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.
53 documents
The article compares five open-source tools for automating cryptocurrency trading: OctoBot, FreqTrade, Hummingbot, Jesse, and Superalgos. It describes their stated strengths, including strategy options, exchange compatibility, testing support, customization,…
This developer note explains two ways to inspect and work with a trading bot’s strategy tests. It says historical candles collected for backtesting are stored in SQLite files, which can be opened in a database browser to examine the available market data.…
This release note describes changes in OctoBot 1.0.2. ChatGPT strategy profiles can now be backtested for some settings using prompts precomputed from historical exchange-pair data downloaded by the service. The ChatGPT profile also shifts from daily trading…
This guide explains how OctoBot scripts obtain historical market data for backtesting. It describes requesting candle history by symbol and timeframe, with optional controls for the starting timestamp, exchange, and market type. The default exchange is…
This French-language overview compares five open-source tools for automating cryptocurrency trading: OctoBot, FreqTrade, Hummingbot, Jesse, and Superalgos. It describes their broad use cases and relative strengths, including configurable strategies, cloud or…
This guide explains how to run trading strategies against historical market data in OctoBot. The workflow is to select a profile, download data for the desired pairs and timeframes, run the backtest, and review the report. It describes how starting funds and…
This product guide explains a redesigned strategy interface with two parts: a viewer for examining and comparing strategies, and a creator for configuring new tests. The viewer presents performance metrics, behavior over time, and individual trade details.…
This product guide describes a strategy-design workflow for OctoBot. It separates strategy review from creation: the viewer presents performance metrics and trade details for analyzing and comparing runs, while the creator walks users through market…
This FAQ explains how OctoBot Cloud users can evaluate strategies and crypto baskets through paper trading with virtual funds, and says strategy performance is assessed periodically through historical backtesting. It notes that results vary with market…
This document explains OctoBot’s evaluator layer, which computes trading signals and routes them to strategies and trading modes. It distinguishes evaluators triggered by closed candles, forming candles, external social feeds, user scripts, and strategy…
This release note describes new features and fixes in OctoBot 1.0.4. Users can download strategies from OctoBot Cloud into a self-hosted bot, then configure them for different exchanges or assets and use the platform’s backtesting or strategy design tools to…
This OctoBot Script documentation page explains how to add charts to a strategy execution report through a plotting function. It describes naming a plotted indicator and supplying optional data for axes, labels, display mode, chart placement, color, and a…
This guide explains a basic workflow for turning TradingView conditions into automated orders. Alerts can be triggered by price levels, indicator thresholds, or Pine Script strategy signals. A receiving trading bot or intermediary can interpret alert…
The document introduces cryptocurrency trading bots as software that places trades according to preset rules. It describes three possible inputs: technical indicators such as moving averages and RSI, predictions based on historical data, and external trading…
This introductory guide outlines a workflow for training and backtesting a cryptocurrency trading agent using a scripting framework. It explains reinforcement learning as an approach in which an agent takes actions in a market environment and receives…
This documentation introduces OctoBot script, an early alpha Python framework for writing automated trading strategies with an interface compared to Pine Script. Its example uses RSI to identify buy entries: it computes the indicator over historical candle…
The document explains how to run strategy backtests in OctoBot: choose a profile, download historical market data, select a data file, run the simulation, and review performance summaries, charts, and individual trades. It describes how the starting…
This French guide explains how to access OctoBot cloud strategies from an OctoBot trading bot, starting with version 1.0.4. Users can find the strategies in the bot’s Community tab and use them in either simulated or live trading. The guide describes…
This introductory article explains cryptocurrency futures as contracts used to gain exposure to expected price movements without directly holding the underlying coins. It outlines long and short positioning, noting that short sellers aim to buy back at a…
This guide surveys ten cryptocurrency trading bot platforms, describing their strategy types, free-plan restrictions, and usability. It introduces bots as software that connects to exchanges and executes predefined rules, then compares offerings that include…
This guide explains how to obtain exchange history for OctoBot Script backtests and how to reuse previously downloaded data. The fetch request is configured with a trading pair and candle interval, with optional settings for the starting timestamp, exchange,…
This guide describes a workflow for exploring crypto investments: select a themed basket, compare available strategies, review each strategy's stated idea, and inspect its historical profit chart. Baskets group cryptocurrencies by a shared theme or…
The document describes how OctoBot script strategies read market data, evaluate signals, decide whether to trade, and create or modify orders. It contrasts two ways to implement a strategy. A precomputed approach can process the full available history once…
This guide explains how investors can explore themed cryptocurrency baskets and ready-made trading strategies on a cloud trading platform. Baskets group cryptocurrencies by a shared theme, such as market capitalization, so users can select a group without…