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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 stock screen for the metaverse sector that looks for a limit-up event within a recent 25-day window and a current low below the prior session’s low. It interprets the earlier limit-up as a sign of market attention and the lower low…

EquitiesTechnical indicatorsMomentum
SuperMind

This document proposes screening stocks in the metaverse sector using a rounded, arc-like price pattern and three consecutive declining sessions. It frames the pattern as a possible sign of accumulation or a developing rebound, while treating the run of down…

EquitiesTechnical indicatorsMean reversion
SuperMind

This Chinese-language post proposes an equity screen combining price movement, profitability, and revenue growth. It selects stocks with a high-low range exceeding the 14-period ATR, return on equity above 15% for five consecutive years, and revenue growth…

EquitiesFactor investingTechnical indicatorsChina markets
BigQuant

This document outlines a forecast of constituent changes for four major mainland Chinese equity indices: the CSI 300, CSI 100, SSE 180, and SSE 50. It explains the potential trading relevance of index rebalancing: when funds tracking an index must adjust…

EquitiesEvent-drivenChina marketsPortfolio construction
SuperMind

This Chinese stock-screening proposal combines three conditions: at least five moving averages converge, a concentration measure is below 20%, and the 30-day moving average is rising. The author interprets convergence as a possible support or resistance…

EquitiesTechnical indicatorsTrend followingStatistics
SuperMind

This article proposes a Chinese A-share stock screen combining MACD above zero, a signal interpreted as large-investor control on the prior day, and at least one limit-up event within the previous month. It describes these conditions as proxies for an upward…

EquitiesChina marketsMomentumTechnical indicators
Qlib

This configuration specifies a Qlib workflow for training a CatBoost model on Alpha158 features for the CSI 500 universe. The data spans 2008 through mid-2020, with training through 2014, validation during 2015–2016, and testing from 2017 onward. The model…

China marketsEquitiesMachine learningBacktesting
SuperMind

This note outlines a Chinese equity screen for stocks classified in the metaverse sector, using a condition that the opening price at 9:25 be less than six percent above the previous close during 2021. It includes a sector-category rule and provides example…

EquitiesChina marketsTechnical indicatorsSentiment
BigQuant

This research summary examines whether macroeconomic and market indicators can predict returns to equity factors, with particular attention to the size and reversal factors in Chinese stocks. It uses IVX regression, presented as a response to endogeneity and…

EquitiesFactor investingStatisticsChina markets
SuperMind

This note describes a Chinese stock screen combining a morning-star candlestick pattern, a daily price range threshold, and a newly formed KDJ bullish crossover. Its indicator reference further conditions the crossover on a low prior J reading. The…

EquitiesTechnical indicatorsMomentumChina markets
SuperMind

This note proposes screening Chinese stocks for daily amplitude above 1, an opening price near the ten-day moving average, and a weekly trend condition described as crossing above a 30-week moving average. The stated interpretation is that proximity to the…

EquitiesTechnical indicatorsBreakoutVolatility
SuperMind

This note describes a Chinese equity screen requiring daily amplitude above 1, a circulating share count at or below 5.5 billion shares, and a limit-up move within the past month. It frames these conditions as a way to find volatile, relatively smaller-float…

EquitiesMomentumVolatilityChina markets
SuperMind

This Chinese stock-screening note combines three filters: daily amplitude above 1, a positive ten-day return below 35%, and a selected company type. Its rationale is to find shares with meaningful movement and recent gains while avoiding the strongest recent…

EquitiesMomentumVolatilityChina markets
SuperMind

This Chinese stock-selection post describes screening stocks in the metaverse theme using a short-term price condition and an opening-auction signal. Its prose says to select stocks whose average price is above the five-day moving average and whose prior-day…

EquitiesChina marketsTechnical indicatorsMean reversion
BigQuant

This summary of a Chinese securities research presentation describes several equity research approaches. It outlines an event-driven system intended to assess whether market events have an effective price impact, alongside a multi-factor risk framework and…

EquitiesChina marketsEvent-drivenFactor investing
SuperMind

This document outlines a Chinese A-share stock screen combining price trends and valuation. It selects Shenzhen main-board stocks with price-to-earnings ratios from 0 to 29.01 and price-to-book ratios from 0 to 3.11, requires the 30-day moving average to be…

EquitiesChina marketsTechnical indicatorsFactor investing
MQL5 code base

The document describes a forex and stock trading EA that uses the DeMarker indicator and changes position size after losses. A user can configure the multiplier or lot-size increments, trading hours, trade limits, stop-loss and take-profit distances, and a…

ForexEquitiesTechnical indicatorsPosition sizing
SuperMind

This post describes a Chinese A-share screening idea based on intraday amplitude, a ratio combining the prior day’s turnover with current auction volume relative to prior volume, and an earlier session’s actual turnover range. It presents the intended ratio…

EquitiesChina marketsTechnical indicatorsMarket microstructure
SuperMind

This Chinese-language post proposes a stock screen combining intraday amplitude above 1%, exclusion of special-treatment stocks, a five-session closing-price high condition described as a five-step limit-up approach, and a prior close above the 250-day…

EquitiesChina marketsTechnical indicatorsBreakout
SuperMind

The described stock-selection rule filters for shares with daily price amplitude above 1% and more than one year since listing, then ranks candidates by the day’s auction trading amount and selects the top five. The rationale is to favor stocks showing price…

EquitiesChina marketsMomentum
SuperMind

This strategy uses a short moving average and a long moving average to generate entry and exit signals. It buys when the 10-period average crosses above the 240-period average, allocating 80% of available cash, and sells the entire position when the short…

EquitiesTrend followingTechnical indicatorsPosition sizing
SuperMind

The proposed Chinese equity screen looks for companies with positive earnings, market capitalization within a stated ceiling, daily price amplitude above a threshold, and revenue growth between two specified years. The article frames the size and revenue…

EquitiesChina marketsFactor investingStatistics
SuperMind

This stock screening idea combines an RSI reading below 65 with seven consecutive sessions in which the close is below the open, while excluding the intended board category. The article presents the sequence of bearish sessions as a sign of weakness and the…

EquitiesChina marketsTechnical indicatorsMean reversion