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.
682 documents
This beginner-oriented guide explains machine learning through classification and house-price estimation. It distinguishes supervised learning, which uses examples with known outcomes, from unsupervised learning, which can group observations or identify…
The article distinguishes planned stop losses from sudden losses that occur when a stop cannot be executed at its intended level. It describes fixed stops based on a price or loss limit, trailing stops that follow conditions such as moving averages or…
This tutorial explains how to collect market data for many trading pairs through aggregated exchange endpoints and organize it for a multi-symbol strategy. Using Binance futures and Huobi spot as examples, it shows how to normalize different response formats…
The document introduces naive Bayes as a classification method that applies Bayes’ theorem while assuming predictor features are conditionally independent given the class. It explains the roles of the class prior, feature likelihood, feature prior, and…
This translated tutorial builds a simplified digital currency called Infocoin to explain core Bitcoin protocol ideas. It begins with signed payment messages, then introduces unique coin identifiers and a shared transaction ledger. Because separate users…
This historical account explains how Abraham de Moivre used probability, calculus, and the binomial structure later associated with Pascal’s triangle to study variation in repeated samples. Its example is sampling stones from a jar: repeated groups produce…
This debugging example shows why three variables assigned from repeated calls to a function can display the same final dictionary contents. The function updates a global dictionary and returns that same mutable object each time. Each local variable therefore…
The document describes three common mistakes made by new options traders: buying far out-of-the-money calls without accounting for timing and time decay, relying on one strategy in every market, and trading without a preplanned exit. It explains that an…
This essay contrasts two stylized accounts of a quantitative trader’s working day. The less automated workflow involves checking strategies and orders manually, adjusting allocations and contracts, monitoring live positions, recording profit, slippage, and…
The article distinguishes high-frequency trading firms from quantitative investment firms by their typical origins, time horizons, capital models, and technical priorities. It describes high-frequency trading as focused on rapid processing and efficient…
This outline maps a beginner’s path through quantitative trading. It starts with the purpose and requirements of quant trading and the components of a complete strategy, then introduces a trading platform, its configuration, common APIs, and strategy…
This project describes a unidirectional arbitrage bot trading Ether and token pairs across Etherdelta and Bittrex. The core idea is to seek gains from price differences between exchanges. Because trades on Etherdelta involve Ethereum transactions, the author…
This tutorial explains interface features for a trading strategy environment. It shows how a status display can present changing text, variables, formatted tables, and encoded images without filling the log with repeated updates. It also describes chart…
This article describes a portfolio component for an event-driven backtester. A portfolio receives signal events, produces order events, and updates positions and holdings from fill events. The NaivePortfolio example tracks each symbol’s quantity, cash,…
This document explains why an order-management interface can benefit from including the time an order was placed. When many limit orders remain unfilled, knowing each order’s age lets a trading system identify and cancel orders that have been pending longer…
This short note presents a reusable wrapper for retrying exchange API calls that fail because of network problems. Rather than adding retry logic separately around account, order-book, or candle-data requests, the wrapper repeatedly invokes a supplied method…
This article explains how nonlinear feature representations can make complex classification possible with a linear decision boundary. It uses support vector machines as an analogy: mapping inputs into a higher-dimensional feature space can make patterns that…
The report compares sparse covariance estimation, which sets selected off-diagonal elements to zero, with rotation-invariant methods that adjust sample covariance eigenvalues. The latter include simulation-based, linear, and random-matrix-based nonlinear…
This guide explains how to make TA-Lib available to strategies running in a self-hosted Python environment on 32-bit Windows with Python 2.7. Its example contrasts a built-in technical-analysis helper, which runs without a separate TA-Lib installation, with…
The article explains why a strategy can make money without winning more often than a coin toss. It contrasts high-win-rate approaches, which seek frequent small gains, with high reward-to-risk approaches, which tolerate more losing trades in pursuit of…
This overview compares common machine learning methods by their assumptions, strengths, and limitations. It introduces the bias variance tradeoff and explains how model complexity can lead to underfitting or overfitting. It then surveys naive Bayes, logistic…
This short post presents a function intended to produce signals around oversold and overbought thresholds. It waits until enough market records are available, then checks the latest two indicator readings: a downward move through 30 returns one signal, while…
The document compares simple systematic strategies, such as indicator rules applied to liquid developed markets, with advanced approaches that use specialist market knowledge, statistical testing, rigorous portfolio construction, and less liquid instruments.…
The document describes a high-frequency futures data method: connect to multiple futures brokers, subscribe each connection to the same contract, and combine incoming tick events. Its platform design uses a continuously running main loop and an event-waiting…