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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

29 documents

QuantInsti blog

The article surveys stock market simulators for practicing trades with virtual funds. It describes services for manual trading, historical chart exercises, and, in some cases, automated strategies or broker connections. The listed features include market…

EquitiesBacktestingTechnical indicatorsOptions
QuantInsti blog

This project describes an automated strategy that uses live EURUSD prices to generate signals for EURUSD, USDCHF, and XOM. A long signal occurs when EURUSD rises above the highest close of the prior five days; a short signal occurs below the lowest close.…

ForexEquitiesBreakoutMomentum
QuantInsti blog

The article outlines a supervised learning workflow for classifying EUR/USD direction. It introduces features, feature selection, and support vector machines, then describes a model using hourly EUR/USD data dating back to 2010, with MACD and Parabolic SAR…

ForexMachine learningTechnical indicatorsBacktesting
QuantInsti blog

This project builds a random forest regression model to estimate the next day’s EUR/USD closing price from daily price data, technical indicators, and Twitter sentiment. Predictors include OHLCV values, short and long EMAs, RSI, OBV, and daily mean sentiment…

ForexMachine learningSentimentTechnical indicators
QuantInsti blog

This tutorial explains how to connect a trading application to FXCM through the FIX protocol using the QuickFIX engine. It outlines the session settings and credentials, shows how the logon exchange works, and describes requesting trading-session status to…

ForexExecutionMarket microstructure
QuantInsti blog

This article turns machine-learning predictions into a rule-based EUR/USD strategy and compares its historical performance with buy and hold. Its indicators are Parabolic SAR, which trails price and reverses after a price break, and the MACD histogram,…

ForexMachine learningTechnical indicatorsBacktesting
QuantInsti blog

The document explains RippleNet’s role as a payments network for financial institutions and distinguishes it from XRP, the digital asset used as a possible bridge currency. It describes the XRP Ledger, validator consensus, trusted Unique Node Lists,…

CryptoForexMarket microstructureRisk management
QuantInsti blog

The document describes automated forex trading as the use of programmed rules to monitor currency markets and place trades. It lays out a development workflow: define entry and exit logic, program the strategy, monitor markets, execute orders, add risk…

ForexBacktestingRisk managementExecution
QuantInsti blog

The document explains the real effective exchange rate (REER) as an inflation-adjusted, trade-weighted measure of a currency against a basket of trading partners. It describes how a country’s REER can help assess changes in currency strength and trade…

ForexStatisticsMulti-asset
QuantInsti blog

This article outlines a Python workflow for retrieving historical market data through OANDA, storing it locally, and evaluating a simple trading rule. It describes selecting an instrument, date range, and granularity, handling data in chunks, and saving…

ForexTechnical indicatorsBacktestingExecution
QuantInsti blog

This tutorial shows how to retrieve historical foreign-exchange price data with yfinance and inspect it in a Python workflow. It covers daily data for a currency pair, minute-frequency data, and downloading multiple pairs together. The described process…

ForexExecution
QuantInsti blog

This document explains how the IBrokers R package connects a strategy to Interactive Brokers through Trader Workstation (TWS). It outlines functions for requesting contract details, live quotes, market depth, real-time bars, and historical data, along with…

ExecutionMarket microstructureEquitiesOptions
QuantInsti blog

This compilation describes QuantInsti’s 2018 webinars on systematic trading, covering risk management, strategy development and backtesting, foreign exchange, and equity products on SGX. The risk session outlines leverage choices, drawdown, stop losses,…

Risk managementBacktestingForexEquities
QuantInsti blog

A forex carry trade seeks to earn the interest-rate difference between currencies by holding a position that receives the higher rate and pays the lower one. The document explains how that return depends on the position and notional, and introduces covered…

ForexCarryRisk managementArbitrage
QuantInsti blog

The article describes directional change (DC), a threshold-based way to represent price movement through confirmed turning points rather than fixed-time observations. It defines upward and downward runs, their overshoots, and three derived measures: total…

ForexTechnical indicatorsMachine learningVolatility
QuantInsti blog

This beginner overview explains why foreign exchange exists, how currency systems evolved from barter and gold-backed notes to floating currencies, and how the FX market supports conversion and trading. It describes currency pairs as relative prices,…

ForexRisk managementPosition sizing
QuantInsti blog

This project describes a daily statistical arbitrage strategy applied to six INR currency pairs over the stated 2011–2013 sample. It screens pair combinations with cointegration tests, then applies a cointegrated Augmented Dickey–Fuller test to selected…

ForexPairs tradingMean reversionStatistics
QuantInsti blog

A bear trap is a brief selloff that appears to signal a reversal but is followed by recovery and continuation of an existing uptrend. The article describes how bearish traders may mistake a pullback or liquidation-driven move for a lasting breakdown, then…

ForexTrend followingRisk managementTechnical indicators
QuantInsti blog

The document explains harmonic trading as a method that combines geometric price swings with Fibonacci ratios to identify potential reversal zones. It describes the Gartley, Butterfly, Bat, and Crab patterns, outlining the retracement and extension…

ForexTechnical indicatorsRisk management
QuantInsti blog

The article explains direct market access (DMA) as a broker-provided route for submitting orders to exchange order books, with checks such as margin review before execution. It contrasts this with retail arrangements where a broker may intermediate orders or…

ExecutionMarket microstructureForexHigh-frequency trading
QuantInsti blog

The article surveys nine factors that may influence exchange rates: political conditions, inflation, interest rates, government debt, terms of trade, speculation, capital-market performance, employment data, and economic planning. For each, it gives a…

ForexChina marketsUS markets
QuantInsti blog

This webinar description introduces using Python to implement automated trading in live markets, with IBridgePy as the main example. It outlines a workflow that connects a strategy to Interactive Brokers and identifies three basic platform tasks: retrieving…

ExecutionBacktestingRisk managementEquities
QuantInsti blog

This guide explains how candlesticks summarize open, high, low, and close prices, then describes common formations that may signal a bullish reversal or continuation. Single-candle examples include the hammer, bullish marubozu, dragonfly doji, and belt hold.…

Technical indicatorsEquitiesForexRisk management