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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

79,386 documents

vn.py community

This short forum exchange addresses how to detect an invalid order price before submitting an order through VeighNa. The response says the framework does not generally filter prices in advance, although its graphical interface prevents users from entering…

ExecutionFutures
Hummingbot docs

This recap describes Hummingbot Miner’s first year, during which token issuers used rewards to attract decentralized market makers. It reports campaign participation, reward payouts, filled trading volume, and activity across Binance and a new KuCoin launch.…

CryptoMarket makingMarket microstructureExecution
SuperMind

The proposed screen selects main-board stocks with circulating market value between 5 billion and 10 billion yuan, turnover between 3% and 12%, and a stated daily maximum decline between 4% and 5%. The article presents the filters as a way to find stocks…

China marketsEquitiesTechnical indicatorsRisk management
MQL5 code base

This Expert Advisor trades when the ColorZeroLagTriX indicator cloud changes color. It forms a signal at bar close when the oscillator crosses its signal line, making the method dependent on a confirmed closing-bar crossover rather than an intrabar move. The…

ForexTechnical indicatorsBacktesting
MQL5 code base

The indicator compares three moving averages whose configured periods must increase from the first average to the second and then the third. It colors the display green when all three averages are ordered from highest to lowest, and red when they are ordered…

Technical indicatorsTrend following
SuperMind

This stock-selection post describes a screen using three short-term conditions: a positive ten-day return below 35%, daily amplitude above 1%, and a stated concentration measure below 20%. It frames these filters as a way to identify stocks with recent gains…

China marketsEquitiesTechnical indicatorsRisk management
SuperMind

This community post proposes a Chinese stock screen within the metaverse industry. It filters for prior-session actual turnover between 3% and 28%, an opening-auction price move ranked among the strongest in the market, and combined net buying by very large…

China marketsEquitiesMarket microstructureExecution
BigQuant

This weekly Chinese equity research note reviews long-short screens built from high-frequency and technical factors. The listed signals include return skewness, downside volatility share, opening-period buying interest and large-order flows, reversal,…

China marketsEquitiesHigh-frequency tradingFactor investing
MQL5 code base

The Aroon Up and Down indicator tracks how recently a chart has made local highs and lows, using a configurable lookback period. Its lines can be used to identify when prices rise from a recent low or decline from a recent high, with line crossings presented…

ForexTechnical indicators
BigQuant

This article reviews global equity factor performance in the third quarter of 2021 and compares defensive factor positioning. It reports that momentum and low residual volatility led the pure factor results, while liquidity lagged. Regional index outcomes…

EquitiesFactor investingMomentumVolatility
SuperMind

This article reviews global equity factor performance in the third quarter of 2021 and compares defensive factor positioning. It reports that momentum and low residual volatility led the pure factor results, while liquidity lagged. Regional index outcomes…

EquitiesFactor investingMomentumVolatility
SuperMind

This Chinese-language article describes an equity screen for Shenzhen main-board stocks associated with the metaverse theme. It selects stocks with a positive return, positive price-to-earnings and price-to-book ratios, and upper bounds on both valuation…

EquitiesChina marketsFactor investing
MQL5 code base

This chart indicator adapts the stochastic volatility concept to highlight periods when volatility is unusually low. It marks candidate bars with red lines in a separate indicator window and red candles on the price chart. The author suggests these periods…

VolatilityTechnical indicators
SuperMind

This document outlines a stock-selection screen that ranks securities by capital strength and requires weekly MACD to be above zero, alongside a year-based filter referring to 2021. It explains capital strength through trading volume and value, and describes…

China marketsEquitiesMomentumTechnical indicators
SuperMind

This document presents a Chinese equity screen for Shenzhen Main Board stocks, combining turnover from 3% to 12%, circulating market capitalization from 5 billion to 10 billion, price-to-earnings ratio from 0 to 29.01, and price-to-book ratio from 0 to 3.11.…

China marketsEquitiesFactor investingStatistics
SuperMind

This document proposes screening stocks whose codes begin with 60, keeping those with turnover between 3% and 12%, then ranking them by a measure described as capital strength. The commentary presents the ranking as a way to identify actively financed market…

China marketsEquitiesExecution
SuperMind

This document describes a Chinese stock screen using amplitude above 1, a stated K-line value below 20, and prior-day actual turnover between 3% and 28%. It presents these conditions as a way to find stocks with notable price movement and moderate trading…

China marketsEquitiesTechnical indicatorsMachine learning
ProRealCode

This indicator combines smoothed Heikin-Ashi candles with a stochastic oscillator and a moving-average condition to mark possible entries and exits. The described logic treats rising Heikin-Ashi candles as bullish and falling candles as bearish, while candle…

Technical indicatorsMomentumOptionsTrend following
SuperMind

The post proposes screening Chinese equities for elevated daily range, at least one daily gain of 10% or more during the past 25 trading days, and a pre-open price change below 6%. It then extends the screen with company and industry comparisons, including…

EquitiesChina marketsMomentumVolatility
SuperMind

This Chinese A-share screening idea combines three technical conditions: at least five moving averages are described as converging, the KDJ indicator has just formed a bullish crossover, and the 20-day moving average is above the 120-day average. The post…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This stock screen combines a metaverse-concept filter with a simple price condition: the current close must be above the previous session’s low. It also excludes Beijing-listed A shares. The document gives corresponding indicator logic and a Python example,…

EquitiesChina marketsTechnical indicatorsPosition sizing
SuperMind

This Chinese-language post proposes screening stocks using turnover, displayed best-level bid and ask volume, and large-order net inflow. Its final selection rule requires turnover between 3% and 15%, bid volume greater than ask volume, and large-order net…

EquitiesMarket microstructureTechnical indicatorsStatistics
MQL5 code base

The Trend Risk indicator estimates a smoothed price and a smoothed high-low range, then uses a deviation multiplier to form upper and lower channel boundaries. A close above the upper boundary or below the lower boundary places the boundary value in a signal…

Technical indicatorsTrend followingBreakoutRisk management