Skip to content

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

MQL5 code base

The document introduces PAIN, a price-action oscillator that displays an OHL3C candlestick price ratio over a chosen period. Its two controls are the calculation period and the moving-average method. The description identifies the moving average used in the…

Technical indicatorsStatistics
MQL5 code base

The Expert Advisor described here trades changes in the direction of the HullTrendOSMA histogram. It generates a signal when a bar closes and the indicator’s direction has changed, making the strategy a reversal-signal approach. The document also states that…

ForexTechnical indicatorsTrend followingBacktesting
SuperMind

This stock screen combines technical filters with valuation limits for Shenzhen main-board listings. It selects shares with RSI below 65, price-to-earnings ratios between zero and 29.01, price-to-book ratios between zero and 3.11, and a 30-day moving average…

EquitiesChina marketsTechnical indicatorsMomentum
MQL5 code base

The document explains the KDJ indicator’s calculation from a recent price range. It finds the highest high and lowest low over the selected period, then expresses the current close’s distance above the low as a percentage of that range. This raw stochastic…

Technical indicatorsMomentum
MQL5 code base

This document describes a chart indicator for MetaTrader that extends the standard crosshair with two readings: the percentage difference between selected price points and the elapsed time between them. Time is displayed in familiar units such as hours,…

Technical indicatorsExecution
SuperMind

This stock-selection method requires a minimum daily price range, prior-day trading turnover above a stated threshold, and positive large-order net flow for at least three consecutive days. The article frames range as a measure of movement, turnover as a…

EquitiesMarket microstructureVolatilityRisk management
BigQuant

This short platform discussion presents a manual construction of the KDJ oscillator alongside built-in KDJ functions. It first derives the raw stochastic value from the close’s position within the rolling ten-period high-low range. It then applies smoothing…

Technical indicatorsEquitiesStatistics
SuperMind

This document describes a stock screen combining a positive MACD reading, a same-day upward spread between moving averages, and an intraday price range above a threshold. Its example calculates exponential averages to form MACD, compares five- and ten-day…

EquitiesTechnical indicatorsMomentumVolatility
SuperMind

The document proposes a Chinese stock screen combining four criteria: daily high-low amplitude above 1%, prior-day trading volume above 60 million, market capitalization below 10 billion, and positive net profits over the previous three years. It presents…

China marketsEquitiesTechnical indicatorsFactor investing
MQL5 code base

The document describes an indicator that reports the minimum and maximum amplitude over a chosen period. It presents the measure as a way to observe volatility and the size of past price swings, and as a possible substitute for ATR. A relative amplitude…

VolatilityTechnical indicators
SuperMind

This Chinese equity screen looks for shares priced below 12 yuan whose MACD is above zero while its value two trading sessions earlier was below zero. The stated intent is to find a recent move from negative to positive MACD territory while imposing a low…

EquitiesChina marketsMomentumTechnical indicators
pyfolio

The document explains a MetaTrader 5 indicator that marks hammer, inverted hammer, and color variants on price charts. It identifies patterns by measuring candle bodies and wick proportions, then places a colored arrow near the candle’s high or low to flag a…

Technical indicatorsVolatility
MQL5 code base

This tutorial presents pyfolio as a Python toolkit for evaluating trading strategies through return, position, transaction, stress-period, and Bayesian analyses. Its central output is a set of tear sheets combining tables and plots, with lower-level plotting…

Portfolio constructionRisk managementBacktestingStatistics
SuperMind

This stock screen selects shares with a daily price change above 1%, more than one year since listing, and a positive price-to-earnings ratio. Its rationale is that larger daily moves may indicate active trading, while a longer listing history may exclude…

EquitiesChina marketsTechnical indicators
SuperMind

This post proposes screening main-board stocks using a combination of price range, a streak of consecutive limit-up sessions on the prior day, and a current-day gain above a stated threshold. It presents the conditions as a way to focus on volatile stocks…

China marketsEquitiesMomentumTechnical indicators
MQL5 code base

This brief description explains an indicator-based breakout system built around a Mikahekin channel. The visual signal changes when price moves outside a gray channel, with blue indicating an upward trend and yellow indicating a downward trend. Candle colors…

BreakoutTechnical indicatorsTrend following
SuperMind

This Chinese-language post describes an equity screening idea that combines a named “morning star” signal for Kute Intelligent with a condition requiring the 20-day moving average to exceed the 120-day moving average. It frames both as technical-analysis…

China marketsEquitiesTechnical indicatorsTrend following
backtesting.py

This tutorial shows how to test a long-only strategy that combines daily and weekly relative strength index readings with a stack of moving averages. It uses daily price bars as the base data, resamples them to weekly intervals to calculate the…

EquitiesTechnical indicatorsTrend followingBacktesting
SuperMind

This stock-selection screen combines a minimum daily amplitude threshold with a minimum circulating market capitalization, then ranks qualifying shares by a popularity measure. The stated rationale is to focus on stocks that show price movement, have a…

China marketsEquitiesTechnical indicatorsSentiment
MQL5 code base

This document outlines a basic automated scalp approach that uses the Zigzag indicator to identify recent price highs and lows. The system treats those swing points as potential support or resistance, draws a trend line based on the market’s reaction around…

Technical indicatorsTrend followingExecutionRisk management
BigQuant

This overview surveys practical considerations for AI and quantitative trading, from data quality and model choice to backtesting, risk controls, and portfolio allocation. It highlights that historical results can mislead when models are overfit or…

Machine learningStatisticsRisk managementBacktesting
SuperMind

This proposed A-share screen looks for companies with turnover between 3% and 12%, market capitalization below 10 billion yuan, and no reported losses, then selects stocks whose prior-day 9:15 indicative matching price was at the lower price limit. The…

EquitiesChina marketsEvent-drivenRisk management
SuperMind

This stock-selection idea combines an amplitude threshold, weekly MACD conditions, and a three-candle pattern described as the Kute Smart morning star. The proposed screen seeks Chinese equities whose weekly MACD is above zero and whose recent candles match…

EquitiesChina marketsTechnical indicatorsMomentum