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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

This research article examines whether lending activity in USDC, USDT, and DAI helps forecast Ethereum volatility. It describes time-series autocorrelation and partial autocorrelation analysis, then uses Granger causality tests to assess whether past…

CryptoDeFiVolatilityStatistics
BigQuant

The document explains abnormal idiosyncratic volatility (AIV), a price based measure of information risk around earnings announcements. It compares each stock’s residual volatility during the five trading days before earnings announcements with its residual…

EquitiesVolatilityFactor investingEvent-driven
SuperMind

This stock-selection idea combines three daily conditions: amplitude above one, a controlling-shareholder control measure above 21 in absolute value, and MACD above its zero line. The post frames amplitude as a volatility filter, the control measure as an…

EquitiesTechnical indicatorsMomentumVolatility
ProRealCode

This indicator classifies each candle by its closing price relative to a 20-period moving average and Bollinger Bands set two standard deviations above and below that average. Closes above the upper band receive one color; closes between the average and…

Technical indicatorsVolatility
SuperMind

This stock screen combines three conditions: amplitude above 1, a circulating share count no greater than 5.5 billion, and a current-day low below the previous day’s low. The post frames the amplitude and float filters as ways to focus on volatile,…

China marketsEquitiesVolatilityMean reversion
SuperMind

The document describes a stock screen combining three conditions: a dividend ratio above 25% for 2019, a 20-day moving average above the 120-day moving average, and daily amplitude above 1%. It interprets the moving-average relationship as an uptrend filter,…

EquitiesChina marketsTechnical indicatorsVolatility
ProRealCode

Voluminator classifies trend by comparing the close with a configurable moving average. When the close is above the average, volume contributes to a bullish series; when it is below, volume contributes to a bearish series. Separate smoothed series are…

Technical indicatorsTrend followingVolatility
MQL5 code base

This document describes a chart indicator that displays signals generated by the Skyscraper_Fix trend indicator using a selected timeframe. It distinguishes continuation from trend-change signals through different arrow shapes and colors, and can produce…

Technical indicatorsTrend followingVolatilityExecution
Amberdata research

This weekly market commentary reviews crypto options conditions around January 29, 2023. It interprets Bitcoin options term structure as having moved into backwardation during a spot rally, suggesting the market priced more near-term movement. It also…

CryptoOptionsVolatilityDerivatives pricing
Amberdata research

The document introduces a chart for examining an options butterfly across constant maturities. It defines the structure as long one call and one put with a short position in two at-the-money options, and says users can select among several delta levels and…

OptionsVolatilityDerivatives pricingCrypto
SuperMind

This A-share screen selects stocks associated with a robotics concept, with daily amplitude above 1%, circulating market value below 10 billion yuan, and prior-day actual turnover between 3% and 28%. The article treats amplitude as a sign of activity, the…

EquitiesChina marketsTechnical indicatorsVolatility
SuperMind

This A-share screening idea combines three conditions: daily amplitude above 1%, a rounded or relatively subdued price pattern, and an auction-period price change between -2% and 5%. The article interprets the amplitude filter as a way to find active stocks,…

EquitiesChina marketsTechnical indicatorsVolatility
MQL5 code base

This short indicator description presents a visual way to show periods when Bollinger Bands narrow or widen. Band narrowing and widening are framed as possible indications of changes in price volatility, and the indicator is intended to make those phases…

Technical indicatorsVolatility
Amberdata research

The document introduces charts for comparing Bitcoin and Ethereum options implied volatility across delta levels. It describes two views: a spread calculated by subtracting Ethereum implied volatility from Bitcoin implied volatility, and a ratio calculated…

CryptoOptionsVolatilityDerivatives pricing
Amberdata research

The article argues that Bitcoin implied volatility should be read alongside broader market measures. It highlights VIX, VVIX, MOVE, the dollar index, gold volatility, and yield curve shape as potential clues to changes in crypto volatility. It attributes…

CryptoVolatilityOptionsMulti-asset
MQL5 code base

The indicator draws high-low boxes for the Asian, London, and New York Forex sessions using one-minute bars. Each box marks the session’s range, with an optional midpoint and label. It also displays average range in pips over a configurable lookback and can…

ForexBreakoutVolatilityTechnical indicators
Amberdata research

The article presents realized volatility (RV) as a measure of observed price movement and implied volatility (IV) as the options market’s forecast. It uses the ratio of 7-day RV to 30-day RV to distinguish short-term expansion from compression, then compares…

CryptoOptionsVolatilityTechnical indicators
ProRealCode

This indicator combines Williams Percent Range with Average True Range to define a directional trend and plot trailing stop lines. Williams Percent Range crossing configurable thresholds switches the trend state. The indicator then places a stop line below…

Technical indicatorsTrend followingVolatilityRisk management
MQL5 code base

The document describes the Chande Kroll Stop, a trend-following indicator that plots separate stop levels for long and short positions. A trader may use the long-position line as a level for closing a purchase if price falls to it, and the short-position…

Technical indicatorsTrend followingVolatilityRisk management
Amberdata research

This market snapshot combines price action with ETF and stablecoin flows, derivatives positioning, funding rates, open interest, orderbook depth, spreads, and volatility. It interprets the period as consolidation: Bitcoin and Ether held up better than…

CryptoPerpetual futuresArbitrageMarket microstructure
MQL5 code base

This indicator adapts the moving averages in a MACD calculation using RSI, while retaining the basic idea of comparing faster and slower averages. It adds floating outer levels to help identify overbought and oversold conditions, addressing a limitation of…

Technical indicatorsMomentumVolatility
vn.py community

This article outlines the engineering challenges of researching and backtesting systematic options strategies. Because listed contracts change over time, a historical test needs an accurate record of which contracts were available on each date. The described…

OptionsBacktestingVolatilityExecution
SuperMind

The document presents a Chinese equity screen combining daily price range, the presence of an outstanding convertible bond, and positive institutional trading activity. It explains the intended roles of these filters: selecting volatile stocks, using…

EquitiesChina marketsVolatilitySentiment
SuperMind

This Chinese stock-selection note describes a three-condition screen: ten-day price gain above zero but below 35, MACD below zero two days earlier, and amplitude above 1. It frames the conditions as combining recent performance, a technical indicator, and…

EquitiesChina marketsTechnical indicatorsMomentum