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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

BigQuant

This assignment asks learners to build a trading strategy using the standard deviation of turnover rate as a stock selection factor. It also specifies two exit rules: liquidate positions when the broad market falls by 4% consecutively, and close an…

China marketsEquitiesFactor investingRisk management
BigQuant

The article contrasts discretionary stock trading with quantitative approaches that analyze large datasets for statistical relationships. It describes using price and volume alongside less conventional inputs, such as online search activity and social media,…

EquitiesMachine learningSentimentExecution
SuperMind

This Chinese equity screening proposal combines three ideas: select stocks with more than two limit-up sessions in the past ten days, constrain turnover to the interval above 2% and below 9%, and rank candidates by a measure of fund strength. The post…

EquitiesMomentumMarket microstructureChina markets
SuperMind

This document describes a Chinese equity screening rule that combines a positive MACD reading, positive price-to-earnings ratio, and an upward-trending 30-day moving average. It interprets the MACD and moving average conditions as signs of upward momentum,…

EquitiesTechnical indicatorsMomentumChina markets
SuperMind

This proposed screen targets Shenzhen main-board stocks with turnover between 3% and 12%, positive product of the day’s price change and large-order net flow, price-to-earnings ratios from 0 to 29.01, and price-to-book ratios from 0 to 3.11. The article…

China marketsEquitiesMarket microstructureFactor investing
SuperMind

This proposed Chinese equity screen selects stocks whose daily range exceeds 1%, that had at least one limit-up day in the prior 25 days, and that appeared on the previous day’s Dragon-Tiger List. The article interprets these conditions as signals of higher…

China marketsEquitiesMomentumVolatility
SuperMind

This stock-selection example screens Chinese equities using a turnover range, year-over-year net profit growth, and the prior day’s trading value. It then ranks qualifying stocks by institutional ownership and selects the highest-ranked names. The rationale…

EquitiesFactor investingChina marketsBacktesting
BigQuant

The document presents a discretionary chart-reading idea for stocks that rally sharply and then drift lower on shrinking volume and narrow price ranges. It interprets this pattern as possible position cleaning by a large market participant, arguing that slow…

EquitiesTechnical indicatorsChina markets
MQL5 code base

This indicator uses peaks in price histograms to draw potential support and resistance levels. It presents four lines based on different histogram horizons: a gold line for one day, plus red, magenta, and blue lines for short-, medium-, and long-term…

Technical indicatorsMarket microstructureEquities
SuperMind

This document describes a Chinese-equity screen combining three conditions: membership in the metaverse theme, circulating market capitalization above 10 billion yuan, and a prior session that did not close at the daily limit. It also provides example…

EquitiesChina marketsTechnical indicatorsRisk management
BigQuant

This 2020 investment analysis discusses the ChiNext index and Bosera's ETF tracking it. It argues that refinancing policy changes and the stock registration system could improve financing access for technology and growth companies. The index is described as…

EquitiesChina marketsPortfolio construction
SuperMind

This stock-selection idea filters for shares with prior-day turnover above 60 million and a price gain at 9:25 below 6%, then orders candidates by descending capital strength, described in the post as favoring larger transaction amounts. The post frames the…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

The post raises a portfolio accounting issue that can affect automated sell rules. After a cash dividend or share distribution, the stock price may adjust downward while a trading program still compares it with the pre-event holding cost. That mismatch can…

EquitiesRisk managementExecution
SuperMind

This post proposes a Chinese stock screen combining three conditions: today's increase in holdings as a share of the stock above 5%, evidence of main-player control on the prior day, and an upward 30-day average. The post interprets the buying-flow measure…

EquitiesChina marketsTechnical indicatorsMomentum
BigQuant

This research summary introduces APM, a stock-selection factor built from differences between morning and afternoon price behavior in Chinese A-shares. Its premise is that informed traders are more active in the morning, making morning price moves a stronger…

EquitiesFactor investingChina marketsBacktesting
SuperMind

This note outlines a daily, end-of-session stock screen that requires MACD to be above zero and an institutional-flow measure to be positive, then ranks qualifying stocks by popularity. It explains MACD as a short-term trend indicator and institutional flow…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This note describes a daily stock screen combining prior-day price amplitude, appearance on the Dragon Tiger List, and trading turnover above a stated threshold. The rationale is that larger price swings may signal opportunity, Dragon Tiger List activity may…

EquitiesChina marketsTechnical indicators
SuperMind

This stock-selection screen combines a moving-average cluster with recent price strength. It looks for shares with at least five moving averages converging and more than two limit-up sessions within a ten-day window, with the stated screen restricted to…

China marketsEquitiesMomentumTechnical indicators
SuperMind

This Chinese equity selection method filters for daily price amplitude above 1, a product of yesterday’s turnover rate and the ratio of today’s opening auction volume to yesterday’s volume between 0.5 and 2, and a positive daily MACD value. The stated intent…

China marketsEquitiesTechnical indicatorsMarket microstructure
SuperMind

This Chinese equity screening idea combines a relative strength index below 65, a condition involving daily price change multiplied by net large-order volume, and a positive 10-day return capped below 35%. The accompanying example expresses the order-flow…

China marketsEquitiesTechnical indicatorsMomentum
SuperMind

This A-share stock-selection proposal combines price amplitude above 1, the presence of an outstanding convertible bond, auction-period price gains associated with large buy orders, and a combined large and extra-large buy volume threshold of more than 0.7…

EquitiesMarket microstructureSentimentChina markets
SuperMind

This document describes a short-term A-share stock screen combining price movement, a candlestick pattern, and trading activity. It looks for amplitude above 1, a condition labeled as a Kute Intelligent morning star, and a range for yesterday’s turnover rate…

EquitiesTechnical indicatorsSentimentChina markets
SuperMind

This Chinese equity screen looks for stocks with turnover between 3% and 12% and at least one limit-up event in both the prior 25-day window and the past month. It treats moderate trading activity as a sign of liquidity and recent limit-up moves as…

EquitiesMomentumBreakoutChina markets