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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

TqSdk

The strategy models a refining spread using crude oil, fuel oil, and a third petroleum product in a 3:2:1 weighting. It calculates the spread as the weighted value of the two product legs minus the weighted crude leg, then compares the current spread with…

FuturesCommoditiesMean reversionArbitrage
MQL5 code base

LeManChanel is described as a technical indicator that estimates the possible boundaries and direction of the next bar. The document identifies the indicator’s original implementation as an MQL4 publication from 2009 and credits LeMan as its author. The…

Technical indicators
SuperMind

This document describes an equity screen combining a 3%–12% turnover-rate range, a candlestick reversal condition, and a circulating-share limit of 5.5 billion shares. It gives a corresponding formula and sample data workflow that calculates a reversal…

EquitiesTechnical indicatorsChina markets
MQL5 code base

The document describes a chart indicator that displays bull power and bear power together in one MetaTrader 5 window. Its stated motivation is that the two measures have different value ranges, which makes a direct overlay in a shared scale difficult to…

Technical indicators
MQL5 code base

This article presents a method for identifying time windows in which an existing trading system performs better. A library analyzes the system’s trading history, removes weaker intervals, and reports results for the remaining periods. In its scalper example,…

BacktestingExecutionRisk management
SuperMind

This post describes a Chinese equity screening rule using three conditions: daily high-low range above 1% of the prior close, a positive but less than 35% return over ten days, and at least one limit-up event during the prior 25 days. The stated rationale is…

EquitiesChina marketsMomentumVolatility
Lumibot

This document presents a QuantStats tear sheet for a strategy labeled “buffett-plain,” compared with SPY over January 4–15, 2026. It lists returns, drawdowns, risk-adjusted statistics, market exposure, daily outcomes, and two drawdown episodes. The reported…

EquitiesBacktestingStatistics
NautilusTrader

This tutorial demonstrates a component-level backtest workflow using NautilusTrader. It loads historical Binance ETH/USDT trade ticks, configures a simulated spot venue with a cash account and maker-taker fees, and aggregates ticks into bars. A strategy…

CryptoTechnical indicatorsTrend followingExecution
MQL5 code base

This brief indicator description introduces a trend tool that displays a colored histogram based on the difference between a Hull Moving Average and an averaging of that moving average. Its stated purpose is to make the trend signal visible in histogram…

Technical indicatorsTrend following
Amberdata research

This report compares hourly Bitcoin returns, volatility, and trading volume across Binance, Bybit, Coinbase, HTX, Kraken, and OKX. It groups activity by the trading hours of several regions, using standard deviation of hourly returns as a volatility proxy…

CryptoVolatilityStatisticsMarket microstructure
vn.py community

The post addresses missing final one-minute bars when a closing or session-boundary tick is not delivered. Its proposed fix adds logic to a bar generator’s tick-update handler: near selected minute boundaries, it checks for a tick arriving in the final…

FuturesMarket microstructureExecution
SuperMind

This Chinese-language post proposes a stock screen combining three conditions: daily amplitude above a threshold, today’s price relative to moving averages in an upward configuration, and a prior-session signal described as main-force control. The rationale…

EquitiesChina marketsTechnical indicatorsMomentum
MQL5 code base

The document describes an accumulated version of the Relative Strength Index (RSI). It forms a new oscillator by combining consecutive RSI calculations, then interprets that oscillator with adaptive thresholds such as floating levels or quantile bands. The…

Technical indicatorsMean reversionBacktesting
MQL5 code base

The document describes an indicator that displays the current trend using values from the Skyscraper_Fix indicator on a fixed timeframe. The signal is derived from the color of the original indicator’s middle line. Markers appear on the chart when a bar…

Technical indicatorsTrend following
vn.py community

The discussion raises two practical issues for CTA strategies: protecting source code when running a strategy on another computer or server, and adapting a strategy as a futures market’s active contract changes. Replies point to a strategy-encryption guide…

FuturesExecutionCommodities
vn.py community

The discussion clarifies that maximum drawdown duration measures how long the strategy remains in its largest drawdown. It distinguishes the time span of a decline and recovery from the size of the loss itself, which is what the maximum drawdown percentage…

BacktestingRisk management
SuperMind

This post outlines a rule-based screen for Shanghai-listed shares with codes beginning in 60. It first restricts candidates to stocks with turnover between 3% and 12%, then requires the previous day’s price to exceed its 250-day moving average. The stated…

EquitiesTechnical indicatorsChina marketsBacktesting
BigQuant

This weekly competition report presents diagnostic summaries for the ten highest-ranked submitted factors and tracks a China 1000 index-enhancement portfolio. Factor diagnostics include average exposures to BARRA style factors and sector-level average Rank…

EquitiesFactor investingStatisticsBacktesting
BigQuant

This introductory note describes quantitative investing as turning research, asset selection, timing, and position decisions into explicit rules that can be tested and executed by a computer. It distinguishes cross-sectional stock selection, which compares…

Factor investingBacktestingMomentumMean reversion
Amberdata research

The article argues that a sharp selloff in World Liberty Financial Token (WLFI) preceded a broader cryptocurrency decline and may have offered an early warning of market stress. It highlights a reported surge in WLFI trading volume after tariff news,…

CryptoMarket microstructurePerpetual futuresVolatility
SuperMind

This introductory overview explains quantitative trading as the conversion of market observations and decision rules into mathematical models and computer programs. It outlines a typical process: analyze historical price, volume, and timing data; design a…

StatisticsBacktestingExecutionMean reversion
SuperMind

The document describes a Chinese A-share stock screen focused on the metaverse sector. It selects stocks whose opening price is less than 6% above the prior close, whose price chart resembles a rounded arc, and whose Bollinger Band width is below 0.05. The…

EquitiesChina marketsTechnical indicatorsVolatility
Qlib

This overview introduces reinforcement learning as a way to learn sequential decisions by interacting with an environment and maximizing accumulated reward. It outlines the agent, environment, policy, and reward, and explains how delayed feedback differs…

Machine learningExecutionPortfolio constructionRisk management
MQL5 code base

This indicator description explains how to display JMACandle bars from a higher timeframe on a chart. It draws each candle as a filled rectangle using fill buffers, distinguishing the candle body from its shadows with separate colors. Up and down candle…

Technical indicatorsFutures