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

22,592 documents

SuperMind

The document proposes a Chinese equity screen combining price amplitude above one, a shrinking negative MACD histogram on 15-minute bars, and a nonempty name for an outstanding convertible bond. It interprets the amplitude as a volatility filter and the…

China marketsEquitiesTechnical indicatorsVolatility
MQL5 code base

The document introduces the Stochastic MACD oscillator, described in an article by Vitali Apirine in a 2019 issue of Technical Analysis of Stocks & Commodities. The indicator combines the stochastic oscillator with MACD and is presented as a momentum…

Technical indicatorsMomentumEquities
SuperMind

The document presents a Chinese stock screen using turnover, circulating share capital, and a historical dividend payout ratio. Its initial criteria specify turnover between 3% and 12%, circulating shares no greater than 5.5 billion, and a 2019 payout ratio…

EquitiesChina marketsFactor investingRisk management
SuperMind

This post describes a daily stock screen using three conditions: MACD above zero, share price below 12 yuan, and a bounded price change. The explanatory text gives the change range as -5% to 2.6%, although the headline abbreviates the condition as a gain…

China marketsEquitiesTechnical indicatorsMomentum
SuperMind

This Chinese-language post outlines a daily A-share screening rule focused on the metaverse sector. It selects stocks whose indicated gain by 9:25 is below 6%, ranks eligible names by the current day's auction amount, and keeps the top five. The post…

China marketsEquitiesMomentumEvent-driven
SuperMind

This 2020 investment analysis argues that Hong Kong equities looked attractive after the Hang Seng Index’s price-to-book ratio fell below one during the pandemic selloff. It compares prior episodes of the index falling below or nearing book value and reports…

EquitiesChina marketsFactor investingPortfolio construction
BigQuant

The discussion explains that a supervised model learns from factors paired with labels, where a label defines the target. For stock selection, the target might be future returns over a chosen horizon. The model and label together determine what predictions…

Machine learningFactor investingEquitiesStatistics
SuperMind

This post proposes an A-share screen using RSI below 65, three consecutive down sessions, and a prior-day “main force control” condition. Its examples approximate the last condition with volume above a moving average and a rolling count of such events. The…

EquitiesChina marketsTechnical indicators
SuperMind

This post describes an A-share stock screen combining turnover between 3% and 12%, a K value below 20, and a current close above the previous session’s low. It presents the conditions as a way to identify stocks with potential for short-term gains, then…

EquitiesChina marketsTechnical indicatorsBacktesting
SuperMind

This document outlines a Chinese A-share stock screen for main-board listings. It keeps stocks whose turnover is between 3% and 12%, whose circulating market value is between 5 billion and 10 billion yuan, and whose weekly MACD is above zero. The conditions…

China marketsEquitiesTechnical indicators
vn.py community

The document describes a Chinese A-share screening rule for main-board stocks. It selects shares with turnover between 3% and 12%, a circulating market value between 5 billion and 10 billion yuan, and weekly MACD above zero. It explains that the screen…

China marketsEquitiesTechnical indicators
SuperMind

The document describes a Chinese equity screening idea that combines a large daily range, a prior-day opening auction price at the limit-down level, and a rising-bottom condition. Its final version adds a price-to-earnings threshold and volume above the…

China marketsEquitiesTechnical indicatorsMomentum
BigQuant

This study examines how exposure to international trade relates to US stock returns. It uses industry transportation costs as a measure of globalization exposure, sorting stocks into portfolios and comparing their excess returns. The reported evidence…

EquitiesFactor investingUS marketsPortfolio construction
SuperMind

This proposed equity screen selects stocks with turnover between 3% and 12%, a listing year of 2021, and a dividend ratio above 25% for 2019. The article presents these as activity, company-age, and historical payout filters. It cautions that relying on a…

EquitiesFactor investingStatisticsBacktesting
SuperMind

This stock screening proposal ranks candidates by relative volume, which the source describes as a proxy for capital activity, and filters for turnover above 8% on the prior day. It also keeps stocks whose price change at 9:25 is below 6%, aiming to avoid…

EquitiesMomentumTechnical indicatorsBacktesting
BigQuant

The document answers whether a factor can be neutralized for both market capitalization and industry exposure. It recommends including market capitalization as a continuous explanatory variable and industry membership as dummy variables in the same…

Factor investingStatisticsEquities
BigQuant

This event study examines how Chinese A-share prices behave around formal earnings reports, especially when companies previously issued earnings forecasts. It compares reported results with forecast ranges and groups companies by forecast category or by the…

EquitiesEvent-drivenMomentumStatistics
SuperMind

This article proposes a Chinese equity screen combining price movement and fundamental filters. Its initial conditions look for stocks with intraday amplitude above one, a positive weekly MACD bar, and a daily low roughly 4% to 5% below the prior low. The…

EquitiesMomentumMean reversionTechnical indicators
SuperMind

This technical screen seeks stocks with a 14-period RSI below 65, three consecutive down sessions, and a daily high-low range above 1% of the previous close. The accompanying formula and sample code also add conditions for a price decline greater than 2% and…

EquitiesChina marketsTechnical indicatorsMean reversion
SuperMind

This Chinese A-share screen combines membership in a metaverse sector with turnover above 8% on the prior day and a three-session limit-up pattern. The article presents the sequence as a way to focus on a hot theme and stocks attracting unusually strong…

EquitiesChina marketsMomentumSentiment
SuperMind

The screen selects Chinese shares with turnover between 3% and 12%, then requires the product of the daily price change and the net amount attributed to very large orders to be positive. It ranks qualifying stocks by opening auction value and keeps the top…

EquitiesChina marketsMarket microstructureExecution
BigQuant

This report applies behavioral finance to equity factor research, using the disposition effect and prospect theory to explain how investors' risk preferences may differ depending on whether they hold gains or losses. It constructs a capital gains overhang…

EquitiesChina marketsFactor investingBacktesting
SuperMind

This Chinese equity screen combines a price-amplitude condition, the presence of an outstanding convertible bond, and a positive arc-shaped technical indicator. The accompanying formula also applies a market-capitalization threshold and filters out certain…

EquitiesChina marketsTechnical indicatorsVolatility