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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
QuantRocket
7 documents
Lumibot strategies
7 documents
Awesome Quant
1 documents

Search the library

3,481 documents

BigQuant

The document reports a question about inconsistent price bases in a Chinese stock strategy backtest. A user compares adjusted closing prices retrieved from a stock factor data table with a position cost price returned after placing an order. The former is…

EquitiesBacktestingRisk management
BigQuant

The report evaluates ten equity valuation measures, including earnings, book, sales, cash flow, dividend, enterprise value, and growth based ratios. It first describes how factor levels vary across industries and company sizes, and how those relationships…

EquitiesFactor investingStatisticsBacktesting
BigQuant

This research roundup describes two separate studies. The first examines the Stochastic Volatility Inspired (SVI) parameterization for modeling implied volatility surfaces. It reports theoretical results and empirical analysis suggesting that, under…

OptionsVolatilityDerivatives pricingStatistics
BigQuant

A forum question examines whether checking an asset's tradeability during a daily backtest is useful when the resulting order may execute on the following day. The concern is that an asset deemed tradable on the signal date could be suspended by the time the…

BacktestingExecutionEquities
BigQuant

This research note describes a method for detecting support and resistance lines in Chinese A-share price data and studying breakout behavior. It defines slope patterns for continuation formations, including triangles, rectangles, flags, and broadening…

EquitiesChina marketsBreakoutTechnical indicators
BigQuant

This forum exchange addresses two practical questions about factor analysis: how to submit a factor that needs Python processing beyond SQL, and whether factor values must exist for every stock on every trading day. The reply says the SQL field may be left…

Factor investingEquitiesStatistics
BigQuant

The report examines how different types of restricted-share unlocks relate to stock performance before and after the release date. It describes supply pressure from newly tradable shares and anticipatory trading by other market participants as possible…

China marketsEquitiesEvent-drivenBacktesting
BigQuant

This summary of a Goldman Sachs outlook presents a framework for assessing China’s 2022 equity market across macroeconomic growth, corporate earnings, market cycles, policy, politics, regulation, and valuation. The report expected slower growth amid…

EquitiesChina marketsFactor investingRisk management
BigQuant

This reference explains how a futures platform derives performance and activity measures at four levels: individual accounts, weighted account portfolios, individual strategies, and weighted strategy portfolios. It maps daily balance, fees, margin, risk,…

FuturesStatisticsRisk managementPortfolio construction
BigQuant

The article proposes a discretionary screen for Chinese stocks that may be entering a strong upward move. It combines four price and volume features: at least one limit-up session in roughly the prior month, an upward price gap, a run of at least four or…

EquitiesChina marketsMomentumBreakout
BigQuant

The document outlines a portfolio-allocation framework built around five macro risk factors: economic growth, consumer inflation, producer inflation, interest rates, and exchange rates. It describes constructing tradable factor proxies, reducing overlap…

Multi-assetPortfolio constructionRisk managementFactor investing
BigQuant

The document shows a SQL query that combines Chinese stock data with valuation, profitability, growth, liquidity, leverage, turnover, and price-volume measures. Examples include book-to-market, earnings-to-price, sales-to-price, cash-flow-to-price, EBITDA…

EquitiesFactor investingTechnical indicatorsChina markets
BigQuant

This brief note frames Chinese A-share price-volume factors as potential signals of local trading behavior. It argues that prices can deviate from underlying value when trading activity affects how individual stocks are priced. Price reversal measures…

EquitiesChina marketsFactor investingMean reversion
BigQuant

The document outlines an equity screening idea for mainland Chinese main-board stocks. It combines a robotics-industry theme, a limit on circulating market capitalization, a specified turnover range, and a rising KDJ reading. It includes example screening…

EquitiesChina marketsTechnical indicatorsMomentum
BigQuant

This 2018 market commentary explains a sharp equity selloff through the interaction of growth, inflation expectations, and the expected pace of Federal Reserve rate increases. It uses a simple valuation relationship—earnings divided by interest rates plus…

EquitiesFixed incomeCommoditiesVolatility
BigQuant

This research summary tests stock-selection signals derived from candlestick upper and lower shadows, then compares them with shadow measures based on the Williams indicator. The reported results distinguish the two approaches: candlestick upper-shadow…

China marketsEquitiesTechnical indicatorsFactor investing
BigQuant

The document introduces the standard form of an equity multi-factor model: stock returns are represented as a linear combination of factor returns, plus a residual component that the factors do not explain. It also notes that a portfolio’s return can be…

EquitiesFactor investingPortfolio constructionStatistics
BigQuant

This note describes ways to reduce memory use and speed up parameter tuning for an ETF rotation strategy. It recommends moving suitable calculations into SQL, loading only needed data, reusing cached data, releasing large objects, precomputing values during…

BacktestingPortfolio constructionExecution
BigQuant

This brief event description presents a practical application of large language models to automated trading. Its central idea is a digital trader that interprets natural-language instructions and connects them to trade execution, with examples intended to…

Machine learningExecution
BigQuant

This study examines equity factors built from changes in analyst forecasts and tests how forecast stability affects their relationship with next-month stock returns. It reports that revision factors are positively associated with subsequent returns, but…

EquitiesFactor investingStatisticsBacktesting
BigQuant

This brief discussion outlines a short-term approach centered on stocks that open sharply higher. It argues that a gap-up can indicate strength, but says the opening move should be evaluated alongside additional signals, including buying pressure, relative…

EquitiesMomentumBreakoutExecution
BigQuant

The document explains how factor-based Smart Beta products can serve investors seeking diversified equity exposure and can act as underlying holdings in fund-of-funds portfolios. It describes the approach as using passive strategies that increase exposure to…

Factor investingPortfolio constructionEquitiesChina markets
BigQuant

This Chinese-language account describes a learning project that builds a China stock selection strategy with five ranked factors and a two-day forward price label. It trains a Ridge regression model, standardizes the inputs, and periodically retrains before…

Machine learningEquitiesFactor investingBacktesting
BigQuant

This short platform discussion addresses why a strategy may appear to buy and sell on the same day despite China’s T+1 stock-trading convention. The suggested code adjustment is to make the sell conditions refer to currently held instruments rather than the…

China marketsEquitiesExecutionBacktesting