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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

29,558 documents

BigQuant

The document examines a top-ranked strategy that selects the smallest stocks in the CSI 1000 and reports unusually strong historical performance. Its central lesson is that a backtest must use index constituents as they were known at each historical date.…

China marketsEquitiesBacktestingRisk management
SuperMind

This stock-selection rule screens for shares with turnover between 3% and 12%, circulating market value between 5 billion and 10 billion yuan, and a proprietary “today control” measure above 21. The post presents the combination as a way to find stocks with…

EquitiesChina marketsTechnical indicatorsRisk management
MQL5 code base

The author describes a manual-trading aid intended to reduce repeated order-entry steps. For pending trades, the script is said to place limit or stop orders at an appropriate setting. For immediate trades, the user enters a stop-loss value without…

ExecutionPosition sizingRisk management
TqSdk

This TqSdk guide explains how to run timed actions inside the main loop driven by wait_update, rather than pausing the program with a separate sleep loop. For actions tied to the trading session, it recommends checking the market timestamp in quote.datetime,…

ExecutionFuturesRisk management
Amberdata research

The analysis compares Binance BTC/FDUSD order book behavior around six 2025 Federal Open Market Committee decisions: five rate holds and one cut. It tracks five-minute averages of volatility, bid-ask spread, depth, order book imbalance, and pressure…

CryptoMarket microstructureVolatilityExecution
SuperMind

The document presents a short-term stock screen combining daily price range, positive large-order net volume over several consecutive days, and a stock-code prefix. Its stated final conditions are amplitude above one, net volume above 0.05 for at least three…

EquitiesTechnical indicatorsMomentumRisk management
SuperMind

The document outlines a Chinese equity screening approach that starts with price amplitude, a minimum market capitalization, and a comparison of 2021 revenue with 2018 revenue. It discusses limitations of relying on revenue growth alone, including omitted…

EquitiesChina marketsFactor investingRisk management
MQL5 code base

The document describes a collection of scripts for closing orders by comment, profit or loss threshold, magic number, order type, or symbol. A combined script supports the criteria offered by the individual tools. This is operational guidance for managing…

ExecutionRisk management
OctoBot

Grid trading places a series of buy and sell orders at set price intervals. As the market moves through those levels, orders can buy at lower prices and sell at higher ones. The approach seeks to collect gains from price fluctuations without relying on a…

Grid tradingVolatilityExecutionRisk management
Lumibot

The document contrasts OpenAlice, presented as an AI agent for researching and managing trades across a full lifecycle, with LumiBot, a Python framework for building trading strategies. LumiBot can support deterministic strategies, individual AI agents, or…

Machine learningBacktestingRisk managementExecution
Amberdata research

This strategy-sharing article describes an enhanced China Securities 150 equity approach that blends model-based stock ranking with technical timing. The universe is manually narrowed to roughly 100–300 large, liquid constituent-style stocks. An AI model…

EquitiesMachine learningMomentumTechnical indicators
SuperMind

This post proposes screening A-shares for turnover between 3% and 12%, a positive gain over ten days that remains below 35%, and no limit-up close on the previous day. The author characterizes the method as a momentum-oriented screen and cautions that…

EquitiesChina marketsMomentumRisk management
Awesome Systematic Trading

This algorithmic example describes a monthly volatility risk premium trade using SPY options and shares. It selects options with an expiry near one month, sells an at-the-money call and put to form a short straddle, and buys a put with a strike near 15%…

OptionsEquitiesVolatilityRisk management
SuperMind

This stock selection approach screens for securities with an RSI below 65, a stated circulating market capitalization range of 5 to 10 billion yuan, and at least seven consecutive declining sessions. It combines a momentum oscillator, company size, and…

EquitiesChina marketsTechnical indicatorsMomentum
MQL5 code base

The script described opens buy positions with stop-loss and take-profit levels set at fixed point distances from the current price. Its money-management input controls trade volume as a proportion of the account deposit, linking position size to the funds…

Position sizingRisk managementExecution
SuperMind

This proposed equity screen combines three conditions: today's increase in holdings must exceed 5%, the company must have been listed before 2019, and its 2019 dividend payout ratio must exceed 25%. The article interprets the holdings increase as possible…

China marketsEquitiesFactor investingRisk management
SuperMind

This Chinese equity screen combines a daily amplitude filter with robotics-sector membership, a circulating market capitalization below 10 billion yuan, and at least two limit-up sessions during the previous 500 days. The rationale is to find smaller…

China marketsEquitiesMomentumRisk management
SuperMind

This note describes a daily stock screen that combines amplitude above 1, a change in a measure labeled institutional buying, and a positive return. Its final rules define amplitude using a platform-specific indicator, institutional activity through the…

EquitiesTechnical indicatorsVolatilityRisk management
MQL5 code base

This expert advisor places buy-stop and sell-stop orders at configurable distances from the current price, forming a grid that can trade in the direction of price breakouts. Settings include starting lot size, optional lot increases, grid start distance,…

ForexGrid tradingBreakoutRisk management
SuperMind

The article outlines an equity screen combining price amplitude above a stated threshold, rising lows as a sign of an improving base, and a ranking by stock or industry attention. It includes example formula logic and Python-like pseudocode, with the latter…

EquitiesTechnical indicatorsMomentumRisk management
MQL5 code base

Pipsover 2 is described as an updated expert advisor that adds trailing-stop and break-even handling. Its stated sequence is to attempt to move a position to break-even first, then allow trailing-stop management. The break-even setting also serves as the…

Risk managementExecutionTechnical indicators
SuperMind

This proposed equity screen selects companies with price amplitude above one percent, market capitalization within 10 billion, positive average net profit, and a current low below the previous session’s low. The article’s example code extends those…

EquitiesTechnical indicatorsRisk management
SuperMind

This Chinese stock-selection proposal combines three filters: price amplitude above one, a rounded chart pattern, and a nonempty name for outstanding convertible bonds. A referenced indicator formula expresses the amplitude and chart-shape conditions, while…

EquitiesTechnical indicatorsRisk management
SuperMind

This stock-selection method screens companies in the metaverse industry using three simultaneous bullish crossovers: MACD above its signal line, the 5-day moving average above the 10-day average, and the 5-day average above the 20-day average. It also…

EquitiesTechnical indicatorsMomentumChina markets