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.
22 documents
This brief guide introduces several common Python errors and ways to begin diagnosing them. It illustrates how visually similar full-width punctuation can trigger a syntax error, how inconsistent indentation can raise an indentation error, and how a function…
This document outlines a per-contract result tracker and a portfolio-level PnL container. The contract tracker stores an opening position, observed trades, position changes, and cumulative long and short traded volumes and costs. It filters duplicate trade…
This example demonstrates a workflow for analyzing Bitcoin market data across multiple time intervals. It loads minute bars for a specified historical period, configures a transaction-rate assumption, and selects several technical indicators, including ATR,…
The document contains historical ADA/USDT candlestick observations at half-hour intervals. Each row records a timestamp, open, high, low, close, and traded volume, allowing a researcher to inspect price movement and activity or use the series as an input to…
This tutorial introduces Python strings as immutable sequences of characters and explains common operations for working with them. It covers concatenation, length, indexing and slicing, splitting text into lists, and searching with methods such as count,…
This example retrieves historical minute bars for a cryptocurrency symbol from a trading database, using an exchange, interval, and date range as query parameters. It then extracts each bar’s timestamp and closing price and plots the resulting price series…
The document contains hourly open, high, low, close, and volume observations for the ADA-USDT market. The visible records begin in early May 2018 and continue through the end of December 2018, with gaps in the displayed sequence. The fields support basic…
This document explains the structure of a historical trading strategy backtester. It loads bar or tick records over a selected date range, initializes a strategy with a warm-up period, then replays the remaining data. The engine tracks simulated orders and…
The document explains utilities for turning incoming trades into one-minute OHLCV bars and combining minute bars into larger time windows. It tracks price extremes, closing price, volume changes, and open interest, then sends completed bars through…
The document describes a graphical workflow for downloading historical bars, configuring a CTA strategy backtest, reviewing performance statistics, and inspecting trades on a candlestick chart. Data can come from a domestic market data service, an…
This guide explains a workflow for researching CTA strategies with historical market data. It covers obtaining and storing data, configuring a backtest with a strategy, date range, slippage, fees, contract multiplier, tick size, and starting capital, then…
This document provides four-hour candlestick observations for BSV/USDT. Each entry records a timestamp, open, high, low, close, and volume. The series shown runs from late November through the end of December 2018 and offers a coarser view of price movement…
This document presents 30-minute candlestick observations for BSV/USDT, with timestamps and open, high, low, close, and volume fields. The visible sample starts at the end of November 2018, includes records from early December, then skips ahead to late…
This document contains 30-minute candlestick records for BIX/USDT. Each row reports a timestamp, open, high, low, close, and trading volume. The visible records begin in July 2018 and resume near the end of December after an omitted portion, so they provide…
The document presents a workflow for evaluating individual trades from a Turtle-style strategy backtest on an hourly Bitcoin instrument. It configures a backtest with a historical date range, fees, slippage, contract size, tick size, and starting capital,…
This document describes a workflow for importing historical bar data from a CSV file into a trading database. The operator configures the input file, instrument symbol, exchange, bar interval, and the column names corresponding to timestamps and OHLCV…
This introductory lesson explains how to install and use Python through Anaconda. It describes Anaconda’s package and environment management features, including creating separate environments so projects can use different Python versions and dependencies. It…
This analysis workflow loads historical bars into a time-indexed table and plots closing prices to inspect gaps. It applies a Ljung–Box test for randomness, an Augmented Dickey–Fuller test for stationarity, and autocorrelation plots to examine serial…
This introductory document explains why Python comments help developers understand and maintain programs. It describes comments as notes attached to statements, code sections, functions, or variables, and says they can clarify a variable’s purpose for both…
This analysis workflow loads historical bars into a tabular dataset and plots closing prices to inspect gaps. It applies a Ljung–Box test for serial dependence, an augmented Dickey–Fuller test for stationarity, and autocorrelation and partial autocorrelation…
This module describes a real-time radar for calculating derived values from multiple contracts. Users define named rules with a Python mathematical expression and assign contract symbols to formula variables. Incoming tick data for any assigned contract…
This document demonstrates how to turn a backtest’s sequence of fills into completed trade records. It accumulates signed position, traded value, and price-based profit and loss until exposure returns to zero, then derives each trade’s duration, volume,…