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.
1,116 documents
Weather Vane is described as an indicator that calculates a symbol’s average price and uses it to determine trend direction. The resulting direction can serve as a signal for taking a trade. The document recommends applying the indicator on a one-minute…
The document summarizes research on how high-frequency trading in equities affects liquidity in options on those stocks. The study combines Nasdaq HFT records with options transaction data and other market data for 103 stocks, then uses instrumental-variable…
This case study describes a hedge fund seeking to add digital asset strategies and the data infrastructure needed to research and trade them. Its requirements included real-time and historical market data, high-volume feeds for algorithm development and…
This overview catalogs Python examples for the WonderTrader framework, including CTA strategies, futures and stock backtests, futures arbitrage, optimization, reinforcement learning, and high-frequency trading. It names Dual Thrust as a sample strategy used…
This article explains triangular arbitrage using three currencies and temporarily inconsistent exchange rates. It first illustrates how to compare a directly quoted cross rate with a synthetic rate derived through two other currency pairs. If the three…
This meetup summary collects questions and answers on quantitative research, strategy development, and live trading. It points readers toward factor analysis, information coefficient interpretation, portfolio performance assessment, and resampling data to…
This article explains how commissions, fees, taxes, slippage, latency, spreads, liquidity, and market impact can alter a strategy’s backtest results. It contrasts fixed transaction-cost assumptions with linear, piecewise linear, and quadratic models. Fixed…
This article describes a high-frequency trading tactic that tries to profit from a large buyer who repeatedly raises a displayed bid. The trader first moves the market up by a tick, watches whether the buyer follows, and continues stepping prices higher if…
OrderNotify is an expert advisor watcher that emails information whenever a trade is opened or closed. The message is intended to include details about the affected trade, allowing a user to receive notifications from an expert advisor’s activity. To use it,…
The article argues that Rust can suit quantitative trading infrastructure where large data workloads, dense computation, concurrency, and low latency matter. It attributes this fit to Rust’s performance, memory and thread safety guarantees, and lack of…
This Chinese Q&A discusses basic factor research and strategy refinement. It recommends using a correlation calculation to compare factors and gives rough absolute-correlation bands for weak and strong relationships. It also suggests tracking factor…
Scalping seeks to accumulate small gains from brief price movements through frequent intraday trades. Positions may last seconds or minutes, and the approach relies on quick entries and exits, often using small time-frame charts, momentum indicators, support…
The article explains adverse selection in electronic limit order markets through the perspective of a market maker. A market maker posts bids and offers to earn the spread, but informed traders may trade against stale quotes when they anticipate price moves.…
This Chinese-language report summary examines intraday price, volume, and trading characteristics using minute data to build factors and compare their behavior in stocks and futures. The factor families include return-distribution statistics such as realized…
This research summary compares high-frequency factors built from minute data in stocks and futures. It groups signals into return-distribution measures, intraday volume patterns, price-volume relationships, order-flow measures, and trend strength. Reported…
This document describes a latency interface for high-frequency trading backtests, separating the delay from submitting an order to exchange processing from the delay between exchange processing and receiving a response. A constant model assigns fixed values…
The document presents a simplified high-frequency grid market-making approach inspired by GLFT. Rather than dynamically estimating order-arrival intensity to set spreads and skew, it uses recent price volatility to determine quote distance. Inventory is…
This overview compares day trading, position trading, swing trading, and scalping. Day traders close positions within the session. Position traders use longer charts to follow established trends over days or weeks, while swing traders seek opportunities as…
This research summary reviews stock-selection factors derived from tick-by-tick trade data, including large-buy share, buy-order concentration, intraday aggressive buying, and informed buying or selling measures. After orthogonalization, the factors…
This community post describes a data-engineering problem in market visualization: historical ticks can arrive after newer real-time ticks, causing a bar that appeared complete to change and making the latest candle visibly jump. The author proposes a minimal…
The document presents a ProRealTime indicator for estimating how many ticks occur per second from bars built from a specified number of ticks. It converts each bar’s open-time value into elapsed seconds, takes the difference between successive bar times, and…
This research summary describes two equity factors, jump beta and continuous beta, constructed from five-minute market data over the prior year. It reports that both factors showed stock-selection power across sample universes, including after industry…
This Chinese-language article describes a workflow for turning intraday trading data into daily stock-selection factors and using those factors in analysis and strategy development. Its example is a large-order-driven price-rise factor, alongside other…
The post asks whether it is possible to calculate trading volume during the final 15 seconds before a stock reaches its daily price limit. A reply says the calculation depends on how the limit-up event is defined and points to tick data as the relevant data…