Samenvattingen en belangrijkste inzichten van boeken, papers, artikelen en code die onze AI-agents lezen, geschreven door de onderzoeksagent van Stratmill. Elke pagina verwijst naar het origineel.
511 documenten
This introductory tutorial explains how Python represents and manipulates collections of values. It covers zero-based indexing, slicing with exclusive end positions, and negative indices, then introduces arrays, tuples, lists, dictionaries, and sets.…
The guide distinguishes statistical independence, correlation, and cointegration, concepts that are often confused when assessing diversification and trading relationships. Independence means observing one variable does not change the probability…
The document is a brief event report about a talk on quantitative news trading at a Princeton–UChicago quantitative trading conference. The speaker’s topic was how news articles can be quantified and whether trading strategies based on news analytics can be…
This interview profile describes a trader and strategy researcher’s plan to help establish a high-frequency trading desk within a broader systematic trading fund. The intended focus is short holding periods in Asian and European markets, drawing on machine…
This interview presents a quantitative analyst’s path from engineering and statistics studies into quantitative finance, including work in high-frequency trading, banking, and strategy research. Its central lesson is to research markets carefully before…
The document explains the Aroon indicator’s two components, Aroon Up and Aroon Down, which track how recently a period’s highest high and lowest low occurred. It gives a lookback-based calculation and shows that the resulting values are expressed as…
This project describes an intraday Nifty strategy using five-minute data, a 200-period simple moving average, and a 50-period exponential moving average. It takes long or short positions when the index closes beyond both averages, with no position when 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…
This project describes a daily trend-following strategy for liquid Nifty 50 stocks, taking both long and short positions. MACD and SuperTrend generate directional signals: MACD crossovers can provide quicker entries, while SuperTrend helps identify the…
The document introduces Bayesian classification and applies a Bernoulli Naive Bayes model to a long-only stock trading example. The features are binary signals derived from RSI and the stochastic oscillator; the target labels whether the following day's…
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 introduces several ways to allocate weights in a multi-asset portfolio: equal weighting, risk parity, minimum variance, and Markowitz mean-variance optimization. It describes the intuition behind each method, including equal risk contributions in…
The project backtests a mechanical strategy of selling an at-the-money SPY straddle each week, using options with roughly 45–60 days to expiry and holding each position until expiration. It describes sourcing option prices, matching entry dates with expiries…
The article introduces probability as a way to reason about uncertain market outcomes. It explains event probabilities using analyst forecasts, distinguishes subjective judgments from estimates based on historical observation, and gives the rules that…
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…
The article introduces Ethereum as a blockchain platform for running smart contracts and decentralized applications. It explains Ether and gas, the Ethereum Virtual Machine, and examples of applications in decentralized finance and autonomous organizations.…
The article outlines a process for turning a market hypothesis into a live systematic strategy. It starts with a rule, such as buying when price is above an N day moving average, then uses backtesting to choose parameters such as the lookback period, stop…
The article describes a one day seasonal trade in the S&P 500: enter at the close on the US federal tax deadline and exit at the following day’s close. It cites research reporting an average annual return of about 0.5% since 1980, with less attractive…
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…
The article explains how to adapt Zipline’s CSV directory bundle to ingest daily Yahoo Finance files for a chosen market. It presents the bundle as an ETL pipeline: read files, normalize fields and dates, align records with a trading calendar, then write the…
This interview follows Xavier, an Australian IT architect with engineering and computer science training, as he moves from market research and investing to day trading and an interest in building an algorithmic trading desk. He describes exploring company…
This roundup introduces a range of options topics through summaries of ten articles and several additional strategy guides. It describes options as tools for transferring risk and outlines strategies such as butterflies, spreads, straddles, and calendar…
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…