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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

Amberdata research

The article describes how crypto derivatives data can help traders assess uncertainty around elections. It focuses on implied volatility as a measure of expected price swings and open interest as an indication of outstanding positions and participation. It…

CryptoOptionsVolatilityDerivatives pricing
MQL5 code base

This document introduces ATRSmoothed, an Average True Range indicator that applies an additional averaging method to the resulting ATR curve. The added smoothing is intended to make the volatility series less jagged while retaining its basis in true range, a…

Technical indicatorsVolatility
SuperMind

This stock screen selects shares with a daily high-to-low range above one percent, excludes Beijing-listed A shares, and rejects stocks that reached the upper price limit on the previous day. The document presents short-term volatility as a way to find…

EquitiesChina marketsVolatilityTechnical indicators
SuperMind

This Chinese stock-selection note describes a daily screen that looks for shares with an amplitude above 1, a largest daily decline between 4% and 5%, and a close below the Bollinger upper band but above its middle band. It frames amplitude and the decline…

EquitiesMean reversionVolatilityTechnical indicators
Amberdata research

The article argues that liquidity alone offers an incomplete view of volatile crypto markets. Traders and institutions also need context on how activity connects across blockchains, DeFi protocols, centralized exchanges, and stablecoin flows. Stablecoin…

CryptoOn-chain dataDeFiMarket microstructure
ProRealCode

This indicator adapts the Sharpe ratio as a proposed input to a future trading strategy. It calculates log returns over a selected lookback, sums those returns, annualizes return volatility using a trading-day factor, and then divides the return measure…

Technical indicatorsVolatilityRisk managementBacktesting
SuperMind

The document outlines a Chinese A-share screening idea: select companies with a daily high-low range of at least 1%, market capitalization below 10 billion yuan, and positive net profit, then rank them by stock popularity. It presents the range as a way to…

EquitiesChina marketsVolatilityTechnical indicators
MQL5 code base

The document introduces a chart indicator that plots a step channel using volatility measured by smoothed standard deviation. This links the channel's construction to the variability of the price series, rather than describing fixed channel boundaries. The…

VolatilityTechnical indicatorsStatistics
Amberdata research

This market recap describes how a sharp Bitcoin and Ether sell-off affected realized and implied volatility, term structure, option skew, trading flows, and dealer gamma. Short-dated put demand pushed weekly skew into put premium, while longer-dated skew…

CryptoOptionsVolatilityDerivatives pricing
SuperMind

This stock-screening rule combines three conditions: a stated amplitude threshold, MACD above its zero line, and at least one daily gain of 10% or more within the most recent 25 trading days. The accompanying rationale treats amplitude as a sign of…

China marketsEquitiesTechnical indicatorsMomentum
SuperMind

This Chinese-language post describes an equity screen that selects stocks with an intraday range above 1, turnover between 2% and 9%, and a positive return, operationalized in the indicator example as a close above the open. The stated rationale is to…

EquitiesChina marketsVolatilityMomentum
SuperMind

This post outlines a short-term Chinese equity screen for stocks with an intraday range above 1, a day's maximum decline between 4% and 5%, and exclusion of the STAR Market. Its rationale is that a sharp move may create a rebound opportunity, while excluding…

EquitiesChina marketsVolatilityMean reversion
Amberdata research

The document compares free and paid crypto options scanners for professional trading teams. It explains that scanners consolidate activity across exchanges and that richer tools can report net volume and positioning, delta-based butterfly measures, block and…

CryptoOptionsVolatilitySentiment
MQL5 code base

This indicator scans chart candles and highlights those whose size exceeds a user-defined threshold measured in points. It can mark only the current candle or display qualifying candles across the chart. An optional alert notifies the user when the current…

Technical indicatorsVolatility
SuperMind

This note describes a China A-share screen that places a stock in a candidate pool when its daily price range exceeds a threshold, it has recorded at least one limit-up day in the prior 25 sessions, and its stated scale measure is above 200 million. The…

EquitiesChina marketsVolatilityBreakout
MQL5 code base

The Volume-Weighted Price Displacement Oscillator measures how far the current close is from a rolling volume-weighted average price, then divides that difference by rolling price volatility. This produces a z-score-like reading centered on the VWAP anchor:…

Technical indicatorsMean reversionMomentumVolatility
BigQuant

This research summary describes a model for estimating the probability that large-cap stocks will outperform small caps over the coming month. It uses changes in short-term interest rates and broad-market volatility as leading inputs, with the aim of…

EquitiesChina marketsFactor investingStatistics
MQL5 code base

This note presents a Chinese stock-selection screen using price amplitude, the presence of an outstanding convertible bond name, and positive afternoon large-order net inflow. Its rationale treats amplitude as a measure of price movement, bond issuance as a…

EquitiesChina marketsVolatilityMarket microstructure
ProRealCode

The document explains an Elder Force Index oscillator that combines price change and volume, then smooths the result with exponential moving averages to produce an EFI line and a signal line. It describes fixed-length and adaptive calculation modes. In…

Technical indicatorsVolatilityMomentum
Amberdata research

This market commentary argues that implied volatility in crypto options appears low relative to an uncertain macroeconomic backdrop. It points to volatility measures and charts for Bitcoin, Ether, Solana, bonds, equities, and precious metals, describing a…

CryptoOptionsVolatilityDerivatives pricing
Stratmill research code

This data-preparation module builds time-series inputs for a deep-learning momentum model. It reads close prices, clips extreme values using an exponentially weighted mean and standard deviation, then derives daily returns and volatility. The target is a…

Machine learningMomentumVolatilityTechnical indicators
SuperMind

This stock screen combines four filters: daily high-low amplitude above 1, prior-day turnover between 3% and 28%, a robotics concept classification, and circulating market capitalization below 10 billion yuan. The document gives example formulas and…

EquitiesChina marketsVolatilityTechnical indicators
SuperMind

The screen selects stocks with codes beginning with 60, a daily high-to-low range exceeding one percent of the opening price, and a current low below the prior day’s low. The article describes this as a short-term selection rule and provides corresponding…

EquitiesChina marketsVolatilityTechnical indicators