To theoretically prepare for trading.camp by Ricki Heicklen I created a four week curriculum.

The goal is to develop a strong "quant-like" intuition without getting lost in the weeds of academic finance. The course is broken down into weekly modules with a mix of theory, practical exercises, and recommended resources.

This plan is built on a roughly 5-7 hour-per-week commitment. You can adjust the pace to fit your schedule.

Week 1: Core Probability and Thinking in Probabilities

• Objective: Internalize the fundamental concepts of probability and begin applying them to simple, real-world scenarios.
   
• Key Topics: Sample Space, Events, Calculating Probabilities, Conditional Probability, Independent Events.
   
• Resources:
  • Primary Textbook: A First Course in Probability by Sheldon Ross (Chapters 1, 2, and the beginning of 3).
     
  • Conceptual Reading: Thinking in Bets by Annie Duke (Part 1, especially the introduction to separating decision quality from outcome).
     
  • Online: Khan Academy's Probability and Statistics course.
     
• Weekly Breakdown:
  1. Theory (2 days): Read Chapters 1 & 2 of Sheldon Ross to understand the core axioms and calculations of probability. Use Khan Academy videos for reinforcement.
  2. Practice (1 day): Solve practice problems from the Ross textbook, focusing on understanding the distinction between different types of events.
  3. Application (2 days): Begin reading Thinking in Bets. Start a journal to practice "thinking in probabilities" by assigning estimated probabilities to real-world events you encounter.
  4. Review (2 days): Review any difficult concepts from the week to ensure a solid foundation.

Week 2: Mastering Expected Value

• Objective: Understand and be able to calculate the expected value of various scenarios, and use it as a primary decision-making tool.
   
• Key Topics: Expected Value ($E\left[X\right]=\sum xiP\left(xi\right)$), Decision-Making under Uncertainty, Risk vs. Reward.
   
• Resources:
  • Primary Textbook: A First Course in Probability by Sheldon Ross (Chapters 3 & 4).
     
  • Conceptual Reading: Thinking in Bets by Annie Duke (Part 2, on finding a statistical "edge").
     
  • Tools: Spreadsheet program (Excel, Google Sheets).
     
• Weekly Breakdown:
  1. Theory (2 days): Read the relevant sections on conditional probability and expected value in Ross's textbook. Master the expected value formula.
  2. Practical Application (1 day): Build a simple spreadsheet model to calculate the expected value of different trading scenarios.
  3. Scenario Analysis (2 days): Refine your spreadsheet model to compare different trading strategies with varying probabilities and outcomes, forcing you to think in terms of risk-reward.
  4. Review & Reflection (2 days): Reread sections of Thinking in Bets and connect the probabilistic decision-making ideas to your spreadsheet models.

Week 3: Introduction to Statistical Thinking

• Objective: Develop an intuitive understanding of statistical measures that are relevant to trading, such as volatility and correlation.
   
• Key Topics: Descriptive Statistics (Mean, Median, Std Dev), Distributions, Correlation, Limitations of Statistical Models.
   
• Resources:
  • Primary Textbook: Statistics and Data Analysis for Financial Engineering by Ruppert & Matteson (Chapters 1, 2, and 3): link
     
  • Conceptual Reading: Fooled by Randomness by Nassim Nicholas Taleb (Chapters 1 & 2).
     
  • Online: Yahoo Finance or another source for historical stock data.
     
• Weekly Breakdown:
  1. Theory (2 days): Read the introductory chapters of Ruppert & Matteson to understand descriptive statistics and the concept of correlation in a financial context.
  2. Practical Application (1 day): Download historical stock data and use your spreadsheet to calculate the mean, standard deviation, and correlation between different stocks.
  3. Distribution & Heuristics (2 days): Read the beginning of Fooled by Randomness. Use your data to visualize the distribution of returns and reflect on how it compares to an ideal "bell curve," connecting to Taleb's ideas on randomness.
  4. Review & Connection (2 days): Review the concepts of standard deviation and correlation, and think about how they combine with expected value to paint a more complete picture of a trading strategy.

Week 4: Heuristics, Edge, and Systematic Thinking

• Objective: Consolidate your learning and translate mathematical concepts into the "fast heuristic reasoning" required for trading.
   
• Key Topics: Risk-Reward Ratio, The Concept of "Edge," Systematic Thinking, Cognitive Biases.
   
• Resources:
  • Conceptual Reading: Thinking in Bets by Annie Duke and Fooled by Randomness by Nassim Nicholas Taleb.
     
  • Tools: Your trading journal.
     
• Weekly Breakdown:
  1. Risk-Reward (2 days): Read more of Thinking in Bets to understand how a good process can lead to a bad outcome. Think about how this applies to a trade with a positive expected value.
  2. Identifying an Edge (2 days): Read the rest of Fooled by Randomness. Internalize the idea that an "edge" is a statistically repeatable advantage.
  3. Systematic Thinking (1 day): Using an engineering mindset, write down a few simple trading rules. For each, think about how you could use your new mathematical intuition to evaluate its potential as a profitable strategy.
  4. Final Review & Synthesis (2 days): Review all of your notes, journal entries, and spreadsheet models. The goal of this week is not to learn new material, but to feel comfortable and confident in your ability to apply probabilistic and statistical thinking to trading scenarios.

Feedback or suggestions are very welcome!