framework to China’s A-share equities. It constructs market, size, book-to-market, profitability, and investment factors from monthly stock data, then forms size-sorted portfolios crossed with…

China marketsEquitiesFactor investingStatistics
BigQuant

This discussion addresses a strategy that runs successfully in backtesting but fails during a simulated live trial. A suggested cause is a missing-data processing step that removes every row because one or more columns contain empty values. The proposed…

BacktestingStatistics
BigQuant

This literature note summarizes research on whether individual investors favor mutual funds that have recently produced unusually large positive returns. The study defines a fund-level MAX measure of extreme gains and reports that funds with higher MAX…

SentimentStatistics
BigQuant

This MetaTrader 5 expert advisor is designed to manage account equity and individual open trades, then place a grid of pending orders when price reaches a user-specified level. The trader must decide in advance where a grid would be appropriate; the EA does…

ForexGrid tradingExecutionRisk management
BigQuant

This research summary adapts Joel Greenblatt’s value-and-quality stock-ranking idea to China’s A-share market. It uses EV/EBITDA as a valuation measure and ROIC as a business-quality measure in place of the original formula’s measures. The described screen…

EquitiesChina marketsFactor investingBacktesting
BigQuant

This report outlines a framework for studying rotation among five Chinese equity style pairs: large and small cap, value and growth, consumption and cyclical, financial and nonfinancial, and technology and traditional industries. It describes building…

EquitiesFactor investingChina marketsStatistics
BigQuant

This report summary describes three methods for rotating among equity industries using macroeconomic information. The first models industry excess returns from cyclical components of leading indicators spanning growth, inflation, trade, and liquidity. The…

EquitiesChina marketsFactor investingPortfolio construction
BigQuant

This research review examines whether sell-side analyst output matters more during economic downturns, when uncertainty makes company valuation harder for both analysts and investors. Drawing on earnings forecasts and stock recommendations over several…

EquitiesStatisticsEvent-driven
BigQuant

This study examines holdings reported by institutions using the Stock Connect channels into mainland China, comparing static position and daily increase factors. It reports that Morgan Stanley Hong Kong Securities had stronger historical information…

EquitiesChina marketsFactor investingMomentum
BigQuant

The document compares Rust with C++, Java, Python, and Go for quantitative trading systems. It presents Rust as a way to reduce certain programming errors and support production debugging, while claiming that it offers performance close to C++, can use less…

High-frequency tradingExecutionRisk management
BigQuant

The report proposes left- and right-tail conditional value-at-risk factors from intraday stock returns. For each stock, it describes measuring the average returns beyond the lower and upper 5% quantiles, then averaging daily values across a 20-trading-day…

EquitiesVolatilityRisk managementFactor investing
BigQuant

This article argues that a sharp bullish candle during a decline should be judged by the likely position and cost basis of the buyers behind it, rather than by candle size alone. It proposes a “3D” screen for small, low-float, low-priced stocks after a…

EquitiesTechnical indicatorsBreakoutMarket microstructure
BigQuant

This article proposes reading a stock’s volume ratio together with its turnover rate to assess changes in trading activity. It assigns interpretations to several combinations: turnover above 5% with a volume ratio of 2–3 as an early activity signal; turnover…

EquitiesTechnical indicatorsMomentumMarket microstructure