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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 A-share screening recipe selects stocks with daily amplitude above 1%, that were not limit-up or limit-down the previous day, and with a circulating market capitalization from 5 billion to 10 billion yuan. The post interprets amplitude and prior limit…

EquitiesTechnical indicatorsRisk managementChina markets
SuperMind

This screening recipe selects stocks with daily amplitude above 1, a high equal to the highest high over the current and prior day, and a named “morning star” condition. The document defines the latter through a crossover of five- and ten-day moving averages…

EquitiesTechnical indicatorsMean reversionChina markets
SuperMind

This A-share stock screen combines three conditions: the stock’s reported increase in positions today must exceed 5%, weekly MACD must be above zero, and the stock must have had more than two limit-up days in the past ten days. The accompanying explanation…

EquitiesMomentumBreakoutTechnical indicators
BigQuant

This report studies whether the most unusual intraday price bar contains useful stock-selection information. It defines extremeness as the absolute distance between a bar’s return and the median intraday return, then examines the bar with the greatest…

EquitiesFactor investingMean reversionMomentum
BigQuant

This study compares six cross-validation approaches for tuning machine-learning models on financial time series. It argues that ordinary shuffled K-fold validation can leak temporal structure and select overly complex models. Expanding-window time-series…

Machine learningStatisticsBacktestingChina markets
SuperMind

This article describes a daily, after-close screen for Chinese stocks with MACD above zero, more than two qualifying limit-up days within ten days, and ranking by individual stock popularity. It defines a qualifying limit-up day as a daily gain of at least…

EquitiesChina marketsMomentumTechnical indicators
SuperMind

This article proposes a Chinese stock selection screen using a turnover range of 3% to 12%, at least one limit-up event within the previous 25 days, and large-order net flow above 0.05 on each of at least three consecutive days. Its example formula adds…

EquitiesChina marketsMomentumTechnical indicators
vn.py community

This tutorial explains how VeighNa’s backtesting engine replays historical daily bars to evaluate an equity strategy. It walks through configuring instruments, interval, dates, and initial capital; attaching a strategy and dated signal table; loading data;…

EquitiesBacktestingExecutionRisk management
TqSdk

This stock-selection idea combines a technical condition, an industry filter, and recent positive returns. It proposes screening for Chinese beverage and alcohol import-export companies with a 14-period RSI below 65 and a positive return, while also…

EquitiesChina marketsTechnical indicatorsStatistics
BigQuant

The document gives a conversion procedure for obtaining forward-adjusted stock prices when a platform supplies backward-adjusted prices and their adjustment factors. The first step is to recover the unadjusted market price by dividing the backward-adjusted…

EquitiesStatistics
SuperMind

The document describes a Chinese equity screening idea: retain stocks whose codes begin with 60, whose turnover rate falls between 3% and 12%, and whose three technical indicators show a bullish crossover. The accompanying explanation frames these filters as…

EquitiesChina marketsTechnical indicatorsMomentum
FMZ forum

The article argues that identifying market turning points consistently is difficult and that missing a small number of the strongest up days can sharply reduce long-term returns. It contrasts steady index exposure with hypothetical timing outcomes in the US…

EquitiesUS marketsChina marketsStatistics
SuperMind

This Chinese stock-selection proposal filters for companies classified in the metaverse sector, a rounded price pattern, and exclusion from the STAR Market. Its example rules also include price movement and range conditions, a moving-average relationship,…

China marketsEquitiesTechnical indicatorsBreakout
SuperMind

This stock screen combines four conditions: price amplitude above one, current volume above ten thousand lots, a higher open, and appearance on the previous day’s Dragon and Tiger List, a ranking of unusually active stocks. The article frames the combination…

China marketsEquitiesMomentumSentiment
BigQuant

This short market commentary presents a July 2020 view of Chinese indices and sector positioning. It describes the Shanghai Composite and SSE 50 as correcting while potentially forming daily-chart continuation setups, and says the ChiNext remained in a…

EquitiesChina marketsTrend followingRisk management
SuperMind

This proposed Chinese equity screen requires MACD to be above zero, the price-to-earnings ratio to be positive, and the weekly five-period moving average to cross above the ten-period average. The screen is intended to run before each trading session.…

EquitiesChina marketsTechnical indicatorsMomentum
SuperMind

This stock-screening proposal combines price activity with reported earnings growth. It selects shares whose amplitude exceeds the stated threshold, that had a three-day limit-up streak as of the prior day, and whose year-over-year growth in net profit…

EquitiesChina marketsMomentumTechnical indicators
BigQuant

This December 2024 market note tracks sentiment, fund crowding, and two stock-selection approaches in Chinese equities. It describes breadth and moving-average sentiment measures as elevated, with momentum indicators pointing upward. It also reports that…

EquitiesChina marketsSentimentFactor investing
BigQuant

This forum post asks how to implement minute-level backtesting for a stock strategy that receives signals at the daily level and refines exits using intraday prices. The proposed rules would sell a holding after it rises by a specified amount and then…

EquitiesBacktestingExecutionRisk management
SuperMind

The post describes a stock screen for mainland Chinese A-shares that excludes Beijing-listed shares, looks for a stacked sequence of moving averages, and requires 2021 revenue to exceed 2018 revenue by a stated ratio. The moving-average condition is…

EquitiesChina marketsTechnical indicatorsFactor investing
SuperMind

The document translates David Polen’s bottom-up investment principles into a quantitative stock-selection approach. The original framework emphasizes financially strong companies, ample free cash flow, earnings momentum, valuation based on expected returns…

EquitiesChina marketsFactor investingPortfolio construction
SuperMind

This Supermind screen selects listed Chinese stocks with price amplitude above 1, circulating market capitalization above 10 billion yuan, and a positive price-to-earnings ratio. The proposed rationale is to combine price movement, company scale, and…

EquitiesChina marketsTechnical indicatorsFactor investing
SuperMind

This Supermind stock screen selects main-board Chinese equities associated with the robotics concept. It requires turnover between 3% and 12%, circulating market capitalization below 10 billion yuan, and a daily maximum decline between 4% and 5%. The…

EquitiesChina marketsTechnical indicatorsRisk management
SuperMind

The document describes a technical stock screen that combines three conditions: daily amplitude above a threshold, a positive weekly MACD histogram, and a current high matching the highest high over the recent two-day window. It frames these conditions as a…

EquitiesTechnical indicatorsMomentumChina markets