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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

This proposed Chinese equity screen combines membership in the metaverse industry with a rounded price pattern and seven consecutive down sessions. The accompanying explanation frames the falling-price condition as an added technical filter intended to…

China marketsEquitiesTechnical indicatorsMomentum
BigQuant

This report explains how the MSCI China A50 Connect Index selects and weights large-cap Chinese equities. It chooses stocks across GICS industries, first taking leading free-float market-cap names by industry and then filling to 50 constituents; weights are…

EquitiesChina marketsFactor investingPortfolio construction
BigQuant

This study examines quantitative stock selection within China’s electronics and electronic-components sectors. It reviews conventional fundamental and price-volume factors, reporting promising selection results for valuation, quarterly profit growth, return…

EquitiesFactor investingChina marketsBacktesting
BigQuant

The document introduces the Bias indicator, which expresses a closing price’s percentage deviation from its moving average over a chosen number of days. The calculation compares the close with the moving average, subtracts the average, and scales the…

Technical indicatorsStatistics
BigQuant

Return on equity (ROE) measures net income relative to shareholders’ equity, expressing how much profit a company generates from its equity base. The document gives the formula and a simple numerical illustration, then describes how investors may interpret…

EquitiesFactor investingStatisticsRisk management
BigQuant

The document describes a stock strategy that scores candidates with a neural network, buys up to three holdings, and aims to sell each after three trading days. It stores each stock and its entry-day index in a context list, then compares that index with the…

EquitiesPosition sizingExecutionBacktesting
BigQuant

This weekly report assesses Chinese equity-market sentiment after a sharp March decline and a subsequent rebound. Its composite sentiment score rose from 38 to 51, while the authors judged that near-term further weakness had become less likely, despite…

EquitiesSentimentFuturesOptions
BigQuant

This tutorial develops a stock factor from the sum of trading volume during the first 15 minutes of a session. It explains why opening activity may be informative: overnight news is reflected in early trading, the opening period contributes to price…

EquitiesTechnical indicatorsFactor investingHigh-frequency trading
BigQuant

The discussion compares quantitative research practices in China and overseas. It says Chinese investors more often try to predict stock prices directly, while overseas researchers may estimate missing observations, factor values, company revenue, or…

Machine learningStatisticsEquitiesChina markets
BigQuant

This post describes a live-order funding problem in an equities strategy. A buy signal was calculated using the previous close for 18,100 shares, while the stock opened higher and the trader submitted the order near the open using the fifth ask level. With…

EquitiesExecutionPosition sizingRisk management
BigQuant

The document addresses how to combine multiple stock-selection factors when they have different preferred directions. Its example asks how to score one factor from low to high and another from high to low, then rank securities by the average of their scores.…

EquitiesFactor investingPortfolio construction
BigQuant

This brief explanation describes “doing T” in Chinese equities: using intraday buys and sells to adjust the cost basis of an existing position, despite the market’s T+1 settlement rule. It says the trader needs to keep cash available rather than invest the…

EquitiesChina marketsGrid tradingPosition sizing
BigQuant

This guide outlines a workflow that combines TQ EDB market and indicator data services with Coze as a conversational research assistant. After adding the EDB skill, a researcher can describe a task and request data retrieval, idea checks, simple backtests,…

FuturesCommoditiesBacktestingStatistics
BigQuant

This Chinese-language research summary describes a stock-selection factor built from quarterly profitability data. It defines a trend measure as the sensitivity of profitability to time in a linear regression, with separate versions based on…

EquitiesFactor investingStatisticsBacktesting
BigQuant

The article reviews research on the 2016 launch of Morningstar’s sustainability ratings for U.S. mutual funds. The ratings use portfolio holdings and company ESG scores to assign funds one to five stars within their categories; the star display appears more…

EquitiesStatisticsSentimentEvent-driven
BigQuant

This guide recommends choosing community trading strategies according to an investor's capital, return expectations, and tolerance for drawdown. It distinguishes a conservative profile, associated with diversified holdings, a smoother equity curve, a longer…

Risk managementBacktestingPortfolio constructionPosition sizing
BigQuant

This indicator description explains a ZigZag variant that calculates turning points from the high and low values of Heikin Ashi candles. The Heikin Ashi period is configurable, and users can choose whether the Heikin Ashi candles themselves are displayed.…

Technical indicatorsVolatility
BigQuant

This article examines whether financial factors such as value, size, profitability, investment, and momentum can be timed using predictive signals. It groups candidate signals into financial conditions, economic conditions, investor sentiment, factor…

Factor investingEquitiesMomentumSentiment
BigQuant

The report describes an asset allocation approach that measures cycle states and uses machine learning to estimate the probability that assets will outperform one another. It reviews macroeconomic timing frameworks, then describes cycle factors derived from…

Multi-assetMachine learningStatisticsPortfolio construction
BigQuant

This tutorial surveys support vector machines, k-nearest neighbors, naive Bayes, and the perceptron as lightweight classifiers for relatively small datasets and feature sets. It explains SVM’s maximum-margin boundary, the role of support vectors, soft…

Machine learningStatistics
BigQuant

This April 2020 market note combines valuation, trading activity, sentiment, sector flows, and style factor monitoring to assess Chinese equities. It describes subdued market turnover and relatively low overall valuations, while agriculture-related stocks…

EquitiesChina marketsFactor investingMomentum
BigQuant

This forum question concerns adding a moving-average exit condition to an AI stock-selection backtest. The proposed logic waits until a minimum holding period has passed, then examines positions in reverse StockRanker prediction order and sells eligible…

EquitiesTechnical indicatorsBacktestingExecution
BigQuant

The document presents a way to estimate how often a one-minute Chinese convertible-bond bar closes above its open after three consecutive up bars. It converts each bar’s return into a binary up-or-not indicator, scans the series for three up bars, and counts…

StatisticsBacktestingTechnical indicatorsFixed income
BigQuant

This review of factor performance during the 2018–2020 quant crisis examines why diversified equity strategies struggled. It analyzes standard size, value, investment, profitability, and momentum factors, alongside portfolios formed by sorting stocks on size…

EquitiesFactor investingMomentumStatistics