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.
157 documenten
This document contains daily open, high, low, close, and volume observations for Bitcoin priced in USDT during 2020. The rows are timestamped at 08:00 and show the market's changing price and trading volume through the year. The visible records include sharp…
This strategy builds 15-minute bars and uses Bollinger Bands to place stop entries at the upper band for a long position and the lower band for a short position when flat. It calculates the middle band as a simple moving average and also computes ATR. Once…
This strategy uses Bollinger Bands on 15-minute bars to place stop entries above the upper band and below the lower band while flat. It calculates a simple moving average as the middle band and uses that level as an exit trigger: long positions are sold when…
This introductory explanation presents functions as reusable blocks of code. It covers defining a function with def, choosing a descriptive name, calling the function, documenting it with a docstring, and returning a value. A market-data example retrieves…
This example describes a two-sided grid for a futures market. It tracks open buy and sell limit orders, checks their statuses, and after a fill places a replacement order on the opposite side at a configured percentage gap. It also maintains another order…
This document explains how to configure a trading application to store historical data and connect to an exchange. It compares SQLite, MongoDB, and MySQL settings, describes database fields such as driver, database name, host, port, and authentication…
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 example implements a spot grid that keeps one buy and one sell order working around the latest top of book. At timed intervals, when neither side has an outstanding order, it places orders offset from the best bid and ask by half the configured grid…
This example manages a spread position using configurable entry and exit prices, a maximum position, order pay-up, and an execution interval. On each spread update, it checks whether the current time falls within the configured trading window. Outside that…
This overview maps a CTA trading system into components for strategy templates, example strategies, backtesting, order conversion, live execution, and a graphical interface. It describes how live initialization can retrieve historical bars through a data…
This algorithm takes liquidity in the active leg of a multi-leg spread when the quoted spread reaches a configured limit. For a long spread, it checks whether the ask is at or below the target; for a short spread, it checks whether the bid is at or above it.…
This strategy uses the previous trading day’s high-to-low range to set stop-entry levels around the next day’s opening price. Separate multipliers scale the upward and downward thresholds. During the session, it chooses an entry side based on whether the…
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…
The document presents a bar-by-bar backtest using historical price data loaded from a CSV file. As each bar is added, the strategy calculates 20-period and 30-period moving averages after sufficient history is available. It enters a long position when the…
The document distinguishes syntax errors, logical errors, and exceptions that arise while a program runs. It uses simple examples to show that syntax mistakes can be identified before execution, while runtime problems such as division by zero or an undefined…
The document describes a pre-trade risk module that intercepts orders before they reach the trading API. Its controls include a cap on orders within a time window, a reset interval for that count, a maximum quantity per order, a daily limit on filled trades,…
This algorithm takes liquidity in the active leg of a multi-leg spread when the quoted spread price reaches a configured limit. For a long spread, it acts when the ask is at or below that limit; for a short spread, it acts when the bid is at or above it. It…
This strategy places paired long and short limit orders around the market, then rebuilds the grid after fills using the last filled price and a position-dependent step. It tracks net position and average entry price with a grid position calculator. When…
This implementation describes a streaming market-data process for a crypto derivatives instrument. After an authenticated connection, it subscribes to position and order-book topics. It initializes bid and ask maps from a snapshot, then applies incremental…
The document describes a spread-taking algorithm that waits for valid bid and ask volume, checks that prior orders have finished, and hedges any unbalanced passive legs before initiating another active-leg order. For a long spread, it takes the active leg…
This document describes a spot trading interface that retrieves balances and market data, submits buy and sell orders, and reports order status. Its execution workflow checks an order after submission and can cancel and replace an unfilled or partially…
The document describes a long and short strategy driven by fast and slow moving averages. It checks crossover conditions using completed-bar values, then opens a position or reverses an existing one. Position size is calculated from current account assets,…
The document explains a graphical workflow for maintaining historical market data. Users can download data from connected market data services or trading interfaces, import CSV files, inspect stored records, export selected ranges, and delete contract data.…
The document presents a rules-based BTCUSD trading example that derives three directional signals from recent price bars: RSI thresholds, CCI thresholds, and a comparison between fast and slow simple moving averages. It sums those signals and scales the…