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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
Quantopian lectures
45 documents
Binance API docs
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

21,023 documents

MQL5 code base

The document describes Super Signals, an indicator that marks potential trend changes with arrows derived from price extremums over a period. It notes that the indicator was first implemented in MQL4 and published in 2007. The text provides a brief…

Technical indicatorsTrend followingStatistics
vn.py community

The forum post addresses why the Average True Range calculated in VeighNa may differ substantially from the value shown in TradingView. It proposes checking several potential causes: differences in the ATR formula or smoothing method, discrepancies in the…

Technical indicatorsVolatilityStatistics
ProRealCode

This indicator estimates a month’s historical tendency by examining monthly open-to-close changes across a configurable number of prior years. It accumulates the price changes and counts how often the month closed above or below its open, then reports an…

StatisticsPosition sizingEquities
SuperMind

This proposed Chinese stock screen excludes Beijing-listed stocks and selects for an intraday range above 1%, alongside a condition combining price change with net trading volume attributed to very large orders. The stated threshold for that combined measure…

EquitiesChina marketsMarket microstructureTechnical indicators
SuperMind

This Chinese A-share screening proposal combines three conditions: an intraday range greater than one, return on equity above 15% in each of five consecutive years, and a stated daily maximum decline between 4% and 5%. The explanation interprets the range as…

EquitiesChina marketsFactor investingMean reversion
SuperMind

This technical analysis note proposes measuring how closely two candlestick sequences resemble one another. It describes candles as summaries of open, high, low, and close prices over a chosen time period, then defines a similarity score as the average of…

EquitiesTechnical indicatorsStatisticsChina markets
SuperMind

This post describes a stock selection screen using four conditions: amplitude above 1, current trading volume above 10,000 lots, a higher opening price, and company size above 200 million. The rationale combines price movement and trading activity with a…

EquitiesTechnical indicatorsStatisticsRisk management
MQL5 code base

This indicator description covers applying a stochastic calculation to several RSI variants, including Cuttler’s, Ehlers’ smoothed, Harris’, Rapid, RSX, Slow, and standard RSI. It also describes an option to smooth prices with one of four basic average…

Technical indicatorsStatistics
SuperMind

This article describes an application of autoregressive models to financial time series, using CSI 300 prices and returns as the study data. It presents the topic as a walkthrough of the modeling process, covering fitting and forecasting with an AR model.…

EquitiesStatistics
SuperMind

The document outlines a Chinese A-share screening rule that selects stocks with a daily high-low range of at least one percent, relative volume between 1.5 and 6 times its five-day average, and a nonempty outstanding convertible-bond name field. It…

EquitiesChina marketsTechnical indicatorsStatistics
MQL5 code base

The document explains a simple automated strategy that opens a position only when none are active, then chooses buy or sell through a pseudo-random even-or-odd result. It describes how the order uses configured trade size, slippage, stop-loss, and…

StatisticsRisk managementExecution
SuperMind

This document proposes screening stocks for price amplitude above a threshold, MACD above zero, and a positive change in the KDJ K value. It argues that amplitude can capture movement, MACD can indicate positive trend conditions, and rising K may reflect…

EquitiesTechnical indicatorsMomentumStatistics
BigQuant

This forum post describes a historical data extraction discrepancy between BigQuant versions 1.0 and 3.0. The author reports calculating a 60-period regression slope relating stock returns to a benchmark return series over January 2010. In the stated…

China marketsStatisticsBacktesting
BigQuant

This Chinese-language support exchange asks why BigQuant’s DNN template does not show a separate standardization module and how to handle an error after adding one. The response explains that the DNN is implemented as code and that data processing, including…

Machine learningStatistics
ProRealCode

The Echo Chamber indicator searches past price data for the segment whose closing-price sequence has the highest Pearson correlation with the most recent sequence. It then takes the price path that followed the historical match, scales its range to the…

Technical indicatorsStatisticsBacktesting
SuperMind

This post introduces an autoregressive model for financial time series, using CSI 300 prices and returns as the subjects of study. It says the material walks through fitting the model and attempting forecasts, presenting a modeling workflow focused on this…

EquitiesChina marketsStatisticsBacktesting
SuperMind

The document defines maximum drawdown as the largest decline from a historical net asset value peak to a subsequent trough within a selected period. It frames the measure as an estimate of the worst loss an investor might have experienced after buying a…

Risk managementStatisticsPortfolio construction
BigQuant

The document summarizes research on whether investor sentiment genuinely helps explain cross-sectional stock return anomalies or appears predictive because it is persistent. Persistent predictors can spuriously forecast returns when expected returns also…

EquitiesSentimentStatisticsFactor investing
vn.py community

The article recommends cleaning tick data before using it in strategy research or backtests, since duplicate records, implausible prices, out-of-order timestamps, and missing fields can distort results. Its example workflow sorts records by timestamp,…

Market microstructureBacktestingStatistics
ProRealCode

This indicator measures historical seasonality by grouping monthly price changes by calendar month, using data from a chosen starting year and month through the present. For each month, it reports the average open-to-close return, a normalized rank relative…

StatisticsTechnical indicatorsBacktestingPosition sizing
FMZ forum

The article explains how liquid factor portfolios can approximate some hedge fund returns, potentially offering an accessible, lower cost substitute for investments with limited liquidity, high fees, or high entry barriers. It reviews linear multifactor…

Multi-assetFactor investingPortfolio constructionRisk management
MQL5 code base

The document describes a reusable class for smoothing an array of double-precision values with a classical moving-average approach. The user supplies an input array, a smoothing period, and the array dimension; initialization prepares the required arrays,…

Technical indicatorsStatistics
BigQuant

The document introduces a stock factor study based on cumulative net money flow over the previous 20 trading days, scaled by the stock’s market capitalization on the current day. It presents this normalization as a way to compare flows across stocks and…

EquitiesFactor investingStatistics
BigQuant

This weekly report reviews Chinese market conditions and fund activity, with particular attention to plans to include exchange-traded funds in the Stock Connect program and the approaching release of restrictions on shares in the first public REITs. It also…

China marketsEquitiesFixed incomeStatistics