📅 2024-11-16 — Session: Trading Simulation and Risk Analysis
🕒 19:15–20:10
🏷️ Labels: Python, Trading, Risk Management, Data Visualization, Simulation
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to develop and analyze a Python simulation tool for modeling trading account performance, focusing on risk management and trading strategies.
Key Activities
- Developed a Python simulation tool to model trading performance with customizable parameters such as win rate, gain-to-loss ratio, and risk per trade.
- Analyzed trading simulation outcomes, highlighting key statistics and implications for decision-making.
- Conducted a structured analysis of the simulation code, focusing on risk management strategies.
- Reviewed simulation results on risk and mean final balance, providing recommendations for optimal risk management.
- Analyzed risk-reward dynamics in trading strategies, emphasizing discipline and the balance between win rate and gain-to-loss ratio.
- Examined box plot distributions by risk levels to understand the impact on median outcomes and variability.
- Enhanced data visualization using Seaborn to improve clarity and aesthetics.
- Presented a DataFrame illustrating exponential growth and insights on compounding.
Achievements
- Successfully implemented and analyzed a trading simulation tool.
- Provided insights into risk management and trading strategies.
- Improved data visualization techniques for better clarity and understanding.
Pending Tasks
- Further refine the simulation tool for additional parameters and scenarios.
- Explore advanced visualization techniques to enhance data presentation.