Tietokirjasto

This document is a historical intraday dataset for the Dalian Commodity Exchange iron ore futures contract. Its rows report timestamped five-minute open, high, low, and close prices, along with volume, turnover, and open interest. The visible entries cover…

This script configures WtCtaOptimizer to run parameter searches for a Dual Thrust strategy on a China Financial Futures Exchange index futures contract. It fixes inputs such as bar count, bar interval, lookback days, and contract, then varies the strategy…

The example sketches a Python environment that connects a CTA backtesting engine to an agent-like training loop. It initializes a backtest, subscribes a strategy to five-minute bars, starts asynchronous execution, and advances the engine one step at a time.…

This example implements a tick-driven futures or securities strategy using the wtpy framework. It estimates a theoretical price from the best bid and ask, weighted by the quantities resting on the opposite sides of the book, then compares that estimate with…

This Python data-feed example adapts RQData historical futures data for use with the Wt trading framework. It maps standardized instrument codes to RQData symbols, requests bar or tick records, renames fields, and converts rows into Wt bar and tick…

This overview catalogs Python examples for the WonderTrader framework, including CTA strategies, futures and stock backtests, futures arbitrage, optimization, reinforcement learning, and high-frequency trading. It names Dual Thrust as a sample strategy used…

This Wtpy CTA strategy calculates upper and lower intraday trigger levels from recent highs, closes, and lows, scaled by configurable parameters around the current bar's open. When flat, it enters long on an upper-level break and, for non-stock instruments,…

This code describes a Dual Thrust style breakout strategy applied across a list of instruments. It calculates a reference range from prior bars using the highest high and close and the lowest low and close, then scales that range by separate parameters to…

This strategy tests whether two price series can support a mean-reverting spread. It applies augmented Dickey–Fuller tests to each series and their first differences, then uses a linear regression to estimate a hedge ratio and intercept when the series…

This code implements a Dual Thrust breakout strategy for a trading platform. It calculates a prior-period range from the highest highs, highest closes, lowest lows, and lowest closes across a configurable number of bars. The strategy scales that range with…

This configuration example sets up a CTA environment for a trading engine, including references to commodity, contract, holiday, session, fee, filter, execution, parser, and trader configuration files. It selects a trading session template and configures…

This trading system uses the JFatl_Digit_System indicator to generate signals when a bar closes with a colored state that differs from the previous bar, including a transition from an uncolored state. An Expert Advisor acts on those indicator transitions.…

The document demonstrates a workflow for backtesting a Dual Thrust strategy and reviewing its performance with Pyfolio. It configures a CTA backtest engine, sets the date range and storage location, and creates a strategy instance with a futures contract,…

This example configures a genetic algorithm optimizer to search parameters for a Dual Thrust futures strategy. It shows how to define an objective from average winning and losing trade results, assign fixed and variable parameters, set a backtest environment…