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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
TqSdk
86 documents
Quantpedia
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
Binance API docs
45 documents
Quantopian lectures
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

Hummingbot docs

This overview explains controllers as reusable, configurable components in Hummingbot Strategy V2. A controller receives market data such as order books, trades, and candles, then emits actions that direct a parent script to create or stop executors.…

Market makingArbitrageGrid tradingExecution
SuperMind

This note proposes a short-term A-share screen requiring price amplitude above 1%, a daily decline between 4% and 5%, and a sequence of higher recent lows. The rising-low condition is intended to identify stocks whose short-term price floor is moving upward…

EquitiesChina marketsTechnical indicatorsMean reversion
SuperMind

This note outlines an A-share stock screen based on daily price amplitude above 1%, a share price of 18.5 yuan, and a rising K value from the KDJ stochastic indicator. It presents the amplitude threshold as a way to find stocks with notable price movement…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This note describes a daily A-share stock screen combining three filters: MACD above its zero line, a share price below 12 yuan, and previous-day trading value above 60 million yuan. It says the screen is run before the market opens and presents the turnover…

EquitiesChina marketsTechnical indicatorsMomentum
MQL5 code base

This expert advisor combines a moving average with MACD to open trades and add to losing positions. It checks for signals or additions when a new bar appears. A sample buy setup requires MACD below zero, its main line above its signal line, and price above…

ForexTechnical indicatorsPosition sizingRisk management
BigQuant

This Chinese-language event listing outlines a dynamic trading approach for timing exchange-traded funds. It identifies three components: selecting a pool of highly liquid ETFs, ranking candidates with multiple momentum dimensions, and adjusting the approach…

EquitiesMomentumTechnical indicatorsExecution
Kraken Learn

Impermanent loss is the reduction in a liquidity provider’s pool value relative to simply holding the deposited assets. The document explains the setting: an automated market maker holds two assets in a smart-contract pool, and traders’ swaps change their…

CryptoDeFiMarket microstructure
BigQuant

This Chinese equity market report summarizes sector performance, index and industry valuations, market breadth, fund positioning, and an intermediate-term trend model. It reports that building materials, agriculture and forestry, utilities, light…

EquitiesChina marketsMomentumTechnical indicators
Qlib

This configuration describes a Qlib experiment using a graph attention model, GATs, with an LSTM base model to predict near-term returns for CSI 300 constituents. It sets Chinese market data, defines a close-to-close forward return label, normalizes features…

EquitiesChina marketsMachine learningBacktesting
SuperMind

This post presents a Chinese equity screen based on price amplitude above 1%, excluding Beijing-listed shares, and auction turnover above 0.26%. Its proposed refinement also filters for prices within 2% of a 60-day moving average and adds positive valuation…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This post outlines a Chinese stock screen using daily amplitude, a reversal-style candle condition, and a fixed closing price of 18.5 yuan. It provides both an indicator formula and Python example, with the latter also invoking candlestick pattern functions.…

EquitiesChina marketsTechnical indicatorsMean reversion
SuperMind

This post describes a Chinese equity screen combining daily price movement, trading activity, and valuation. It selects stocks with amplitude above 1%, current volume above 10,000 lots, a higher open, and Shenzhen main-board listing, while requiring…

EquitiesChina marketsVolatilityFactor investing
SuperMind

The document proposes screening equities for a daily high-to-low range above one percent, a reversal or engulfing-style pattern, and then sorting selected names by a popularity measure. It frames range as a way to find volatile stocks, the pattern as a…

EquitiesTechnical indicatorsVolatilitySentiment
MQL5 code base

This brief note describes a version of a modified optimum elliptic filter indicator that adds a user-selectable chart timeframe. The example default is a four-hour period, while the input is intended to let a trader choose another timeframe for the…

Technical indicators
SuperMind

The document describes a stock screen combining membership in the metaverse sector, a minimum circulating market capitalization, and weekly MACD above the zero line. Its stated rationale is to find larger companies in that sector whose trend indicator is…

EquitiesTechnical indicatorsTrend followingChina markets
MQL5 code base

The indicator measures each candle’s body relative to its full range, using the ratio to classify candles as strong, weak, or neutral. It presents the current candle’s body and wick proportions alongside a lookback summary of average body ratio and…

Technical indicatorsMomentumStatistics
SuperMind

This equity screen looks for stocks with turnover in a specified range, a rising K value from the KDJ indicator, and greater displayed volume at the best bid than at the best ask. The article explains these as filters for trading activity, short-term…

EquitiesTechnical indicatorsMarket microstructure
SuperMind

This stock-screening idea combines daily range, a rising-bottom condition, and three consecutive declining closes. The article also gives a more specific indicator version using trend and Bollinger Band filters, then proposes selling when price or a candle…

EquitiesTechnical indicatorsMean reversionRisk management
vn.py community

This forum question examines why changing the initialization length of a trading system’s ArrayManager can materially alter a backtest. The strategy uses RSI generated through TA-Lib, and the author suspects that the indicator’s path dependence makes its…

BacktestingTechnical indicatorsRisk managementStatistics
SuperMind

This post describes an A-share stock screen combining a daily price-amplitude threshold, a nonempty convertible-bond name field, and a company classification filter that can be configured for criteria such as industry or state ownership. It proposes ranking…

EquitiesChina marketsFactor investingTechnical indicators
BigQuant

This short Chinese-language note defines quantitative investing as using programs to invest based on collecting and analyzing substantial market data. It presents automation as a way to respond to market changes more quickly, follow a consistent process, and…

Machine learningStatisticsBacktestingRisk management
Amberdata research

The recap compares Bitcoin and Ethereum options markets through realized and implied volatility, term structures, skew, and relative gamma pricing. It describes BTC shifting into contango as front-end implied volatility falls more sharply than longer-dated…

CryptoOptionsVolatilityDerivatives pricing
SuperMind

This stock-selection proposal combines three filters: RSI below 65, year-over-year growth in net profit attributable to parent-company shareholders above 20% and no greater than 100%, and exclusion of stocks that hit the daily limit-up on the prior day. It…

EquitiesChina marketsTechnical indicatorsMomentum
MQL5 code base

This document describes a utility script for viewing open forex positions’ profit or loss in pips. It says the tool does not place or close trades, and reports four outputs: aggregate pip P&L across positions, the pip result for each position, the sum of…

ForexRisk management