Monthly Portfolio Access

A structured system for allocation, signals, and rebalancing

This is for you if you want:

• A clear equity framework (stock recommended positions - equal weight)

• Ongoing portfolio updates and signals

• A structured system to remove guesswork

How It Works

1. Access the members area via web or IOS / Android App.

2. Follow the recommended stock holdings

3. Update every 1-6 months or year

4. Use the system as your core equity structure

5. This gives you a repeatable system to manage your portfolio.

Case Study: Multi-Model Portfolio with Tactical Risk Overlay

Objective

Evaluate whether combining fundamentally driven stock selection models with a tactical risk overlay can improve risk-adjusted returns relative to the S&P 500.

Framework

This portfolio integrates four independently tested strategies:

• Lutey Growth (CAN SLIM) – momentum + earnings acceleration
• Lutey Moderate Growth (ACS) – balanced growth exposure
• Lutey Value (Buffett) – quality + long-term compounding
• Lutey Value (Graham) – deep value / mean reversion

These models are combined into a single portfolio structure, then enhanced with a:

➡️ Weekly Tactical Capital Weighted Volume (CWV) Overlay
Used to dynamically adjust exposure based on market conditions.

Methodology

• Universe: U.S. equities (NYSE/Nasdaq)
• Timeframe: Backtested (1999–present) + live forward tracking
• Rebalancing:
  • Monthly (model updates)
  • Weekly (risk overlay adjustments)
• Benchmark: S&P 500 (SPY equivalent)
• Metrics Evaluated:
  • Total Return
  • Sharpe Ratio
  • Maximum Drawdown
  • Volatility (Standard Deviation)

Hypothesis

A diversified model framework combined with a tactical overlay should:

1. Capture upside from growth and value cycles
2. Reduce drawdowns during market stress
3. Improve consistency of returns over time

Results (Summary)

(Reference chart below)

• Higher total return vs. S&P 500
• Lower maximum drawdown during major downturns
• Improved Sharpe ratio, indicating better risk-adjusted performance
• Reduced volatility relative to standalone growth models

Key Insight

The edge is not just stock selection—it’s timing exposure.

While individual models perform well independently, the risk overlay acts as a governor, helping to:

• Scale down during weak market conditions
• Reallocate toward strength when trends confirm
• Avoid prolonged drawdowns that erode compounded returns

Why This Matters

Most portfolios fail not due to poor stock selection—but due to poor risk management during regime shifts.

This framework addresses both:

• What to own (multi-model selection)
• When to be exposed (tactical overlay)

Conclusion

Combining systematic stock selection with a rules-based risk overlay produces a more stable, adaptive portfolio capable of outperforming traditional benchmarks across multiple market environments.

Access the Model

Follow the live portfolio and see the current positioning. Self-directed tactical model ($379/month). 

$15,997 — AI Portfolio Mastery

 Build a Portfolio That Adapts to the Market—Automatically

Learn how to integrate Artificial Intelligence into your investment process and create a system that evolves with changing market conditions.

From static portfolios → to intelligent systems.

Program Name Ideas

Dr. Lutey Quant Portfolio Systems Lab

Build Your Own Technical Pattern + Macro Portfolio Engine

Advanced Portfolio Research Implementation Program

Core Positioning

This $14,997 program teaches investors, researchers, advisors, and advanced students how to move beyond simply reading strategy papers and instead build, test, and operate their own portfolio research system.

The program combines:

1. Technical chart pattern database construction
2. R-based pattern testing
3. Mathematica dissertation model implementation
4. Macro regime classification
5. Red / Yellow / Green market state logic
6. Automated stock selection from passing strategies
7. CAN SLIM, Graham, and Buffett-style portfolio screens

Checkout / Sales Page Copy

Advanced Portfolio Systems Implementation Program

Build Your Own Pattern Database, Macro Regime Model, and Automated Stock Selection Engine

This private implementation program is designed for serious investors, researchers, advisors, and advanced students who want to learn how to build a complete portfolio research system from the ground up.

Instead of simply following a model portfolio, you will learn how the research process works behind the scenes.

We will walk through how to use large financial datasets, such as CRSP-style stock return databases, to identify and test technical chart patterns across thousands of securities. You will learn how to run an R-based technical chart pattern program, organize the output into a usable pattern database, and understand how those results can be connected to portfolio selection rules.

The program also includes a walkthrough of the Mathematica-based framework originally developed through my dissertation research. This gives you a deeper look at how academic-style financial modeling can be translated into practical investment systems.

From there, we begin building the foundation of the full $15,000 system: understanding the macro environment.

You will learn how to organize macro inputs, evaluate whether the market environment is favorable or defensive, and classify the economy into a simple Red / Yellow / Green state. That regime state can then be used as a filter for deciding whether to be aggressive, cautious, or defensive with portfolio exposure.

Once the macro state is identified, the system then connects to strategy-based stock selection models, including:

CAN SLIM / Lutey Growth
Benjamin Graham / Lutey Hybrid Value
Warren Buffett / Lutey Value
Technical chart pattern screens
Macro-regime portfolio overlays

The goal is to help you understand how to build a repeatable research and portfolio process that can identify passing stocks, organize them by strategy type, and create a disciplined framework for portfolio construction.

What You Learn

You will learn how to:

Run the R program for technical chart pattern identification.

Use large stock databases to build a historical pattern library.

Understand how chart patterns can be tested across broad equity universes.

Work through the Mathematica framework from dissertation-level research.

Connect technical signals to portfolio selection rules.

Build a macro input dashboard.

Classify the market into Red, Yellow, or Green regimes.

Use macro conditions to determine whether portfolio exposure should be aggressive, moderate, or defensive.

Pull passing stocks from strategy screens such as CAN SLIM, Graham, and Buffett-style models.

Connect academic research, technical analysis, and portfolio implementation into one system.

Program Structure

Phase 1 — Technical Pattern Database

We begin with the R-based technical chart pattern program. You will learn how the data is structured, how the pattern logic is applied, and how the output can be organized into a usable research database.

Phase 2 — Mathematica Dissertation Framework

Next, we walk through the Mathematica program developed from my dissertation research. The focus is on understanding how deeper academic modeling can be translated into practical testing and portfolio construction.

Phase 3 — Macro Regime System

Then we build the beginning of the macro regime model. We identify the key input variables, organize them into a usable framework, and classify the market into a Red, Yellow, or Green state.

Phase 4 — Strategy Stock Selection

Once the market state is identified, we connect the regime framework to stock selection. This includes pulling passing stocks from CAN SLIM, Graham, Buffett, and other strategy-based models.

Phase 5 — Portfolio System Design

Finally, we combine the technical pattern database, macro model, and strategy screens into a repeatable research workflow that can be updated over time.

Investment

Advanced Private Implementation Program
$14,997

This is not a basic investing course. This is a private implementation program for people who want to understand how to build the research infrastructure behind technical, fundamental, and macro-driven portfolio systems.

Call to Action (CTA)

Enroll in the Advanced Portfolio Systems Implementation Program and learn how to build your own technical pattern database, macro regime model, and automated stock selection framework.