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.
8 documents
This introductory guide organizes quantitative trading into four connected areas: finding strategies, testing them on historical data, executing trades through a broker, and managing capital and risk. It sketches mean-reversion and momentum approaches,…
This article proposes a staged reading path for people entering quantitative and algorithmic trading. It recommends first learning how a trading system fits together, including alpha generation, risk controls, automated execution, and common momentum and…
The document describes building a small distributed computer cluster to run independent parameter variations for systematic trading backtests in parallel. It presents four Raspberry Pi computers connected by Ethernet, with SLURM as the workload manager, and…
The article explains how to distribute a US sector ETF momentum strategy’s parameter sweep across a Raspberry Pi cluster managed with SLURM. It varies momentum lookback windows from 21 to 252 business days and the number of holdings from one to eight,…
This tutorial explains how to implement a long-only, monthly rebalanced momentum strategy with QSTrader. It ranks ten US sector ETFs by six-month holding-period return and allocates to the three strongest sectors for the next month. The example accounts for…
This tutorial implements a long-only moving average crossover strategy in a pandas-based research backtester. It compares a short simple moving average with a longer one, enters when the short average is above the long average, and exits when it falls below.…
This introduction defines deep learning as machine learning that learns layered data representations, rather than relying entirely on manually designed features. It explains the idea through image recognition, where successive network layers can build from…
This introduction describes tactical asset allocation as a long-horizon portfolio approach that adjusts broad asset-class exposures at relatively infrequent intervals. It contrasts the approach with fixed buy-and-hold allocations and short-term trading, and…