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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

ProRealCode

This indicator constructs Heikin-Ashi values from open, high, low, and close prices, then smooths each component using a configurable average type and period. It draws candles using the smoothed open and close, while the channel boundaries come from the…

Technical indicatorsTrend followingVolatility
SuperMind

The document proposes selecting stocks with amplitude above 1, a share price of 18.5 yuan, and company size above 200 million. It frames the screen as a way to find active stocks with meaningful scale, then acknowledges that size alone cannot assess…

EquitiesVolatilityTechnical indicatorsRisk management
SuperMind

The article proposes a short-term equity screen based on amplitude above 1, three consecutive prior daily gains that are not limit-up moves, and large-order net inflow during the afternoon. It interprets amplitude as a sign of an active security and…

EquitiesMomentumVolatilityMarket microstructure
SuperMind

The document describes an equity screen requiring price amplitude above 1, return on equity above 15% for five consecutive years, and more than three years since listing. It presents these conditions as a way to combine active trading with a record of…

EquitiesFactor investingVolatilityRisk management
SuperMind

The article describes a short-term A-share screening rule combining three conditions: prior-session price amplitude above 1%, circulating shares no greater than 5.5 billion, and a stock code beginning with 60. Its sample implementation intersects these…

EquitiesChina marketsVolatilityTechnical indicators
SuperMind

This A-share stock screen combines a range expansion condition, a Bollinger Band location filter, and a historical dividend ratio threshold. It selects stocks whose daily high-low range exceeds its 20-day average, whose close lies between the middle and…

EquitiesChina marketsTechnical indicatorsVolatility
ProRealCode

The document describes an RSI variant that places adjustable bands around the conventional center level. It calculates the RSI from closing prices, then sets an upper and lower band by adding or subtracting a multiple of the standard deviation of the RSI…

Technical indicatorsVolatilityMean reversion
SuperMind

This short-term stock screen combines three signals: a high-low range greater than one, a shortening negative MACD histogram on a 15-minute chart, and at least one limit-up move during the past month. The document interprets the range as a sign of…

EquitiesChina marketsMomentumVolatility
SuperMind

This note proposes a Chinese equity screen for stocks with amplitude above 1, rising lows, membership in the robotics concept group, and circulating market capitalization below 10 billion yuan. It combines a price-pattern condition with a sector theme and a…

EquitiesChina marketsTechnical indicatorsVolatility
SuperMind

This note describes a Chinese equity screen combining three conditions: price amplitude above 1, circulating market capitalization above 10 billion yuan, and at least one limit-up event in the prior 25 days. It frames the screen as a way to find larger,…

EquitiesChina marketsVolatilityBreakout
SuperMind

This stock screen combines three daily price conditions: amplitude greater than 1%, an opening price within 5% of the 10-day moving average, and a current low below the previous day's low. The document includes formula and Python examples for calculating…

EquitiesTechnical indicatorsVolatilityChina markets
MQL5 code base

The document describes a chart indicator that automatically positions two standard deviation channels. It offers a visual channel-based view of price behavior, but does not explain the calculation method, how the channels are anchored, or how a trader might…

Technical indicatorsVolatility
ProRealCode

This indicator adapts the idea of nested Hurst channels by plotting a shorter-cycle channel inside a medium-cycle channel. Both use smoothed price averages as centers and average true range offsets to set their upper and lower bounds. The description frames…

Technical indicatorsVolatilityMean reversion
MQL5 code base

This note describes an intraday extension of the Keltner channel. The channel combines a simple moving average with average true range multiplied by a user-selected factor; this variant uses intraday ATR. It further modifies the basic intraday version by…

Technical indicatorsVolatility
MQL5 code base

This document describes a simple indicator that expresses an asset’s recent high-low price range in points. For each averaging period, it sums the maximum prices and subtracts the sum of the minimum prices; the result is averaged using a selectable…

VolatilityTechnical indicatorsStatistics
SuperMind

This recap of an Amberdata and Blockworks webinar discusses institutional participation in Bitcoin markets, with attention to derivatives, market structure, and the possible effects of a spot exchange-traded fund. It frames Bitcoin's 2023 performance and…

CryptoOptionsFuturesVolatility
MQL5 code base

This indicator description presents an adaptation of a double-smoothed Wilder exponential moving average. It adds a volatility-ratio mode to adjust the average and a correction method attributed in the source to Alexander Uhl. The suggested use is similar to…

Technical indicatorsVolatilityTrend following
SuperMind

This Chinese-language post describes a stock screen combining three conditions: daily amplitude above 1%, a weekly five-period moving average crossing above the ten-period average, and a concentration measure below 20%. The stated rationale is to find stocks…

EquitiesChina marketsMomentumTechnical indicators
MQL5 code base

The HWC indicator is described as a channel around a Holt-Winters moving average. Its upper and lower boundaries are formed by adding and subtracting a scaled estimate of dispersion from the central average. The moving average uses parameters for smoothing…

Technical indicatorsVolatilityTrend following
ProRealCode

The document explains a trend indicator attributed to Andrew Abraham’s 1998 article. It defines trend direction using a trailing level built from a weighted average of true range. True range is the largest of the current high-low range and the gaps from the…

Trend followingVolatilityTechnical indicatorsRisk management
Amberdata research

This article outlines factors to assess before depositing token pairs into a decentralized exchange liquidity pool. Liquidity providers receive a share of swap fees, generally represented by redeemable pool tokens, and some pools may also distribute…

DeFiRisk managementVolatilityBacktesting
Stratmill research code

This code excerpt implements three filters intended to support spread trading and risk adjustment. The correlation filter calculates rolling correlation between the first two series, rescales it to a zero-to-one range, and uses changes in that measure to…

Pairs tradingVolatilityRisk managementBacktesting
SuperMind

This proposed stock screen combines amplitude above 1, institutional participation, and year-over-year growth in net profit attributable to parent-company shareholders above 20% and at most 100%. The final criteria specify institutional participation above…

EquitiesChina marketsVolatilityMomentum