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.
102 documents
The article explains short selling as borrowing an asset, selling it, then buying it back to return to the lender. Its gold illustration and a stock example show how a falling price can create a gain after borrowing costs and transaction charges. It also…
This overview explains how European Union financial regulation applies to algorithmic trading. It describes ESMA’s role in setting standards and the role of national regulators in implementing and supervising them. It introduces MiFID II as a framework…
This event announcement outlines a talk on risk oversight for automated trading. It emphasizes that algorithmic systems add operational and technology concerns to familiar market, financial, credit, and liquidity risks. The proposed discussion uses failures…
The article distinguishes algorithmic trading, high-frequency trading (HFT), and news-based trading by their aims, time horizons, speeds, and data sources. It describes algorithmic systems as rule-based automation across varied horizons, HFT as speed-focused…
This guide introduces algorithmic trading as a process of turning trading rules into programs, evaluating them with historical data, and deploying them for automated or partly automated execution. It outlines a learning path covering financial markets and…
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.…
The article explains the order management system (OMS) as a component of an automated trading system. It describes the information an order should carry, including instrument, direction, quantity, price constraints, type, duration, execution algorithm, and…
This article organizes suggested reading for people learning algorithmic trading. Its categories span market microstructure, statistics and econometrics, technical analysis, options, advanced statistics, machine learning, Python, and portfolio management.…
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…
The article introduces algorithmic trading as using coded rules to generate and execute orders, then compares it with manual trading. It highlights speed, simultaneous monitoring of markets, reduced reliance on emotional judgment, and the ability to backtest…
This event overview outlines a two-day NSE workshop on algorithmic trading, with material spanning strategy research, trading technology, regulation, and portfolio management. Topics include execution methods such as time- and volume-weighted orders,…
The article introduces multithreading as a way to handle several stock data downloads concurrently. Since network requests spend time waiting for external responses, separate threads can work on different tickers while other requests are pending. It outlines…
This article introduces FIX as a standardized messaging protocol used to connect participants and systems across electronic trading workflows. It describes how a shared format can reduce integration effort, simplify communication with multiple brokers, and…
This article introduces Nasdaq Data Link as a source of traditional financial, ESG, and alternative datasets, then explains how to retrieve data through the Quandl API in Python. It describes dataset categories and subscription access, and outlines the…
This guide explains the long-short equity approach: buying stocks expected to outperform and shorting those expected to underperform. It distinguishes general long-short portfolios from market-neutral funds, which seek to offset broad market exposure, and…
The document outlines a framework for deciding whether to expand algorithmic trading into another country or exchange. It groups the assessment into four considerations: market access and regulation, the technical requirements for connectivity, traded…
The article explains latency as the time required for data and orders to move through a trading system, distinguishing it from bandwidth or capacity. It compares a traditional workflow, where market data passes through a broker to a trader’s tools before…
The article argues that a backtest should approximate live trading conditions rather than maximize the appearance of historical returns. It recommends including commissions and slippage, with estimates adjusted to the instrument and checked against actual…
This project describes a cloud based automated system for WTI futures that uses machine learning to classify market conditions as trending or ranging. Several models vote within separate trend and range groups; when the groups disagree, their confidence…
This article describes India’s securities regulator, SEBI, considering new algorithmic trading rules. The proposed measures discussed include reducing high order-to-trade ratios, discouraging orders submitted without intent to execute, and potentially…
This event report describes two algorithmic trading workshops held at IIT Bombay’s Entrepreneurship Summit in 2015. The workshops were intended as introductions to the field and covered system architecture, latency, standardized protocols, strategy design…
The document discusses SEBI’s approval for Indian exchanges to set equity derivatives trading hours between 9 a.m. and 11:55 p.m., subject to suitable risk systems and infrastructure. Approval alone does not ensure the exchanges will extend their sessions.…
This career-focused article explains how banking experience may transfer to quantitative trading. It points to financial knowledge, disciplined processes, comfort with targets, collaboration, and attention to transaction speed as potentially useful…
The article describes a shift in Indian financial engineering education from broad, long-duration programs toward focused training in areas such as quantitative and algorithmic trading. It outlines traditional subjects including quantitative methods, equity…