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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

79,386 documents

OctoBot

The document explains automated trading bots as programs that use market or other data to analyze conditions and place trades under a configured strategy. It describes potential benefits such as faster, more frequent execution and less emotion-driven…

CryptoEquitiesForexGrid trading
SuperMind

The post proposes a Chinese equity screen using turnover between 3% and 12%, a positive return over ten days below 35%, and a dividend payout ratio above 25% for 2019. It says to select stocks before 10 a.m. and presents the dividend filter as a way to…

EquitiesChina marketsFactor investingBacktesting
Amberdata research

The article outlines how Amberdata datasets can be accessed through Snowflake, Google Analytics Hub, and Databricks. It frames these integrations as a way for institutional researchers and traders to work with historical and fresh digital-asset data using…

CryptoOn-chain dataDeFiMarket microstructure
ProRealCode

This article describes a backtesting indicator for evaluating exit distances on a supplied trading signal. It simulates a single-unit position, closes equal portions at up to three take-profit levels, and exits the remaining position at the first stop level…

BacktestingRisk managementTechnical indicatorsExecution
vn.py community

The forum exchange addresses whether a backtest for Shanghai Futures Exchange instruments needs to distinguish between closing a position opened the same day and closing one opened earlier. The question comes from a trader analyzing fill prices in a trade…

FuturesBacktestingExecution
SuperMind

This Chinese-language post outlines a proposed screen for mainland Chinese exchange-listed stocks in the metaverse industry. It selects names among the five highest by the day’s auction trading value, then requires the weekly five-period moving average to…

EquitiesChina marketsTechnical indicatorsMomentum
Amberdata research

This market report surveys Bitcoin’s first quarter of 2025, linking sharp price movements to macroeconomic developments, regulatory news, security events, and institutional activity. It discusses a peak near $109,000, subsequent pullbacks, a major exchange…

CryptoOn-chain dataSentimentVolatility
Lumibot

This report presents a short backtest of a large-cap stock strategy attributed to a multi-agent AI trading bot and compares it with SPY. The stated test ran from January 4 to January 15, 2026, using Yahoo data and a universe of large technology and other…

EquitiesBacktestingUS marketsMachine learning
SuperMind

The document describes a daily stock screen based on three conditions: a high-to-low range greater than one percent, a reversal or engulfing-style pattern, and a close above the previous day’s low. It presents these conditions as a way to find stocks whose…

EquitiesTechnical indicatorsMean reversionBacktesting
Cryptohopper blog

The document introduces the information in a candlestick: the open and close define its body, while the high and low define its wicks. It classifies candles as bullish, bearish, or neutral by comparing closing and opening prices. These descriptions apply to…

CryptoTechnical indicatorsMomentum
SuperMind

The post describes a stock-selection screen based on turnover between three and twelve percent, appearance on a market trading list the previous day, and a negative MACD reading from two days earlier. The accompanying formula adds further filters involving…

EquitiesTechnical indicatorsMomentumRisk management
MQL5 code base

The document explains the Detrended Price Oscillator (DPO) as the difference between a closing price and its simple moving average over a chosen period. By subtracting the moving average, the indicator filters out some of the broader price direction,…

Technical indicatorsStatistics
SuperMind

This Chinese equity screening note combines three conditions: turnover between 3% and 12%, membership in a beverage and alcohol import-export category, and an auction-period price change greater than -2% and less than 5%. It frames the filters as a way to…

EquitiesChina marketsTechnical indicators
BigQuant

This report excerpt reviews several Chinese equity strategies for the week ending around July 19, 2020. It says valuation and quality factors performed relatively well while momentum weakened. The CSI 300 and CSI 500 enhanced portfolios both declined for the…

EquitiesChina marketsFactor investingMomentum
MQL5 code base

This brief indicator description explains Acceleration Bands, attributed to Price Headley, as bands derived from the daily price range. It identifies two configurable inputs: the calculation period and a factor that controls how widely the bands expand. The…

Technical indicatorsStatistics
SuperMind

This note describes a Chinese equity screen requiring turnover between 3% and 12%, a stock code beginning with 60, and a nonempty name for an unredeemed convertible bond. The stated rationale is to focus on stocks with a specified level of trading activity…

EquitiesChina markets
MQL5 code base

This document describes a function for producing directional signals from the OsMA indicator: one return value represents a buy and another represents a sell. It says the function can be included in an expert advisor and called to check the current signal.…

ForexTechnical indicatorsBacktestingRisk management
MQL5 code base

This indicator presents the standard stochastic oscillator's %K and %D lines together with a histogram showing their relationship. Histogram colors distinguish whether %K is above or below %D and whether it lies above or below the configured overbought and…

Technical indicatorsMomentum
SuperMind

This post outlines a Chinese A-share screen combining membership in a metaverse-related category with a turnover-based condition, a technical signal, market-cap ranking, and a valuation filter using PEG. It also sketches a Python workflow that retrieves…

China marketsEquitiesTechnical indicatorsFactor investing
MQL5 code base

ColorMFI_X20_Cloud is a chart indicator that adds adjustable background shading to overbought and oversold regions. Its inputs define five reference levels around the middle of the indicator range, including upper and lower thresholds and more extreme…

Technical indicatorsMean reversion
FMZ forum

This annotated strategy describes a directional grid that can operate buy-first or sell-first. In buy-first mode, it places a sequence of buy orders below an initial price at fixed intervals. When a buy fills, it places a sell order above that fill by a…

Grid tradingExecutionRisk managementPosition sizing
Amberdata research

This market commentary connects Federal Reserve easing, Bitcoin price prospects, spot ETF adoption, and options volatility. It contrasts a possible short-term volatility surge with a longer-term decline as institutional ownership grows. For a bullish…

CryptoOptionsVolatilityDerivatives pricing
SuperMind

This stock-selection idea screens Chinese equities for four conditions: membership in the metaverse theme, positive net buying by large participants during the opening auction, a robotics concept association, and circulating market capitalization below 10…

EquitiesChina marketsSentimentRisk management