Kunnskapsbibliotek

This guide describes capabilities for building and operating automated cryptocurrency strategies. It covers exchange order actions, market and position data access, indicator calculations, and example strategies. Its execution assistant can cancel unfilled…

This strategy combines a slower trend signal with faster entry and exit rules. It builds 15-minute bars and compares a fast simple moving average with a slow one; their ordering sets the directional trend. On 5-minute bars, it calculates RSI and opens a long…

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…

The document shows how a graphical trading application is assembled from an event engine, a main engine, exchange gateways, and several trading applications. The configured components include strategy execution, backtesting, data management and recording,…

The document demonstrates a WebSocket client that authenticates, subscribes to level-two order-book feeds, and maintains separate bid and ask maps for each symbol. It handles snapshot messages by loading initial levels, then applies inserts, updates, and…

The document implements a Turtle-style breakout strategy using Donchian channel levels for entries and exits, with ATR-based stop placement and position sizing. It tracks the trade’s high and low, moves stops as prices advance, and adds to positions at…

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,…

This spot grid strategy places paired buy and sell orders around the market, then rebuilds the grid after a fill using the filled order price and current bid and ask. Grid spacing and order size are configurable. A position calculator tracks net exposure and…

This strategy uses Bollinger Bands calculated from hourly closing prices to generate long and short trades. It enters long when the latest tick rises above the upper band and enters short when it falls below the lower band. A long is closed below the middle…

This example describes a WebSocket client that connects to a derivatives exchange, authenticates, subscribes to public order-book feeds, and requests private account-related streams after authentication. Its worker loop receives messages, calls event…

This guide describes an interactive Python workflow for quantitative analysis and automated trading through a script engine. Unlike a single-strategy workflow tied to one instrument or venue, the engine can connect to multiple interfaces and subscribe to…

This strategy uses two simple moving averages of closing prices to generate directional trades. It compares a faster average with a slower one on each bar and identifies a bullish crossover when the fast average moves above the slow average, or a bearish…

This spread strategy uses Bollinger Bands to enter and exit positions. After building spread bars and waiting for its array manager to initialize, it calculates the moving average and upper and lower bands over a configurable window. When flat, it opens a…