Stateful Long-Short with Exits

This trading strategy demonstrates the use of Quantiacs libraries to implement a stateful long-short strategy with conditional exits, evaluated on a day-by-day basis using the multipass backtester. This strategy is designed for the Quantiacs platform.

How to Run the Strategy

In an Online Environment

The strategy can be executed in an online environment using Jupiter or JupiterLab on the Quantiacs personal dashboard. To do this, clone the template in your personal account.

In a Local Environment

To run the strategy locally, you need to install the Quantiacs Toolbox.

Strategy Overview

This strategy uses a stateful approach to manage long and short positions with specific exit conditions. It operates on NASDAQ-100 stocks and employs various indicators to make trading decisions.

Key Features:

• Universe: NASDAQ-100 stocks
• Trading Logic: Positions are adjusted based on calculated signals, with conditional exits for taking profit, stopping loss, and day counting for short positions.
• Indicators Used: Simple Moving Average (SMA), Rate of Change (RoC), Average True Range (ATR), etc.
• State Management: Utilizes the Quantiacs state management system to maintain and update strategy state across different days.

Strategy Components:

1. Data Loading and Preparation:
   • Load stock data using qndata.stocks.load_ndx_data.
2. Strategy Function:
   • Define the strategy function which computes the weights (positions) based on signals and applies exit conditions.
   • The strategy adjusts weights according to the trading logic and exits conditions.
   • Conditional exits are applied to manage risks and capture profits.
3. State Management:
   • Use state to manage positions and exits dynamically.
   • Due to the state requirement, this strategy and the exits only work with the multipass backtester
4. Backtesting:
   • Use the multipass backtester to evaluate the strategy performance over historical data.
   • Analyze the results and visualize performance metrics.

Recommendations for Competitive Submissions:

• Limit the amount of exit functions to reduce computational demand.
• Keep in mind that exits that happen too often will also often trigger slippage penalties.
• Compare notebook statistics with the submission statistics to make sure there are no unintended interactions such as forward-looking.