Join Our Thriving user group: OBUG

The Owl Bundle User Group (OBUG) is a dynamic and supportive community of passionate traders who meet weekly via Zoom to explore the intricacies of the market. Our primary focus is on the continuous development and refinement of trading systems using Thinkorswim and EdgeRater. Each session is a hands-on experience, blending theory with practical application, ensuring that members gain actionable insights and sharpen their trading skills.

MEMBER TESTIMONIAL

“The OBUG group and the Applied Swing course have been outstanding, and the content continues to excel. One has to appreciate the instructors going above and beyond to bring all the insights together into strategies we can incubate,and to provide guidance on the nuances of which filters and exits to use for which objectives or under which conditions...” DB

Why Join OBUG?

Collaborative Learning: Engage with experienced traders who share your dedication to Dr. Ken Long’s methodologies. Our weekly Zoom meetings provide a platform for mutual learning and the exchange of advanced trading techniques using EdgeRater and Thinkorswim.
State-of-the-Art Tools and Techniques: Master the use of powerful tools like EdgeRater for backtesting and Monte Carlo analysis, and develop custom indicators on Thinkorswim based on Dr. Ken Long's methodologies. We guide you from basic tutorials to sophisticated strategies and multifactor analysis.
System Development and Optimization: Focus on the ongoing enhancement of trading systems. We rigorously analyze backtest results, optimize parameters, and perform Monte Carlo simulations to ensure your strategies are robust and effective.
Diverse Topics and Insights: Each meeting covers a wide array of subjects, providing a holistic understanding of various trading aspects. From market scans and strategy backtests to exit strategies and system development, our discussions are thorough and insightful.
How to sessions: Included are regular educational sessions on how to backtest, run Muiti-Factor Analysis, Batch Testing, Monte-Carlo Analysis using Dr Ken Long’s Swing Templates.

* TUTORIAL **

Step-by-Step Backtesting with EdgeRater

A step-by-step guide on trade simulation and backtesting using EdgeRater on Dr. Ken Long's trading strategies. It is designed to guide you how to backtest, conduct multifactor analysis, optimize parameters, and perform Monte Carlo analysis. The intent is to equip you with the knowledge to conduct your own trade simulations and backtests.

Objectives:

Understand EdgeRater's Simulation and Backtesting Capabilities: Gain a comprehensive understanding of how to set up and operate simulations and backtesting within EdgeRater, exploring its full range of features.
Apply Trading Strategies in Simulated Setups: Implement the trading strategies you've learned in simulated setups to evaluate their performance under diverse market conditions.
Analyze Backtesting and Simulation Results: Learn to effectively analyze the outcomes of your simulations and backtests to make informed decisions about strategy adjustments and refinements.

Scope:

Setting Up Simulations and Backtests: Detailed instructions on configuring EdgeRater for both trade simulations and backtesting, including how to select parameters and analyze different scenarios.
Running Simulations and Backtests: Step-by-step guidance on conducting simulations and backtests, featuring examples from common trading scenarios using Dr. Ken Long’s systems.
Result Analysis: Techniques for interpreting the results of trade simulations and backtests, focusing on performance metrics and areas for strategic improvement.
Practical Exercises: Engage in hands-on exercises that enable you to simulate and backtest trades using both pre-defined and custom strategies, aimed at reinforcing learning and building operational confidence.

Intent:

Participants will not only understand the theoretical aspects of trade simulation and backtesting but also be able to apply these concepts practically, providing a solid foundation for advanced trading strategy development.