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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
QuantRocket
7 documents
Lumibot strategies
7 documents
Awesome Quant
1 documents

Search the library

3,481 documents

BigQuant

This study examines the low-volatility effect in Chinese A-shares using price amplitude as a volatility proxy. The original amplitude factor has negative stock-selection ability, but its performance is unstable: the reported monthly IC and rank IC are…

China marketsEquitiesFactor investingVolatility
BigQuant

The document summarizes research on how high-frequency trading in equities affects liquidity in options on those stocks. The study combines Nasdaq HFT records with options transaction data and other market data for 103 stocks, then uses instrumental-variable…

EquitiesOptionsHigh-frequency tradingMarket microstructure
BigQuant

This account summarizes a 2021 conference talk on using machine learning to price stocks. A simple example feeds market-wide daily open, high, low, close, and average prices into an LSTM time-series model. The speaker stresses preparing noisy financial data,…

EquitiesMachine learningBacktestingStatistics
BigQuant

This Chinese-language forum exchange addresses a data handling issue that can arise after computing regression coefficients with an OLS factor expression. The questioner finds that beta values appear in DataFrame cells as array-like objects rather than as…

Factor investingStatistics
BigQuant

The article introduces a stock-analysis framework built around candlesticks, trading volume, moving averages, and financial statements, then focuses on candlestick interpretation. Its central setup is a strong bullish candle breaking above a prolonged…

EquitiesBreakoutMomentumTechnical indicators
BigQuant

This short Chinese-language forum exchange addresses how to preserve promising results from a quantitative strategy’s hyperparameter search. The example need is to save parameter sets whose score exceeds a chosen threshold. The poster reports that attempts…

BacktestingStatistics
BigQuant

This research explores shared analyst coverage as a way to represent links between Chinese A-share companies. It extends direct links to indirect, multi-step connections, arguing that these can reveal less visible information spillovers, especially for…

China marketsEquitiesFactor investingMean reversion
BigQuant

The document summarizes two strands of research. One examines analyst-run mutual funds across multiple fund companies, reporting that analyst-managed funds outperformed comparison funds on risk-adjusted measures and that stronger analyst skill was associated…

EquitiesFactor investingStatisticsRisk management
BigQuant

The document describes two measures of active fund manager ability based on whether a manager’s holdings or portfolio changes resemble those of historically capable peers. The holdings measure assigns stocks a quality score from the weighted skill estimates…

EquitiesFactor investingPortfolio constructionBacktesting
BigQuant

The document summarizes lifecycle fund design through human-capital theory and liability-driven dynamic asset allocation. Under stated assumptions, it says an optimal glide path can be derived analytically, and discusses how design factors affect the path.…

Multi-assetPortfolio constructionRisk managementTrend following
BigQuant

This brief research submission describes an experiment on stocks priced between zero and two yuan, using three five-day factors: momentum, reversal, and volatility. The author says the backtest results were weak and asks for ideas to improve the analysis.…

China marketsEquitiesMomentumMean reversion
BigQuant

This short BigQuant forum post concerns a modified XGBoost strategy whose equity curve and recent trade records appear unchanged despite adjustments to the data. The response offers two possible explanations: the backtest module may be reusing cached…

Machine learningBacktestingEquities
BigQuant

The report extends a single-asset drawdown adjustment approach to portfolios of strategies. It describes selecting the control parameter gamma directly from the single-dimension result, avoiding Monte Carlo optimization for the multidimensional case. The…

EquitiesRisk managementPortfolio constructionPosition sizing
BigQuant

The article explains recurrent neural networks and LSTM gates, then outlines an A-share stock-selection example that predicts five-day returns from sequences of seven factors. It describes missing-value handling, outlier filtering, standardization, and…

EquitiesMachine learningFactor investingBacktesting
BigQuant

This article introduces a custom-coded stock selection strategy built around five rules, mainly seeking stocks that have fallen sharply and begun to stabilize, with some rules intended to capture possible strong buying. It contrasts rule-based strategies,…

EquitiesMean reversionBacktestingPosition sizing
BigQuant

The article explains how risk-constrained Kelly sizing modifies the classic Kelly approach, which chooses a capital fraction to maximize long-run log growth but can produce large drawdowns. The constrained version adds a limit on the probability that wealth…

Risk managementPosition sizingBacktestingMachine learning
BigQuant

The document describes a China equity index enhancement approach that combines a multi-factor return forecast with portfolio constraints. Candidate factors span size, valuation, growth, profitability, technical signals, liquidity, and volatility. Symmetric…

EquitiesFactor investingPortfolio constructionRisk management
BigQuant

The document outlines a framework for allocating across asset classes according to macroeconomic trends. It first identifies whether individual indicators are rising or falling, using historical averages or filtering, then compares asset returns over the…

Multi-assetPortfolio constructionBacktestingStatistics
BigQuant

This overview surveys a broad set of quantitative approaches, describing their basic mechanisms and the market settings or investor capabilities they may suit. It covers trend following, machine learning, arbitrage and market neutral methods, factor…

Trend followingArbitrageFactor investingMachine learning
BigQuant

This Chinese-language research abstract describes a study of order sizes in stock-level tick data. It reports a Pareto-like pattern: small orders occur more often than large orders, with order-size frequencies declining according to a power law. The authors…

EquitiesFactor investingStatisticsMarket microstructure
BigQuant

This short platform discussion addresses whether a backtest can sell existing holdings at the open and use the proceeds to buy other stocks at that same open. The questioner reports that setting both order prices to the open did not make sale proceeds…

EquitiesBacktestingExecution
BigQuant

This study compares time-series and cross-sectional standardization of price and volume factors in an A-share stock-selection setting. It uses a dataset spanning 2011–2022 with 98 daily factors and a five-day return label, and compares LightGBM and deep…

EquitiesChina marketsMachine learningFactor investing
BigQuant

This Chinese-language forum post addresses two data needs in quantitative stock research: constructing weekly bars from daily observations and obtaining historical quarterly financial measures such as return on equity. It outlines grouping daily data by…

EquitiesChina marketsStatisticsFactor investing
BigQuant

This report summary describes a fund-selection approach that uses portfolio holdings to estimate managers’ stock-picking and market-timing abilities. Holdings provide information for attributing and forecasting performance that is not available from fund net…

Factor investingStatisticsPortfolio constructionChina markets