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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
WonderTrader
14 documents
Alphalens
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

SuperMind

This Chinese stock-screening post combines three filters: rank stocks by a measure of capital inflow, require weekly MACD to be above its zero line, and keep stocks whose ten-day gain is positive but below 35%. The author frames the filters as a way to find…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

This Chinese equity screen selects stocks with daily amplitude above 1, turnover between 2% and 9%, and displayed first-level bid volume greater than first-level ask volume. The article frames amplitude and turnover as activity and liquidity measures, with…

China marketsEquitiesMarket microstructure
ProRealCode

This indicator plots a conventional RSI of closing prices alongside an RSI calculated from a multi-vote On-Balance Volume series. The OBV component assigns directional votes based on changes in the high, close, and low, averages those votes, weights them by…

EquitiesTechnical indicatorsMomentum
SuperMind

This Chinese equity screening method combines daily amplitude above 1, a weekly crossover of the five-period moving average above the ten-period average, and a positive change in the KDJ K value. The article presents the conditions as a way to identify…

China marketsEquitiesMomentumTechnical indicators
SuperMind

This Chinese equity screen combines daily price amplitude above 1, a positive weekly MACD reading, and a market-cap rank between the 20th and 70th percentiles. The article also describes ranking candidates by volume relative to its 20-period average, then…

China marketsEquitiesMomentumTechnical indicators
MQL5 code base

This expert advisor uses a moving average to generate directional entries. Four consecutive declining moving-average values establish a downward trend condition, with a price rebound above the latest average triggering a sell; four rising values establish an…

ForexTechnical indicatorsPosition sizingRisk management
MQL5 code base

This indicator presents the standard Relative Strength Index as a histogram after rounding its readings to configurable increments. The described settings range from no rounding to progressively coarser groupings, including a three-level display at zero, the…

Technical indicatorsEquitiesForex
SuperMind

This Chinese-language post describes an equity screening rule combining price amplitude above a threshold, a rounded or arc-like price pattern, and a signal that the stock was controlled by major traders on the previous day. It presents the combination as a…

EquitiesTechnical indicatorsRisk management
ProRealCode

This long-only daily strategy seeks short-term rebounds in equity index CFDs while limiting entries to prices above a 200-period moving average. It sums RSI readings over the most recent two periods and enters when this cumulative measure falls below 35,…

EquitiesMean reversionTechnical indicatorsRisk management
BigQuant

This brief request proposes a factor based on the correlation between a benchmark’s returns and an individual stock’s returns over a three-day window. It names the intended inputs and lookback, but provides no code, worked example, explanation of how to…

EquitiesStatisticsFactor investing
SuperMind

This stock-selection idea combines three filters: a daily trading range above one percent of the previous close, a stock code beginning with 60, and a positive afternoon large-order flow signal. The code example operationalizes the range and code filters,…

EquitiesChina marketsTechnical indicatorsMarket microstructure
BigQuant

This April 2020 market note reviews a sharp decline in Chinese equities amid weakening fundamentals and falling investor sentiment. It reports that large- and small-cap indexes had similar declines, while consumer and utility sectors held up better and…

EquitiesChina marketsPortfolio constructionRisk management
MQL5 code base

This programming note explains how an object-oriented trading advisor can manage its configurable inputs as a structured set. It contrasts manually declaring fields and writing string conversion methods with a macro-based library that generates parameter…

ExecutionBacktestingPortfolio construction
SuperMind

This note describes a Chinese equity screen for stocks associated with the metaverse concept. It requires turnover between 3% and 12% and at least one limit-up event during the prior 25 days. The accompanying examples translate these conditions into…

EquitiesChina marketsMomentumBreakout
SuperMind

This note outlines a screen for Chinese equities associated with the robotics concept. It combines turnover between 3% and 12%, floating market capitalization below 10 billion yuan, and a ratio of 2021 revenue to 2018 revenue above 1.1. The post includes…

EquitiesChina marketsFactor investingRisk management
SuperMind

This note describes a Chinese A-share filter combining a turnover rate between 3% and 12%, a Dragon-Tiger list appearance the previous day, and a floating market capitalization between 5 billion and 10 billion yuan. It presents this as a way to find actively…

EquitiesChina marketsMarket microstructureRisk management
MQL5 code base

The method treats signals from an indicator as candidate highs or lows rather than immediate trade entries. It uses zigzag-style logic to connect candidate pivots and checks whether each candidate can form a geometrically plausible leg. A candidate that…

Technical indicatorsBreakoutRisk management
BigQuant

This note explains how to handle low-frequency financial or analyst factors alongside daily price and volume factors when constructing nonlinear models. One approach is to merge monthly or quarterly fundamentals with daily market data and carry the latest…

Machine learningFactor investingStatisticsBacktesting
SuperMind

This stock-selection approach combines a positive MACD reading with a company-type condition and circulating market capitalization above 10 billion yuan. The document presents the screen as a way to find stocks with upward price trends, sound fundamentals,…

EquitiesTechnical indicatorsMomentumChina markets
SuperMind

This post outlines a Chinese A-share stock screen combining an RSI below 65, seven consecutive down days, and a weekly five-period moving average crossing above the ten-period average. It presents the conditions as a way to identify stocks with a potentially…

EquitiesTechnical indicatorsMomentumChina markets
BigQuant

This brief note describes a feature-selection exercise based on a random forest template. The author says they ranked 37 stock factors by random forest importance and retained the nine factors with the highest importance scores. The document does not…

EquitiesFactor investingMachine learningStatistics
BigQuant

This Chinese-language research summary discusses forecasting stock-selection factor returns after commonly used factors became more volatile. It focuses on screening timing variables with Lasso and Elastic Net regression, then extending factor timing with…

EquitiesFactor investingMachine learningBacktesting
BigQuant

The post raises a backtesting concern: a user observes that a stock delisted on one date still appears sellable on a later scheduled rebalance date. A reply explains the platform behavior as a special backtest-engine rule: when a strategy does not handle a…

BacktestingEquitiesRisk management