Stock Exchanges Essentials - Automated Stock Analysis Engine

Participants should possess a working knowledge of basic fundamental analysis (e.g., P/E ratios, revenue growth) and technical analysis (e.g., moving averages, support/resistance).

By the end of the course, you will be able to approach any stock with a structured, repeatable methodology - one that tells you not just whether to trade, but when and how much. You will know how to assess a company's fundamental quality, read the technical signals that separate noise from opportunity, and size your positions in a way that protects your capital as rigorously as it pursues returns.

Beyond the analytical framework itself, you will gain hands-on mastery of a professional-grade tool that automates almost the entire process, from data retrieval to risk-adjusted position sizing. Rather than spending hours on each name, you will be able to run a comprehensive analysis in minutes, freeing you to focus on judgment and decision-making rather than mechanical number-crunching.

The course closes with a series of real case studies - stocks analyzed at actual decision points in early 2026 - so you can see the framework applied under genuine market conditions, not sanitized hindsight.

The course is organized in three parts that build on each other naturally.

The first part lays the intellectual foundation. It walks you through a complete stock analysis methodology structured around three questions every serious trader must answer: Is this trade valid? Is the timing right? How much should I risk? You will work through fundamental analysis, market regimes, relative strength, technical buy (and sell) signals, and a rigorous approach to risk management covering reward-risk ratios, correlation control, and position sizing.

The second part introduces a professional-grade Python program that automates almost the entire analysis pipeline, from raw data retrieval to fully computed, actionable outputs. You will learn to operate it with confidence - understanding what goes in, what comes out, and why the logic works - without any involvement in coding whatsoever. A validation framework ensures the tool behaves correctly across a range of market conditions, giving you full trust in what it tells you.

The third part puts everything to work on real stocks at real moments: Broadcom, TSMC, Bank of America, Nvidia, Meta, Amazon, Caterpillar, and Schneider Electric - all analyzed at specific dates in January and February 2026, capturing the actual information and uncertainty that existed at the time. These cases are not textbook examples cleaned up after the fact: they are the methodology in action, with all the ambiguity that live markets bring.

1 Reading the Market: How to Find, Evaluate, and Size a Trade

1.1 Trade Validity (The "What")
1.1.1 Fundamental Analysis
1.1.2 Market & Asset Regimes
1.1.3 Benchmark-Relative Strength & Moat Quality
1.2 Technical Setup (The "When")
1.2.1 Buy Signals
1.2.2 More about Price Structures & Regime Dynamics
1.2.3 Sell Signals
1.2.4 Event Check
1.3 Risk Management (The "How Much")
1.3.1 Capital Protection Framework
1.3.2 Reward–Risk Ratio
1.3.3 Exposure & Correlation Control
1.3.4 Target Price Computation Techniques
1.3.5 Changing Time Horizon: Trade versus Purchase Targets
1.3.6 Retrieving Analyst Consensus Targets from Yahoo

2 Your Edge at Scale: Putting a Professional Analysis Engine to Work

2.1 Comprehensive Stock-Analyzing Python Code
2.2 Mandatory Input-Data Files
2.2.1 Stock OHLCV CSV
2.2.2 Benchmark OHLCV CSV
2.2.3 Automated OHLCV Data Retrieval
2.3 Mandatory Input Parameters
2.4 Automated High-Impact Event Calendar Acquisition
2.5 Core Algorithm Execution
2.6 Code Validation Framework
2.6.1 Strategic Context
2.6.2 Technical Framework
2.6.3 Risk Governance

3 Live from the Market: Real Trades, Real Decisions

3.1 Assets in Focus
3.2 The AI Pipeline: The Technology and the Actors
3.3 Broadcom – January 21, 2026
3.4 TSMC – January 23, 2026
3.5 Bank of America – January 27, 2026
3.6 Nvidia – January 28, 2026
3.7 Meta – January 28, 2026
3.8 Amazon – January 31, 2026
3.9 Amazon – February 9, 2026
3.10 Caterpillar – February 10, 2026
3.11 Schneider Electric – February 10, 2026
3.12 TSMC – February 10, 2026

Effective training begins with the ability to set aside one's own expertise. This requires self-awareness, active reflection on one's explanations, and a deliberate effort to present concepts clearly and precisely without assuming prior knowledge.

No formal evaluation - self-assessment encouraged.

Participants receive a certificate of completion from Your Science - a ministerially authorized training provider, confirming their participation in comprehensive training on systematic stock analysis, risk management, and analytical engine operation.

The training is delivered via Microsoft Teams webinars, requiring no software installation for participants. Each session combines clear, instructor-guided learning with practical demonstrations. We provide personalized support: participants may submit questions by email and receive responses via email (or phone).

The course fee of €449 includes the 14-hour webinar, the training materials, and a complimentary 30-day (or 30-run) license to the cloud-based stock analysis engine (value €25+), activated when the platform goes live (launch planned for Q2 2026).

The next session will be scheduled in consultation with participants once the first five enrollments are confirmed.

Registration is now open at our website