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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

22,592 documents

SuperMind

This document describes a Chinese equity screening rule that combines price movement, trend, momentum, and trading activity. Its final version selects stocks with amplitude above 1, MACD above zero, RSI(14) above 50, and prior-day auction turnover above…

China marketsEquitiesTechnical indicatorsMomentum
SuperMind

The document presents a stock screen for securities whose codes begin with the specified Shanghai prefix, whose daily trading range exceeds a threshold, and whose moving averages are described as diverging upward. It includes a technical formula and a Python…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

The document describes a Chinese equity selection rule combining turnover, the ratio of market buy volume to market sell volume, and institutional net buying. It filters for turnover between the stated bounds, a buy-to-sell volume ratio above the specified…

EquitiesChina marketsMomentumMarket microstructure
BigQuant

The document explains how a backtest engine turns an investment strategy into simulated trades. It distinguishes strategy logic, such as selecting securities and generating signals, from trade logic, such as deciding position size, rebalance timing, order…

BacktestingExecutionPosition sizingRisk management
SuperMind

The document proposes a stock screen that combines price amplitude above one, a rising sequence of recent lows, and a positive price-to-earnings ratio. It presents these as technical and fundamental filters intended to identify shares with substantial…

EquitiesChina marketsTechnical indicatorsFactor investing
BigQuant

This document introduces the cyclically adjusted price-to-earnings ratio, or CAPE, as a way to compare equity prices with a decade of inflation-adjusted earnings. It summarizes historical analyses of the S&P 500 and Shanghai Composite, reporting that higher…

EquitiesMean reversionStatisticsBacktesting
SuperMind

This short programming example shows how to screen daily stock data with several conditions at once, then select only the desired columns. The example combines a date cutoff, a minimum trading amount, and a maximum closing price using boolean masks joined…

EquitiesChina markets
BigQuant

The document explains the cyclically adjusted price-to-earnings ratio (CAPE), calculated as an inflation-adjusted share price divided by the average inflation-adjusted earnings per share over the prior decade. It compares CAPE with future real returns for…

EquitiesChina marketsUS marketsMean reversion
SuperMind

This stock-selection rule screens companies associated with the metaverse theme, requiring a volume ratio above 1.5 and below 6, alongside circulating market value above 10 billion yuan. The rationale is to combine a thematic industry filter with relatively…

EquitiesChina marketsTechnical indicators
SuperMind

This post describes an equity screen that combines membership in the metaverse concept group with two price conditions: the close must exceed the previous session’s low, and the open must fall within ten percent above or below the ten-day simple moving…

EquitiesTechnical indicatorsChina marketsRisk management
SuperMind

This post describes a China A-share screening idea focused on stocks in the metaverse sector. It adds two filters: a morning price-change condition below six percent and a measure intended to indicate that large participants controlled trading on the prior…

EquitiesTechnical indicatorsMomentumChina markets
SuperMind

This Chinese-language post outlines a stock screen combining three conditions: price amplitude above one, prior-day turnover above 60 million, and MACD above its zero line. It frames amplitude as a measure of price movement, turnover as a gauge of activity,…

EquitiesTechnical indicatorsMomentumChina markets
SuperMind

The article describes a stock screen that excludes Beijing-listed shares, selects stocks with a daily high-low range above one percent, and applies a filter based on the prior day's turnover and the ratio of current opening-auction volume to the previous…

EquitiesChina marketsVolatilityTechnical indicators
SuperMind

This stock selection rule screens companies in the metaverse theme for a closing price above the five-day moving average, trading volume above the stated threshold, and an opening price above the previous close. The article presents these conditions as a way…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

This article proposes screening stocks with turnover between three and twelve percent, displayed best-bid volume greater than best-ask volume, and a prior-day condition described as a 9:15 matched price at the daily limit-down. The first two filters are…

China marketsEquitiesMarket microstructureRisk management
BigQuant

This article describes a stock-selection screen based on three conditions: a daily high-low range above a stated threshold, an opening price near the ten-day moving average, and at least five years since listing. The intended interpretation is that elevated…

China marketsEquitiesTechnical indicatorsVolatility
SuperMind

This article outlines a Chinese equity screen for stocks in the metaverse sector. It combines bullish technical signals, including MACD and short moving-average crossovers, with a filter intended to exclude stocks that hit the daily price limit on the…

China marketsEquitiesTechnical indicatorsMomentum
SuperMind

The proposed stock screen filters for amplitude above 1 and a closing price below 20, then ranks candidates by today's auction amount and selects the top five. The article also gives example indicator and Python logic, including a comparison of current and…

EquitiesTechnical indicatorsChina marketsVolatility
SuperMind

This stock screen combines three technical conditions: daily amplitude above 1, MACD above its zero line, and closing price above the five-day moving average. The document explains these as filters for price movement and recent upward direction, then gives…

EquitiesTechnical indicatorsMomentumChina markets
SuperMind

The document presents a Chinese equity screen that requires a 14-period RSI below 65, a circulating market value between 5 billion and 10 billion yuan, and exclusion of Beijing-listed A shares. The example code applies these filters and, when enough…

China marketsEquitiesTechnical indicatorsMomentum
SuperMind

The document describes a Chinese equity selection rule combining a daily range filter, afternoon large-order net inflow, and a score based on price change multiplied by a large-order volume measure. It ranks candidates by the resulting score and selects the…

China marketsEquitiesTechnical indicatorsMomentum
SuperMind

The stated screen looks for stocks with turnover between 3% and 12%, a listing year of 2021, and ownership concentration below 20%. The article treats lower concentration as a sign of more dispersed ownership and suggests that the turnover band may help…

EquitiesChina marketsRisk managementStatistics
SuperMind

The screen selects stocks with turnover between 3% and 12%, beginning with the Chinese stock-code prefix 60, and keeps companies whose 2021 revenue exceeded their 2018 revenue by more than 10%. The article describes this as a way to combine trading activity…

EquitiesChina marketsFactor investingStatistics