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.
8,851 documents
This article introduces five technical indicators for assessing price trends, momentum, and volatility: moving averages, the Average Directional Index, Moving Average Convergence Divergence, the Relative Strength Index, and Bollinger Bands. It distinguishes…
Sourabh Sisodiya describes moving from discretionary trading based on technical analysis and candlestick patterns toward rule-based strategies after questioning whether his approach had a reliable edge. He presents backtesting as a way to assess a system and…
The article proposes evaluating automated strategies with two linked measures: win rate and the ratio of average winning to average losing trades. It defines expected edge as win probability times average win minus loss probability times average loss, and…
This article is a curated overview of technical analysis learning resources rather than a single trading method. It points readers toward material on using indicators, combining signals, and creating indicator-based strategies, along with guides to bullish…
The document explains how moving averages summarize a rolling window of prices and how traders compare a faster average with a slower one. A cross above the slower average is commonly treated as a potential bullish signal, while a cross below is treated as…
The article explains divergence as a mismatch between an asset’s price swings and an indicator or oscillator’s swings. It distinguishes regular bullish and bearish divergence, which may warn of a trend reversal, from hidden bullish and bearish divergence,…
The document explains Donchian Channels, which mark the highest high and lowest low over a chosen lookback window, with a middle line derived from the two bands. It describes three breakout strategies: long-short, long-only, and long-only entries filtered by…
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 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…
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 document introduces autocorrelation as the relationship between observations in a time series and their lagged values. It explains that positive autocorrelation can indicate persistence, while negative autocorrelation can suggest reversal, and describes…
The document outlines the classic bearish head and shoulders reversal pattern. It describes three successive peaks: an initial peak, a higher central peak, and a lower third peak. The neckline connects the intervening lows and is presented as a level to…
The article presents five broad practices for developing a trading strategy: define its edge and rules, test it against historical data, align it with the trader’s strengths and the strategy’s needs, refine parameters, and treat trading as an ongoing…
The article examines how fixed and trailing stop-loss rules affect a strategy’s return distribution. Its central point is that stopped trades remain part of the results: a stop can cut large losses while also closing positions that might have recovered or…
This guide introduces algorithmic trading for retail traders, explaining how software applies predefined rules to market data and places orders. It names moving-average crossovers, momentum, and mean reversion as beginner strategy examples. It also describes…
The article describes collecting cryptocurrency price and volume observations at minute intervals, storing them for analysis, and accounting for delays caused by fetching data across many coins. It then presents a simple trend-following strategy that uses…
This overview explains how standardized futures contracts differ from private forward agreements, and describes contract expiry, delivery months, tickers, margin, and profit and loss. It also introduces futures continuation series, which join successive…
The document introduces Zipline as an event-driven Python library for running trading algorithms and backtests. It outlines the algorithm structure: an initialization step stores the selected security, while a handler processes each market bar, places…
This interview traces a trader’s progression from executing commodity orders to coding trading systems and researching algorithmic strategies. The subject describes developing trend detection and momentum systems with position sizing, then building a…
This guide describes a trend-following method that calculates short- and long-window moving averages on the Nifty index, then uses their crossovers to signal long call option trades. It outlines a Python workflow: obtain index and option data, combine the…
Steven Downey describes using quantitative research to test investment beliefs rather than accepting them without evidence. His examples include examining whether gold behaves as an inflation hedge, whether oil and an energy company’s shares are related, and…
This project describes a simple web tool for exploring how rule-based trend-following strategies might perform before implementation. Users select a ticker, view closing prices and indicators such as simple moving averages and Bollinger Bands, then define…
This first-person account describes experiments with a volatility-triggered scalping strategy and a moving-average momentum strategy. The initial scalping rule used Average True Range to set a trading threshold and compared recent price action, but its…