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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
Quantpedia
86 documents
TqSdk
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

12,303 documents

BigQuant

This report summary examines ways to improve measures used to monitor crowding in Chinese equity factors. It focuses on pair correlation and factor volatility, two of four measure families previously tested alongside valuation spreads and long-term return…

EquitiesFactor investingStatisticsVolatility
ProRealCode

The document describes a moving average inspired by an electronic RC filter. It combines an amplitude filter based on average true range with a frequency filter intended to suppress waves whose periods are shorter than a threshold derived from the filter…

Technical indicatorsTrend followingVolatility
SuperMind

The document describes a Chinese equity screening rule that selects stocks with turnover between 3% and 12%, a positive ten-day return below 35%, and an average true range above 1. It frames the filters as a way to find stocks with moderate trading activity,…

China marketsEquitiesTechnical indicatorsVolatility
SuperMind

This Chinese equity screening proposal combines three filters: prior-session price amplitude above a threshold, an opening price near the 10-day moving average, and an activity measure based on the previous day’s turnover multiplied by the ratio of today’s…

China marketsEquitiesTechnical indicatorsVolatility
MQL5 code base

This indicator describes a daily breakout approach based on the previous session’s high and low. A close above or below those boundaries is treated as a possible entry signal, with separate Fibonacci-based stop and profit levels projected from the prior…

BreakoutTechnical indicatorsVolatilityRisk management
SuperMind

This note describes a Chinese A-share screening rule that selects stocks when the daily high-to-low range exceeds 1% and the 14-period RSI is below 65, limited to observations from 2021. It gives equivalent conditions for a charting formula and a Python…

EquitiesTechnical indicatorsVolatility
MQL5 code base

This document describes an MQL5 indicator that draws two colored filled regions between channel values produced by the GRFLeadingEdger indicator on a bar. Its configurable inputs include a sample count, look-ahead setting, two standard-deviation levels,…

Technical indicatorsVolatility
MQL5 code base

The KCI Directional Matrix is presented as an indicator with three bounded outputs: a main line for directional efficiency or trend expansion, plus and minus lines for bullish and bearish pressure. The described calculation separates upward and downward…

Technical indicatorsMomentumVolatilityStatistics
MQL5 code base

This indicator combines a straight-line regression to estimate trend direction with a curved regression channel to represent changing support and resistance. It measures price dispersion using root-mean-square deviation, then applies Fibonacci coefficients…

ForexTechnical indicatorsTrend followingVolatility
SuperMind

This screening rule looks for Chinese A-shares with a daily high-low range of at least 1% and relative volume between 1.5 and 6, while excluding stocks from Beijing and Tianjin markets. The article frames the range condition as a way to find more active…

EquitiesChina marketsVolatilityTechnical indicators
ProRealCode

The indicator uses Bollinger Band widths calculated over two lookback lengths to flag a possible range or contraction regime. It computes the distance between the upper and lower bands for the longer window and for the shorter window. When the shorter-window…

Technical indicatorsVolatilityMean reversion
MQL5 code base

Historical volatility describes how widely an asset's returns have varied over a chosen period. The document presents standard deviation as the common calculation approach, while noting that it is not the only possible method. A higher reading indicates…

VolatilityStatisticsRisk management
MQL5 code base

This indicator applies Ehlers’ nonlinear Kalman filter to deviation estimation as an alternative to standard-deviation measures based on moving averages. The description emphasizes responsiveness as an important property of volatility estimates and offers…

VolatilityTechnical indicatorsStatistics
MQL5 code base

The document presents a script that estimates a power factor from historical price increments and uses the estimate to characterize a market as more range-bound or more prone to volatile, heavy-tailed moves. It reports example estimates across EUR/USD,…

StatisticsVolatilityMean reversionTrend following
Amberdata research

This newsletter connects a forthcoming Federal Reserve decision with crypto markets and options positioning. It reports market expectations for a rate cut, summarizes recent macroeconomic context, and outlines a base case in which an expected decision could…

CryptoOptionsVolatilityDerivatives pricing
SuperMind

This stock-selection screen targets mainland Chinese equities outside Beijing, requiring a daily high-low range above 1% and a circulating market value between 5 billion and 10 billion yuan. The document provides both an indicator formula and a Python…

EquitiesChina marketsVolatilityTechnical indicators
SuperMind

This note describes an A-share stock screen combining price movement, a fixed closing price, and prior-day auction turnover. The stated criteria are amplitude above 1%, a close of 18.5 yuan, and auction turnover above 0.26. It presents the screen as a way to…

EquitiesChina marketsVolatilityTechnical indicators
SuperMind

This document proposes selecting stocks with amplitude above 1%, a specified turnover-to-auction-volume ratio between 0.5 and 2, and a weekly price crossover above the 30-week average. It frames the filters as a combination of price variability, trading…

EquitiesChina marketsVolatilityTrend following
SuperMind

This document describes a Chinese equity screen that excludes Beijing-listed shares and selects stocks with a daily high-low range above 1% and prior-day trading value above 60 million. It presents the filters as signals of price variability and market…

EquitiesChina marketsVolatilityTechnical indicators
SuperMind

This A-share screening idea combines a daily amplitude threshold, a turnover-rate band, and a candlestick condition described as a morning-star signal. The stated rationale is to find stocks with notable price movement and active trading, then use the…

EquitiesChina marketsTechnical indicatorsVolatility
SuperMind

This A-share stock screen combines daily amplitude above 1%, tradable share count no greater than 5.5 billion, and a closing price between the middle and upper Bollinger Bands. The article presents the band position as a way to identify stocks in an upward…

EquitiesChina marketsTechnical indicatorsVolatility
Amberdata research

The newsletter argues that Bitcoin remained in a short volatility and price consolidation regime, while Solana offered more relative volatility interest. It points to Bitcoin’s modest weekly price change, options-implied weekly movement, and limited…

CryptoOptionsVolatilityDerivatives pricing
Amberdata research

This podcast summary covers derivatives trader Gordon Grant’s discussion of volatility across asset classes and in crypto options. Topics include quoting interest-rate volatility in basis points to compare different tenors, how zero-rate policies can affect…

CryptoOptionsVolatilityMarket making
MQL5 code base

This document describes iMAX3, a configurable indicator for detecting trend direction. Its inputs include a step size, an option to select that step automatically, and switches for three detection modes: iMAX, HP, and HPX. Step size affects sensitivity, and…

Technical indicatorsTrend followingVolatility